Methods and compositions for quantifying immune cell nucleic acids

Abstract

Provided herein is an RNA analysis method for detecting and quantifying RNA (such as RNA from an immune cell or from a cancer cell) and / or for identifying and quantifying immune cell types from which the RNA originated. In some embodiments, expression levels of genes differentially expressed between healthy subjects and subjects having a disease or disorder are determined based on the RNA. In some embodiments, immune cell types from which the RNA originated are identified and quantified. Provided herein are also methods for determining the likelihood that a subject has the disease or disorder, such as a cancer.

Description

METHODS AND COMPOSITIONS FOR QUANTIFYING IMMUNE CELL NUCLEIC ACIDSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of priority of US Provisional Patent Application No. 63 / 510,026, filed June 23, 2023, which is incorporated by reference herein in its entirety for all purposes.FIELD OF THE INVENTION

[0002] The present disclosure provides methods related to analyzing RNA, such as immune cell RNA or RNA from a cancer cell. In some embodiments, the RNA is from a subject having or suspected of having a disease or disorder, such as cancer. In some embodiments, expression levels of genes differentially expressed between healthy subjects and subjects having the disease or disorder are determined based on the RNA. In some embodiments, immune cell types from which the RNA originated are identified and quantified.SEQUENCE LISTING

[0003] The present application contains a sequence listing that has been submitted electronically in XML format. Said XML copy, created on June 21, 2024, is named “01228-0036-00PCT.xml” and is 19,443 bytes in size. The information in the electronic format of the sequence listing is incorporated herein by reference in its entirety.INTRODUCTION AND SUMMARY

[0004] Invasive diagnostic procedures, including biopsies, are commonly used for detecting or diagnosing cancer, ulcers, liver diseases, infections, transplant rejections, and other diseases and disorders in which analysis of cells or tissue from a possible site of a malady are analyzed for relevant features. Detection of diseases and disorders based on analysis of body fluids (“liquid biopsies”), such as blood, is an intriguing alternative. A liquid biopsy is noninvasive, sometimes requiring only a blood draw. However, it has been challenging to develop accurate and sensitive methods for analyzing liquid biopsy material because the amount of nucleic acids released into body fluids is low and variable as is recovery of nucleic acids from such fluids in analyzable form.

[0005] An alternative or supplemental approach is to detect the signal linked to secondary effects of the presence of a disease such as cancer. One such secondary effect is the effect on RNA expression in other cells, including but not limited to cells involved in the immune response to tumorigenesis. In the presence of tumor cells, immune cells proliferate, differentiate, and potentially turn over at a higher rate than in a healthy subject. Such phenomena can result in changes in immune cell populations and the amount of RNA thereof in the blood. Therefore, a secondary RNA signal may be useful for detecting diseases or disorders, such as cancer, with improved sensitivity in at least some circumstances.

[0006] Furthermore, quantification of different blood cell types provides important information about a subject’s overall health in addition to information about disease states. The ability to distinguish between different cell types, including closely related cell types, can be important for distinguishing between different types of diseases and disorders. In a disease state, RNA from certain immune cell types may be elevated, and can be used as an indicator of the disease. In a number of genomic regions, the DNA methylation signatures in different immune cell types are distinguishable from myeloid cells and other immune cell types. Existing methods, such as complete blood counts and microarray-based profiling of differentially methylated regions, allow detection of many cell types but do not discriminate between certain types of immune cells, e.g., naive and activated lymphocytes, and therefore do not provide important information about the state of the subject’s immune system.

[0007] The methods herein provide an approach to quantify the levels of RNA derived from different immune cell types based on RNA sequencing data, e.g., generated by sequencing RNA and determining expression levels for a target gene set comprising genes that are differentially expressed in one or more immune cell types and / or in samples from subjects with a disease or disorder(such as cancer) relative to samples from healthy subjects, thus facilitating determining the presence, absence, or likelihood of the disease or disorder in the subject. Applications of this approach include, e.g., cancer detection by detecting tumor-induced immune cell proliferation.

[0008] The present disclosure aims to meet the need for improved analysis of RNA originating from different immune cell types, including rare immune cell types, such as activated lymphocytes or regulatory T cells. Improved differentiation of immune cell types over existing methods, such as complete blood count (CBC) or DNA methylation-based methods that do not discriminate between immune cell types, allows for more accurate detection of diseases anddisorders (diagnosis) and therefore improved treatments. Accordingly, the following exemplary embodiments are provided.

[0009] Embodiment 1 is a method of analyzing RNA in a sample from a subject, the method comprising: a) sequencing the RNA and determining expression levels for a target gene set comprising a plurality of target genes that are differentially expressed in a plurality of immune cell types and / or in samples from subjects with a disease or disorder relative to samples from healthy subjects; and b) determining(1) quantities of the immune cell types from which the RNA originated based on the expression levels; and / or(2) expression levels of the plurality of target genes; and c) determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types and / or the expression levels of the plurality of target genes.

[0010] Embodiment 2 is the method of embodiment 1, wherein the plurality of immune cell types comprises one or more, or each, of neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, eosinophils, T cells, CD4+ T cells, B cells, NK cells, megakaryocytes, CD8+ central memory cells, CD8+ effector memory cells, CD4+ central memory cells, CD4+ effector memory cells, immature neutrophils, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells, follicular helper T cells; regulatory T cells (Tregs), gamma delta T cells, resting NK cells, activated NK cells, M0 macrophages, Ml macrophages, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, and activated mast cells.

[0011] Embodiment 2.1 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises one or more, or each, of naive B cells, naive CD4+ T cells, CD8+ T cells, resting NK cells, Tregs, and monocytes.

[0012] Embodiment 3 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises one or more, two or more, or three or more of CD8+ T cells, resting CD4+ memory T cells, Tregs, and naive B cells.

[0013] Embodiment 4 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises CD8+ T cells, resting CD4+ memory T cells, Tregs, and naive B cells.

[0014] Embodiment 5 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises CD8+ T cells, resting CD4+ memory T cells, and T regs.

[0015] Embodiment 6 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises CD8+ T cells, Tregs, and naive B cells.

[0016] Embodiment 7 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises CD8+ T cells, resting CD4+ memory T cells, and naive B cells.

[0017] Embodiment 8 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises resting CD4+ memory T cells, Tregs, and naive B cells.

[0018] Embodiment 9 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises CD8+ T cells.

[0019] Embodiment 10 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises resting CD4+ memory T cells.

[0020] Embodiment 11 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises Tregs.

[0021] Embodiment 12 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises naive B cells.

[0022] Embodiment 13 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises neutrophils.

[0023] Embodiment 13.1 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises naive CD4+ T cells

[0024] Embodiment 13.2 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises resting NK cells.

[0025] Embodiment 13.3 is the method of embodiment 1 or embodiment 2, wherein the plurality of immune cell types comprises monocytes.

[0026] Embodiment 14 is the method of any one of the preceding embodiments, wherein the plurality of immune cell types comprises: a) T cells, B cells, and NK cells; b) neutrophils and lymphocytes; c) neutrophils, T cells, B cells, and NK cells;d) granulocytes and lymphocytes; or e) granulocytes, T cells, B cells, and NK cells.

[0027] Embodiment 15 is the method of any one of the preceding embodiments, wherein determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types comprises determining the levels of one or more, or each, of the plurality of immune cell types relative to total blood cells.

[0028] Embodiment 16 is the method of any one of the preceding embodiments, wherein determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types comprises determining the levels of one or more, or each, of the plurality of immune cell types relative to total white blood cells.

[0029] Embodiment 17 is the method of any one of the preceding embodiments, wherein determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types comprises determining the levels of one or more, or each, of T, B, and NK cells relative to all lymphocytes.

[0030] Embodiment 18 is the method of any one of the preceding embodiments, wherein determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types comprises determining relative proportions of neutrophils and lymphocytes.

[0031] Embodiment 19 is the method of any one of the preceding embodiments, wherein determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types comprises determining relative proportions of neutrophils and one or more, or each, of T cells, B cells, and NK cells.

[0032] Embodiment 20 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed in an activated cell type relative to the same cell type that is not activated.

[0033] Embodiment 21 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed in at least (a) a first cell type that is activated relative to the same first cell type that is not activated, and (b) a second cell type that is activated relative to the same second cell type that is not activated.

[0034] Embodiment 22 is the method of embodiment 20 or embodiment 21, wherein the activated cell type is neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, or eosinophils.

[0035] Embodiment 23 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed in neutrophils relative to a nonneutrophil cell type.

[0036] Embodiment 24 is the method of the immediately preceding embodiment, wherein the non-neutrophil cell type is one or more, or each, of a non-immune cell type, a non-granulocyte cell type, a myeloid non-granulocyte cell type, a lymphoid cell type, lymphocytes, T cells, B cells, and NK cells.

[0037] Embodiment 25 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed in lymphocytes relative to a non-lymphocyte cell type.

[0038] Embodiment 26 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed in a first cell type relative to a second cell type different from the first cell type, and the first cell type is neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, eosinophils, T cells, CD4+ T cells, B cells, NK cells, megakaryocytes, CD8+ central memory cells, CD8+ effector memory cells, CD4+ central memory cells, CD4+ effector memory cells, immature neutrophils, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells; follicular helper T cells; regulatory T cells (Tregs); gamma delta T cells; resting NK cells; activated NK cells, M0 macrophages, Ml macrophages, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, or activated mast cells.

[0039] Embodiment 27 is the method of the immediately preceding embodiment, wherein the second cell type is neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, eosinophils, T cells, CD4+ T cells, B cells, NK cells, megakaryocytes, CD8+ central memory cells, CD8+ effector memory cells, CD4+ central memory cells, CD4+ effector memory cells, immature neutrophils, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells; follicular helper T cells; regulatory T cells (Tregs); gamma delta T cells; resting NK cells; activated NK cells, M0 macrophages, Ml macrophages, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, or activated mast cells.

[0040] Embodiment 28 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed in a first cell type relative to a second cell type different from the first cell type, and the first cell type is B cells, T cells, or NK cells.

[0041] Embodiment 29 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed when the disease or disorder is present relative to when the disease or disorder is not present.

[0042] Embodiment 30 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed in the disease or disorder cells relative to healthy cells of the same cell type as the disease or disorder cells.

[0043] Embodiment 31 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed in the disease or disorder cells relative to healthy colon epithelial cells.

[0044] Embodiment 32 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed in the disease or disorder cells relative to a myeloid cell type or an erythroid cell type.

[0045] Embodiment 33 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes differentially expressed in colon epithelial cells relative to a myeloid cell type or an erythroid cell type.

[0046] Embodiment 34 is the method of any one of the preceding embodiments, wherein the plurality of target genes comprises genes having above-average expression variance in a training set comprising gene expression data from samples from healthy subjects and from subjects with the disease or disorder.

[0047] Embodiment 35 is the method of embodiment 34, wherein the genes having above- average expression variance comprise genes having an expression variance in the top 25th, top 20th, top 15th, top 10th, top 9th, top 8th, top 7th, top 6th, top 5th, top 4th, top 3rd, top 2nd, or top 1stpercentile of the genes of the training set.

[0048] Embodiment 36 is the method of embodiment 35, wherein the genes having above- average expression variance are genes with an expression variance ranking in the top 1000, top 750, top 500, top 250, top 200, top 150, top 100, top 90, top 80, top 70, top 60, top 50, top 40, top 30, top 25, top 20, top 15, top 10, or top 5 genes in the training set.

[0049] Embodiment 37 is the method of any one of the preceding embodiments, wherein one or more, a majority, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or all, of the target genes are protein-coding genes.

[0050] Embodiment 38 is the method of any one of the preceding embodiments, wherein the expression levels of the plurality of target genes are transcripts per million (TPM)-normalized, reads per kilobase million (RPKM)-normalized, or fragments per kilobase million (FPKM)- normalized.

[0051] Embodiment 39 is the method of any one of the preceding embodiments, wherein the expression levels of the plurality of target genes are mean-centered and / or are scaled to unit variance.

[0052] Embodiment 39.1 is the method of any one of the preceding embodiments, wherein the quantities of the immune cell types are mean-centered and / or are scaled to unit variance.

[0053] Embodiment 39.2 is method of any one of the preceding embodiments, wherein the quantities of the immune cell types are proportions of the immune cell types.

[0054] Embodiment 40 is the method of any one of the preceding embodiments, comprising: a) determining the presence or absence of the disease or disorder; or b) determining the likelihood of the disease or disorder.

[0055] Embodiment 41 is the method of any one of the preceding embodiments, wherein determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of sex on gene expression.

[0056] Embodiment 42 is the method of the immediately preceding embodiment, wherein compensating for effects of sex on gene expression comprises regressing out the effects of sex on gene expression.

[0057] Embodiment 43 is the method of any one of the preceding embodiments, wherein determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of sex on cell type quantity or cell type proportion.

[0058] Embodiment 44 is the method of the immediately preceding embodiment, wherein compensating for effects of sex on cell type quantity or cell type proportion comprises regressing out the effects of sex on cell type quantity or cell type proportion.

[0059] Embodiment 45 is the method of any one of the preceding embodiments, wherein the target genes comprise genes that are not differentially expressed according to sex.

[0060] Embodiment 46 is the method of the immediately preceding embodiment, wherein at least 50%, at least 60%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% of the target genes are not differentially expressed according to sex.

[0061] Embodiment 47 is the method of any one of the preceding embodiments, wherein the target genes were identified using a training set comprising samples from individuals of the same sex as the subject.

[0062] Embodiment 47.1 is the method of any one of the preceding embodiments, wherein the quantities of the immune cell types were identified using a training set comprising samples from individuals of the same sex as the subject.

[0063] Embodiment 48 is the method of any one of the preceding embodiments, wherein the subject is female.

[0064] Embodiment 49 is the method of any one of the preceding embodiments, wherein the subject is male.

[0065] Embodiment 50 is the method of any one of the preceding embodiments, wherein determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of age on gene expression.

[0066] Embodiment 51 is the method of the immediately preceding embodiment, wherein compensating for effects of age on gene expression comprises regressing out the effects of age on gene expression.

[0067] Embodiment 52 is the method of any one of the preceding embodiments, wherein determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of age on cell type abundance or cell type proportion.

[0068] Embodiment 53 is the method of the immediately preceding embodiment, wherein compensating for effects of age on cell type abundance or cell type proportion comprises regressing out the effects of age on cell type abundance or cell type proportion.

[0069] Embodiment 54 is the method of any one of the preceding embodiments, wherein the target genes comprise genes that are not differentially expressed according to age.

[0070] Embodiment 54.1 is the method of any one of the preceding embodiments, wherein the quantities of the immune cell types do not differ according to age.

[0071] Embodiment 55 is the method of embodiment 54, wherein at least 50%, at least 60%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, atleast 97%, at least 98%, at least 99%, or 100% of the target genes are not differentially expressed according to age.

[0072] Embodiment 55.1 is the method of the embodiment 54.1, wherein at least 50%, at least 60%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% of the immune cell types do not differ in quantity according to age.

[0073] Embodiment 56 is the method of any one of the preceding embodiments, wherein the target genes were identified using a training set comprising samples from individuals that, at the time of sample collection from each individual, were of an age that is within 1 year, within 2 years, within 3 years, within 4 years, within 5 years, within 6 years, within 7 years, within 8 years, within 9 years, within 10 years, within 11 years, within 12 years, within 13 years, within 14 years, or within 15 years of the age of the subject at the time of sample collection from the subject.

[0074] Embodiment 56.1 is the method of any one of the preceding embodiments, wherein the quantities of the immune cell types were identified using a training set comprising samples from individuals that, at the time of sample collection from each individual, were of an age that is within 1 year, within 2 years, within 3 years, within 4 years, within 5 years, within 6 years, within 7 years, within 8 years, within 9 years, within 10 years, within 11 years, within 12 years, within 13 years, within 14 years, or within 15 years of the age of the subject at the time of sample collection from the subject.

[0075] Embodiment 57 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more, or each, of GZMH, PATL2, FCRL6, ZNF600, IL10RA, DTHD1, PYHIN1, HDAC11, XCL1, GZMA, RAB37, ID2, SLC9A3R1, MOSPD3, TES, EML4, CD99, ACSL6, YPEL1, H2AC17, FGFBP2, TBX21, F2R, PTGDS, DDX3Y, SYNGR1, ZNF683, SERPTN86, PRSS23, ID2, SRSF2, PRR5, CST3, SHISA4, PLAC8, BRD2, BMF, NIPAL2, UTS2, RARS2, ZNF320, RBL2, CREB3L2, RNF38, CCDC88A, MEX3C, SLC38A11, COL19A1, PNPLA7, AFF3, STEAP1B, CELSR1, GRAPL, CBX5, AKAP6, EVL, CRISP3, BPI, MMP8, OLFM4, MPO, MR0H6, KDM5D, IDH2, ABB, S100A4, H2AC17, GIMAP4, PPP1CB, XAF1, RPL37, PTPRO, CD177, RPS13, NAIP, RPS12, ID2, SH3BP1, RAB37, PLEKHG3, AFDN, SLC9A3R1, FLNA, SSBP3, RHOB, LIPA, ISCA1, PAG1, DDX3X, KDM5C, PIM2, IL4R, ZFX, FCGR2B, KDM6A, SARAF, TTC39C, NCOR2,ATP5MD, ARHGD1A, TRAF5, SCAMP2, RPS26, GSTM4, MICAL3, TOMM20, SSBP3, RALGDS, ITGB1, DYRK1B, ARRB1, TRIM11, LFNG, PAXX, ACCS, and SLC2A6.

[0076] Embodiment 57.1 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more, or each, of GZMH, PATL2, FCRL6, ZNF600, IL 1 ORA, DTHD1, PYHIN1, HDAC11, XCL1, GZMA, RAB37, ID2, SLC9A3R1, MOSPD3, TES, EML4, CD99, ACSL6, YPEL1, and H2AC17.

[0077] Embodiment 57.2 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of FGFBP2, TBX21, F2R, PTGDS, DDX3Y, SYNGR1, ZNF683, SERPIN86, PRSS23, ID2, SRSF2, PRR5, CST3, SHISA4, PLAC8, and BRD2.

[0078] Embodiment 57.3 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of BMF, NIPAL2, UTS2, RARS2, ZNF320, RBL2, CREB3L2, RNF38, CCDC88A, MEX3C, SLC38A11, COL19A1, PNPLA7, AFF3, STEAP1B, CELSR1, GRAPL, CBX5, AKAP6, and EVL.

[0079] Embodiment 57.4 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of CRISP3, BPI, MMP8, OLFM4, MPO, MR0H6, KDM5D, IDH2, ABB, S100A4, H2AC17, GIMAP4, PPP1CB, XAF1, RPL37, PTPRO, CD177, RPS13, NAIP, RPS12.

[0080] Embodiment 57.5 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of ID2, SH3BP1, RAB37, PLEKHG3, AFDN, SLC9A3R1, FLNA, SSBP3, RHOB, LIPA, ISCA1, PAG1, DDX3X, KDM5C, PIM2, IL4R, ZFX, FCGR2B, KDM6A, and SARAF.

[0081] Embodiment 57.6 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of TTC39C, NCOR2, ATP5MD, ARHGD1A, TRAF5, SCAMP2, RPS26, GSTM4, MICAL3, TOMM20, SSBP3, RALGDS, ITGB1, DYRK1B, ARRB1, TRIM11, LFNG, PAXX, ACCS, SLC2A6.

[0082] Embodiment 57.7 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of GZMH, PATL2, FCRL6, ZNF600, IL10RA, DTHD 1 , PYHIN 1 , HD AC 11 , XCL 1 , and GZMA.

[0083] Embodiment 57.8 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of RAB37, ID2, SLC9A3R1, MOSPD3, TES, EML4, CD99, ACSL6, YPEL1, and H2AC17.

[0084] Embodiment 57.9 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of FGFBP2, TBX21, F2R, PTGDS, DDX3Y, SYNGR1, ZNF683, SERPIN86, PRSS23, and ID2.

[0085] Embodiment 57.10 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of SRSF2, PRR5, CST3, SHISA4, PLAC8, and BRD2.

[0086] Embodiment 57.11 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of BMF, NIPAL2, UTS2, RARS2, ZNF320, RBL2, CREB3L2, RNF38, CCDC88A, and MEX3C.

[0087] Embodiment 57.12 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of SLC38A11, COL19A1, PNPLA7, AFF3, STEAP1B, CELSR1, GRAPL, CBX5, AKAP6, and EVL.

[0088] Embodiment 57.13 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of CRISP3, BPI, MMP8, OLFM4, MPO, MR0H6, KDM5D, IDH2, ABB, and S100A4.

[0089] Embodiment 57.14 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of H2AC17, GIMAP4, PPP1CB, XAF1, RPL37, PTPRO, CD177, RPS13, NAIP, and RPS12.

[0090] Embodiment 57.15 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of ID2, SH3BP1, RAB37, PLEKHG3, AFDN, SLC9A3R1, FLNA, SSBP3, RHOB, and LIPA.

[0091] Embodiment 57.16 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of ISCA1, PAG1, DDX3X, KDM5C, PIM2, IL4R, ZFX, FCGR2B, KDM6A, and SARAF.

[0092] Embodiment 57.17 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of TTC39C, NCOR2, ATP5MD, ARHGD1A, TRAF5, SCAMP2, RPS26, GSTM4, MICAL3, and TOMM20.

[0093] Embodiment 57.18 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more (or each) of SSBP3, RALGDS, ITGB1, DYRK1B, ARRB1, TRIM11, LFNG, PAXX, ACCS, and SLC2A6.

[0094] Embodiment 58 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more, or each, of ICA1, CD38, ABCB4, TNFRSF17, RRP12,CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL18RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80, TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CD A, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, N0D2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MR0H7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, HLA- DOB, PGLYRP1, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIM1, HSD3B7, OSM, UPB1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYOIO, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, 0RM1, STON1, CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MY01B, LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1 , PDGFD, NMUR1, NBEA, OLR1, PTPRM, PAWR, ABCA13, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, L1CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.

[0095] Embodiment 59 is the method of the immediately preceding embodiment, wherein the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 of ICAl, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL I 8RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80,TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CDA, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, N0D2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MR0H7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, HLA-DOB, PGLYRP1, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIM1, HSD3B7, OSM, UPB 1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYOIO, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, 0RM1, STON1, CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MYO1B, LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB 1, SLC23A1, PDGFD, NMUR1, NBEA, OLR1, PTPRM, PAWR, ABCA13, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, LI CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.

[0096] Embodiment 60 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more, or each, of PGLYRP1, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIM1, HSD3B7, OSM, UPB 1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYOIO, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D,SEMA6B, PFKFB3, PAQR8, SH3PXD2B, F0SL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, 0RM1, and STONE

[0097] Embodiment 61 is the method of the immediately preceding embodiment, wherein the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 of PGLYRP1, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIM1, HSD3B7, OSM, UPB1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYO10, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, ORM1, and STONE

[0098] Embodiment 62 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more, or each, of ICA1, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL18RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80, TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CDA, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, NOD2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MROH7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, and HLA- DOB.

[0099] Embodiment 63 is the method of the immediately preceding embodiment, wherein the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 of ICAl, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL I 8RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80,TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CDA, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, N0D2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MR0H7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, and HLA-DOB.[000100] Embodiment 64 is the method of any one of the preceding embodiments, wherein the target genes comprise one or more, or each, of CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MYO IB, LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1, PDGFD, NMUR1, NBEA, OLR1, PTPRM, PAWR, ABCA13, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, L1CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.[000101] Embodiment 65 is the method of the immediately preceding embodiment, wherein the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 of CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MYO1B, LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPTB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1, PDGFD, NMUR1 , NBEA, OLR1, PTPRM, PAWR, ABCA13, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, L1CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.[000102] Embodiment 66 is the method of any one of the preceding embodiments, wherein the method comprises preparing cDNA from the RNA and ligating adapters to the cDNA, thereby producing adapter-ligated cDNA.[000103] Embodiment 67 is the method of the immediately preceding embodiment, wherein the adapters comprise barcodes.[000104] Embodiment 68 is the method of embodiment 66 or embodiment 67, wherein the adapter-ligated cDNA is amplified prior to the sequencing.[000105] Embodiment 69 is the method of any one of the preceding embodiments, further comprising enriching for at least one target region set from the RNA, cDNA prepared from the RNA, or a subsample thereof, comprising contacting the RNA, cDNA prepared from the RNA, or a subsample thereof with target-specific probes specific for the at least one target region set. [000106] Embodiment 70 is the method of any one of the preceding embodiments, further comprising a step of ribosomal RNA depletion.[000107] Embodiment 71 is the method of any one of the preceding embodiments, further comprising a step of globin mRNA depletion.[000108] Embodiment 72 is the method of any one of embodiments 1-69 or 71, further comprising a step of selection of polyadenylated RNA (poly(A)) transcripts.[000109] Embodiment 73 is the method of any one of the preceding embodiments, further comprising a step of RNA fragmentation prior to the sequencing.[000110] Embodiment 74 is the method of the immediately preceding embodiment, wherein the fragmenting provides RNA fragments of 25-400, 25-300, 25-200, 50-400, 50-300, 50-250, 50- 200, 100-400, 100-300, 100-200, 125-400, 125-300, 125-200, 125-175, 150-400, 150-300, 200- 400, 250-400, 300-400, 200-350, 200-300, 225-375, 250-350, or 275-325 base pairs in length. [000111] Embodiment 75 is the method of any one of the preceding embodiments, wherein the sample is a whole blood sample.[000112] Embodiment 76 is the method of any one of the preceding embodiments, wherein the RNA comprises RNA isolated from intact cells originally present in the sample.[000113] Embodiment 77 is the method of any one of the preceding embodiments, wherein the determining quantities of each of the plurality of immune cell types or sequencing comprises generating a plurality of sequencing reads, and wherein the method further comprises mapping the plurality of sequence reads to one or more reference sequences to generate mapped sequence reads, and processing the mapped sequence reads to determine the presence or absence of the disease or disorder in the subject, or the likelihood that the subject has the disease or disorder. [000114] Embodiment 77.1 is the method of any one of the preceding embodiments, further comprising dividing the sample from the subject into at least first and second subsamples, wherein the first subsample comprises RNA and the second subsample comprises DNA (optionally wherein the RNA is isolated from the first subsample and the DNA is isolated fromthe second subsample); or further comprising separately isolating DNA and RNA from the sample from the subject.[000115] Embodiment 77.2 is the method of embodiment 77.1, further comprising capturing at least an epigenetic target region set from the DNA, optionally wherein the capturing comprises contacting the DNA with a plurality of target-specific probes specific for members of the epigenetic target region set, thereby providing captured DNA.[000116] Embodiment 77.3 is the method of embodiment 77.2, further comprising determining a methylation level of the at least one of the plurality of epigenetic target regions.[000117] Embodiment 77.4 is the method of any one of embodiments 77.1-77.3, further comprising capturing sequence-variable target regions of the DNA, optionally wherein the capturing comprises contacting the DNA with a plurality of target-specific probes specific for the sequence-variable target regions.[000118] Embodiment 77.5 is the method of any one of embodiments 77.1-77.5, further comprising partitioning the DNA or a portion thereof into a plurality of further subsamples by contacting the DNA with an agent that recognizes methyl cytosine in the DNA, the plurality comprising a first subsample and a second subsample, wherein the first subsample comprises DNA with a methyl cytosine in a greater proportion than the second subsample.[000119] Embodiment 77.6 is the method of the immediately preceding embodiment, wherein the agent that recognizes methyl cytosine is a methyl binding reagent.[000120] Embodiment 77.7 is the method of the immediately preceding embodiment, wherein the methyl binding reagent is a methyl binding domain (MBD) protein or an antibody.[000121] Embodiment 77.8 is the method of any one of embodiments 77.6 or 77.7, wherein the methyl binding reagent specifically recognizes 5-methylcytosine.[000122] Embodiment 77.9 is the method of any one of embodiments 77.5-77.8, wherein the DNA of the first subsample and the DNA of the second subsample are differentially tagged.[000123] Embodiment 77.10 is the method of any one of embodiments 77.1-77.9, further comprising subjecting the DNA or one or more subsamples thereof to a procedure that affects a first nucleobase in the DNA differently from a second nucleobase, wherein the first nucleobase is a modified or unmodified nucleobase, the second nucleobase is a modified or unmodified nucleobase different from the first nucleobase, and the first nucleobase and the second nucleobase have the same base pairing specificity.[000124] Embodiment 77.11 is the method of the immediately preceding embodiment, wherein the first nucleobase is an unmodified cytosine and the second nucleobase is a modified cytosine, optionally wherein the modified cytosine is 5 -methyl cytosine or 5-hydroxymethylcytosine.[000125] Embodiment 77.12 is the method of any one of embodiments 77.10 or 77.11, wherein the procedure that affects a first nucleobase of the DNA differently from a second nucleobase of the DNA is a methylation-sensitive conversion.[000126] Embodiment 77.13 is the method of the immediately preceding embodiment, wherein the methylation-sensitive conversion is bisulfite conversion, oxidative bisulfite (Ox-BS) conversion, Tet-assisted bisulfite (TAB) conversion, APOBEC-coupled epigenetic (ACE) conversion, enzymatic methyl-seq (EM-seq) conversion, single-enzyme 5-methylcytosine sequencing (SEM-seq) conversion, or direct methylation sequencing (DM-seq).[000127] Embodiment 77.14 is the method of any one of embodiments 77.1-77.13, further comprising sequencing the DNA or a portion thereof.[000128] Embodiment 77.15 is the method of any one of embodiments 77.11-77.13, further comprising sequencing the DNA or a portion thereof in a manner that distinguishes the first nucleobase from the second nucleobase.[000129] Embodiment 77.16 is the method of any one of embodiments 77.1-77.15, further comprising contacting the DNA or at least one subsample thereof with at least one nuclease, optionally prior to the capturing or prior to the sequencing, further optionally wherein the at least one nuclease is at least one restriction enzyme.[000130] Embodiment 77.17 is the method of the immediately preceding embodiment, wherein the at least one restriction enzyme is at least one methylation-sensitive restriction enzyme (MSRE) and / or at least one methylation-dependent restriction enzyme (MDRE).[000131] Embodiment 77.18 is the method of any one of embodiments 77.1-77.17, wherein the method comprises ligating one or more adapters to the DNA, thereby producing adapter-ligated DNA.[000132] Embodiment 77.19 is the method of the immediately preceding embodiment, wherein the adapter-ligated DNA is amplified prior to the sequencing.[000133] Embodiment 77.20 is the method of any one of embodiments 77.14-77.19, wherein the sequencing comprises generating a plurality of sequencing reads, and wherein the method further comprises mapping the plurality of sequence reads to one or more reference sequences togenerate mapped sequence reads, and processing the mapped sequence reads to determine the likelihood that the subject has cancer or precancer.[000134] Embodiment 77.21 is the method of any one of embodiments 77.1-77.20, wherein the DNA is cfDNA.[000135] Embodiment 78 is the method of any one of the preceding embodiments, wherein the disease or disorder is a cancer or precancer.[000136] Embodiment 79 is the method of the immediately preceding embodiment, wherein the cancer or precancer is advanced adenoma (AA) and / or colorectal cancer (CRC).[000137] Embodiment 80 is the method of the immediately preceding embodiment, comprising: a) determining the presence or absence of AA; b) determining the likelihood of AA; c) determining the presence or absence of CRC; d) determining the likelihood of CRC; e) determining the presence or absence of AA and CRC; or f) determining the likelihood of AA and CRC.[000138] Embodiment 81 is the method of any one of embodiments 78-80, wherein the sample is obtained from a subject who was previously diagnosed with the cancer and received one or more previous cancer treatments, optionally wherein the sample is obtained at one or more preselected time points following the one or more previous cancer treatments.[000139] Embodiment 82 is the method of any one of embodiments 78-80, wherein the sample is obtained from a subject who was previously diagnosed with the cancer, and the sample is obtained from the subject before the subject receives a cancer treatment.[000140] Embodiment 83 is the method of any one of embodiments 80-82, further comprising determining a cancer recurrence score, optionally wherein a cancer recurrence status of the subject is determined to be at risk for cancer recurrence when the cancer recurrence score is determined to be at or above a predetermined threshold or the cancer recurrence status of the subject is determined to be at lower risk for cancer recurrence when the cancer recurrence score is below the predetermined threshold.[000141] Embodiment 84 is the method of the immediately preceding embodiment, further comprising comparing the cancer recurrence score of the subject with a predetermined cancer recurrence threshold, wherein the subject is classified as a candidate for a subsequent cancer treatment when the cancer recurrence score is above the cancer recurrence threshold or not acandidate for a subsequent cancer treatment when the cancer recurrence score is below the cancer recurrence threshold.[000142] Embodiment 85 is the method of any one of the preceding embodiments, further comprising evaluating or monitoring a response to a treatment in the subject.[000143] Embodiment 86 is the method of the immediately preceding embodiment, wherein the evaluating or monitoring the response to the treatment in the subject comprises comparing the expression levels for the target gene set comprising a plurality of target genes that are differentially expressed in a sample from the subject collected at at least a first time point and a sample from the subject collected at at least a second time point.[000144] Embodiment 87 is the method of embodiment 85, wherein the evaluating or monitoring the response to the treatment in the subject comprises comparing the quantities of the immune cell types in a sample from the subject collected at at least a first time point and a sample from the subject collected at at least a second time point.[000145] Embodiment 88 is the method of embodiment 86 or 87, wherein the first time point is a time point prior to administration of the treatment to the subject, and the second time point is a time point after the administration of the treatment to the subject.[000146] Embodiment 89 is the method of embodiment 86 or 87, wherein the first time point is a time point after administration of the treatment to the subject, and the second time point is a time point after the administration of the treatment to the subject and after the first time point.[000147] Embodiment 90 is the method of any one of the preceding embodiments, wherein the RNA comprises one or more of mRNA, IncRN A, or miRNA.[000148] In some embodiments, including but not limited to any one of the embodiments described above, the results of the methods disclosed herein are used as an input to generate a report. The report may be in a paper or electronic format. For example, quantities of immune cell types and / or expression levels of a plurality of target genes, as obtained by the methods disclosed herein, or information derived therefrom, can be displayed directly in such a report. Alternatively or additionally, diagnostic information or therapeutic recommendations which are at least in part based on the methods disclosed herein can be included in the report.[000149] The various steps of the methods disclosed herein may be carried out at the same or different times, in the same or different geographical locations, e.g. countries, and / or by the same or different people.[000150] Additional advantages will be set forth in part in the description which follows or may be learned by practice. The advantages will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims.BRIEF DESCRIPTION OF THE DRAWINGS[000151] FIGS. 1A-1D show receiver operating characteristic (ROC) curves for four models that were used for training from the following gene sets: (1) a cell type deconvolution (CTD) gene panel (approximately 400 genes) (FIG. 1A); (2) the top 500 variable genes based on variance (FIG. IB); (3) the top 100 differentially expressed genes for CRC (FIG. 1 C); and (4) the top 100 differentially expressed genes for AA (FIG. ID).[000152] FIG. 2 is a schematic diagram of an example of a system suitable for use with some embodiments of the disclosure.[000153] FIG. 3 shows a ROC curve for a model trained from a dataset comprising the compositions and relative proportions of certain cell types (naive B cells, memory B cells, plasma cells, CD8+ T cells, CD4+ T cells, Treg cells, NK cells, monocytes, macrophages, and dendritic cells) in samples from subjects that had advanced adenoma and samples from healthy subjects. In the ROC curve, cohort A included training set samples, and cohort B included test set samples (See Table 4).[000154] FIGS. 4A-4L show box and whisker plots illustrating within-sex differences in the proportions of particular cell types (FIG. 4A: Naive B cells fraction, cohort A; FIG. 4B: Naive B cells fraction, cohort B; FIG. 4C: Naive CD4 T cells fraction, cohort A; FIG. 4D: Naive CD4 T cells, cohort B; FIG. 4E: CD8 T cells fraction, cohort A; FIG. 4F: CD8 T cells fraction, cohort B; FIG. 4G: resting NK cells fraction, cohort A; FIG. 4H: resting NK cells fraction, cohort B; FIG. 41: regulatory T cells fraction, cohort A; FIG. 4J: regulatory T cells fraction, cohort B; FIG. 4K: monocytes fraction, cohort A; FIG. 4L: monocytes fraction, cohort B) between samples from subjects that had AA and samples from healthy subjects in both cohorts A and B (See Table 4). Cell proportions were mean-centered and scaled to obtain Z-scores for plotting.DETAILED DESCRIPTION OF CERTAIN EMBODIMENTS[000155] Reference will now be made in detail to certain embodiments of the invention. While the invention will be described in conjunction with such embodiments, it will be understood that they are not intended to limit the invention to those embodiments. On the contrary, the invention is intended to cover all alternatives, modifications, and equivalents, which may be included within the invention as defined by the appended claims.[000156] Before describing the present teachings in detail, it is to be understood that the disclosure is not limited to specific compositions or process steps, as such may vary. It should be noted that, as used in this specification and the appended claims, the singular form “a”, “an” and “the” include plural references unless the context clearly dictates otherwise. Thus, for example, reference to “a nucleic acid” includes a plurality of nucleic acids, reference to “a cell” includes a plurality of cells, and the like.[000157] Numeric ranges are inclusive of the numbers defining the range. Measured and measurable values are understood to be approximate, taking into account significant digits and the error associated with the measurement. Also, the use of “comprise”, “comprises”, “comprising”, “contain”, “contains”, “containing”, “include”, “includes”, and “including” are not intended to be limiting. It is to be understood that both the foregoing general description and detailed description are exemplary and explanatory only and are not restrictive of the teachings. [000158] Unless specifically noted in the above specification, embodiments in the specification that recite “comprising” various components are also contemplated as “consisting of’ or “consisting essentially of’ the recited components; embodiments in the specification that recite “consisting of’ various components are also contemplated as “comprising” or “consisting essentially of’ the recited components; and embodiments in the specification that recite “consisting essentially of’ various components are also contemplated as “consisting of’ or “comprising” the recited components (this interchangeability does not apply to the use of these terms in the claims).[000159] The section headings used herein are for organizational purposes and are not to be construed as limiting the disclosed subject matter in any way. In the event that any document or other material incorporated by reference contradicts any explicit content of this specification, including definitions, this specification controls.I. Definitions[000160] “Buffy coat” refers to the portion of a blood (such as whole blood) or bone marrow sample that contains all or most of the white blood cells and platelets of the sample. The buffy coat fraction of a sample can be prepared from the sample using centrifugation, which separates sample components by density. For example, following centrifugation of a whole blood sample, the buffy coat fraction is situated between the plasma and erythrocyte (red blood cell) layers. The buffy coat can contain both mononuclear (e.g., T cells, B cells, NK cells, dendritic cells, and monocytes) and polymorphonuclear (e.g., granulocytes such as neutrophils and eosinophils) white blood cells.[000161] As used herein, “fragment” or “fragmenting” refers to the breaking or separation of a biological component, such as a nucleic acid molecule (such as RNA) into two or more pieces. Fragmentation, such as RNA fragmentation, can occur spontaneously or can be induced intentionally, such as using standard laboratory procedures, such as described herein. RNA fragmentation can be performed, for example, to prepare RNA (such as RNA isolated from a sample comprising cells) for sequencing (such as RNA-seq).[000162] As used herein, “isolated” refers to a biological component (such as a nucleic acid molecule, protein, or cell) that has been substantially separated, produced apart from, or purified away from other components (for example, other components in a sample, cell, or organism in which the component naturally occurs). Nucleic acid molecules, proteins, or cells that have been “isolated” include those purified using standard purification methods. The term “isolated” or “purified” does not require absolute purity; rather, it is intended as a relative term. Thus, for example, an isolated biological component is one in which the biological component is more enriched in a preparation than the biological component is in its natural environment within a cell, organism, sample, or production vessel (for example, a cell culture system). For example, an isolated biological component can represent at least 50%, such as at least 70%, at least 80%, at least 90%, at least 95%, or greater, of the total biological component content of the preparation. [000163] As used herein, “leukapheresis” refers to a procedure in which white blood cells (leukocytes) are isolated from a sample of blood collected from a subject. Leukapheresis may be performed, e.g., obtain cells for research, diagnostic, prognostic, or monitoring purposes, such as those described herein. Thus, as used herein, a “leukapheresis sample” refers to a sample comprising leukocytes collected from a subject using leukapheresis.[000164] As used herein, “peripheral blood mononuclear cells” or “PBMCs” refers to immune cells having a single, round nucleus that originate in bone marrow and are found in the peripheral circulation. Such cells include, e.g., lymphocytes (T cells, B cells, and NK cells) as well as monocytes, and are isolated from blood samples (such as from a whole blood sample collected from a subject) using density gradient centrifugation.[000165] As used herein, a “combination” comprising a plurality of members refers to either of a single composition comprising the members or a set of compositions in proximity, e.g., in separate containers or compartments within a larger container, such as a multiwell plate, tube rack, refrigerator, freezer, incubator, water bath, ice bucket, machine, or other form of storage. [000166] The “capture yield” of a collection of probes for a given target set refers to the amount (e.g., amount relative to another target set or an absolute amount) of nucleic acid corresponding to the target set that the collection of probes captures under typical conditions. Exemplary typical capture conditions are an incubation of the sample nucleic acid and probes at 65°C for 10-18 hours in a small reaction volume (about 20 pL) containing stringent hybridization buffer. The capture yield may be expressed in absolute terms or, for a plurality of collections of probes, relative terms. When capture yields for a plurality of sets of target regions are compared, they are normalized for the footprint size of the target region set (e.g., on a per-kilobase basis). Thus, for example, if the footprint sizes of first and second target regions are 50 kb and 500 kb, respectively (giving a normalization factor of 0.1), then the RNA or cDNA corresponding to the first target region set is captured with a higher yield than RNA or cDNA corresponding to the second target region set when the mass per volume concentration of the captured RNA or cDNA corresponding to the first target region set is more than 0.1 times the mass per volume concentration of the captured RNA or cDNA corresponding to the second target region set. As a further example, using the same footprint sizes, if the captured RNA or cDNA corresponding to the first target region set has a mass per volume concentration of 0.2 times the mass per volume concentration of the captured RNA or cDNA corresponding to the second target region set, then the RNA or cDNA corresponding to the first target region set was captured with a two-fold greater capture yield than the RNA or cDNA corresponding to the second target region set.[000167] “Capturing” one or more target nucleic acids (such as RNA, or cDNA produced from the RNA) or one or more nucleic acids comprising at least one target region refers to preferentially isolating or separating the one or more target nucleic acids or one or more nucleicacids comprising at least one target region from non-target nucleic acids or from nucleic acids that do not comprise at least one target region.[000168] A “captured set” of nucleic acids or “captured” nucleic acids refers to nucleic acids that have undergone capture.[000169] As used herein, a “capture moiety” is a molecule that allows affinity separation of molecules, such as nucleic acids (such as RNA, or cDNA produced from the RNA), linked to the capture moiety from molecules lacking the capture moiety. Exemplary capture moieties include biotin, which allows affinity separation by binding to streptavidin linked or linkable to a solid phase or an oligonucleotide, which allows affinity separation through binding to a complementary oligonucleotide linked or linkable to a solid phase.[000170] As used herein, a “cell type” is a set of cells having a shared characteristic. For example, immune cell types can include immune cells of different origins, differentiation types, different activation types, or any combination of different origins, different differentiation types, and different activation types. Indeed, differentiation status and activation status can overlap and often change together in a given immune cell. For example, activation of an immune cell may induce differentiation of the cell. Immune cells of different activation types can include activated cells (such as cells activated by inflammatory cytokines or antigens), suppressive cells (such as T regulatory cells (Tregs), M2 macrophages, and others, or their subsets), or suppressed cells, such as cells suppressed by Tregs. Exemplary immune cell types include, but are not limited to, macrophages (including Ml macrophages and M2 macrophages); activated B cells (including regulatory B cells, memory B cells, and plasma cells); T cell subsets, such as CD4 central memory T cells, CD8 central memory T cells, naive-like T cells, naive T cells, and activated T cells (including cytotoxic T cells, regulatory T cells (Tregs), CD4 effector memory T cells, and CD8 effector memory T cells); immature myeloid cells (including myeloid-derived suppressor cells (MDSCs), low-density neutrophils, immature neutrophils, and immature granulocytes); and natural killer (NK) cells. Additional exemplary immune cell types include neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, eosinophils, T cells, CD4+ T cells, B cells, megakaryocytes, CD8+ central memory cells, CD4+ central memory cells, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells, follicular helper T cells, gamma delta T cells, resting NK cells; activated NK cells, M0 macrophages, resting dendritic cells, activated dendritic cells, restingmast cells, and activated mast cells. In some embodiments, cell types may be distinguished based on characteristics such as one or more cell surface markers, a genetic signature (such as expression (or expression level) of a particular gene or set of genes). As used herein, the term “based on,” such as in the context of determining quantities of immune cell types from which RNA originated “based on” expression levels of a target gene set comprising a plurality of target genes” does not require exclusivity. In other words, a determination of quantities of immune cell types from which RNA originated may be further based on one or more additional measures or features, such as one or more additional target regions.[000171] As used herein, a “cell cluster” or “cluster” is a plurality of related cell types, e.g., immune cell types. In some embodiments, the cell types within a cluster have similar RNA expression profiles, such as within a set of target genes.[000172] A “target region” refers to a nucleic acid targeted for identification and / or capture, for example, by using probes (e.g., through sequence complementarity). A “target region set” or “set of target regions” refers to a plurality of loci targeted for identification and / or capture, for example, by using a set of probes (e.g., through sequence complementarity).[000173] “Specifically binds” in the context of a primer, a probe, or other oligonucleotide and a target sequence means that under appropriate hybridization conditions, the primer, oligonucleotide, or probe hybridizes to its target sequence, or replicates thereof, to form a stable hybrid, while at the same time formation of stable non-target hybrids is minimized. Thus, a primer or probe hybridizes to a target sequence or replicate thereof to a sufficiently greater extent than to a non-target sequence, to ultimately enable capture or detection of the target sequence. Appropriate hybridization conditions are well-known in the art, may be predicted based on sequence composition, or can be determined by using routine testing methods (see, e.g., Sambrook et al., Molecular Cloning, A Laboratory Manual, 2nded. (Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, 1989, incorporated by reference herein).[000174] A nucleic acid (such as RNA) is “produced by a tumor” if it originated from a tumor cell. Tumor cells are neoplastic cells that originated from a tumor, regardless of whether they remain in the tumor or become separated from the tumor (as in the cases, e.g., of metastatic cancer cells and circulating tumor cells).[000175] As used herein, “precancer” or a “precancerous condition” is an abnormality that has the potential to become cancer, wherein the potential to become cancer is greater than the potential if the abnormality was not present, i.e., was normal. Examples of precancer include butare not limited to adenomas, hyperplasias, metaplasias, dysplasias, benign neoplasias (benign tumors), premalignant carcinoma in situ, and polyps. It should be noted that certain types of carcinoma in situ are recognized in the field as cancerous, e.g., Stage 0 cancer, as opposed to premalignant.[000176] The terms “or a combination thereof’ and “or combinations thereof’ as used herein refers to any and all permutations and combinations of the listed terms preceding the term. For example, “A, B, C, or combinations thereof’ is intended to include at least one of: A, B, C, AB, AC, BC, or ABC, and if order is important in a particular context, also BA, CA, CB, ACB, CBA, BCA, BAC, or CAB. Continuing with this example, expressly included are combinations that contain repeats of one or more item or term, such as BB, AAA, AAB, BBC, AAABCCCC, CBBAAA, CAB ABB, and so forth. The skilled artisan will understand that typically there is no limit on the number of items or terms in any combination, unless otherwise apparent from the context.[000177] A nucleic acid molecule is “differentially expressed” when the amount of one or more of its expression products (e.g., transcript, such as mRNA, and / or protein) is higher or lower in one sample (such as a sample from a subject that has a disease or disorder, such as a cancer) as compared to another sample (such as a sample from a subject that does not have the disease or disorder). Detecting differential expression can include measuring a change in gene (such as by measuring mRNA) or protein expression. An exemplary gene expression measurement method is RNA sequencing.[000178] As used herein, the term “regressing out” refers to use of a statistical procedure intended to remove the correlative influence of one variable on another, e.g., intended to remove the effects of a variable from an analysis. For example, the effect of sex on expression levels or quantities of immune cell types can be regressed out in certain embodiments disclosed herein. [000179] “ Or” is used in the inclusive sense, i.e., equivalent to “and / or,” unless the context requires otherwise.II. Exemplary MethodsA. Overview[000180] In some embodiments, methods disclosed herein comprise sequencing RNA (such as mRNA, IncRNA, and / or miRNA) isolated from a blood sample and determining expressionlevels for a target gene set comprising a plurality of target genes that are differentially expressed in a plurality of immune cell types and / or in samples from subjects with a disease or disorder relative to samples from healthy subjects. In some embodiments, the RNA to be sequenced is isolated from a blood sample, such as a buffy coat sample, a whole blood sample, a leukapheresis sample, or a PBMC sample. In some embodiments, the RNA to be sequenced is isolated from cells of a blood sample, such as a buffy coat sample, a whole blood sample, a leukapheresis sample, or a PBMC sample. In any of the embodiments of this disclosure, the RNA isolated from any type of sample comprising cells, including but not limited to a blood sample (e.g., a buffy coat sample, a whole blood sample, a leukapheresis sample, or a PBMC sample) may be RNA isolated from the cells of that sample. In some embodiments, methods disclosed herein comprise enriching for (e.g., using hybrid capture) at least one target region set from the RNA, cDNA prepared from the RNA (e.g., cDNA prepared from mRNA), or a subsample thereof, comprising contacting the RNA, cDNA prepared from the RNA, or a subsample thereof with target-specific probes specific for the at least one target region set. [000181] The expression levels of the target gene set (e.g., as determined by RNA sequencing (RNA-seq) of RNA isolated from a blood sample and optionally additional RNA, e.g., including analysis of data obtained from RNA-seq) can be used to determine quantities of each of a plurality of immune cell types from which the RNA originated. This can be useful, e.g., to detect the presence of cancer or precancer, or other conditions (e.g., infection, transplant rejection), in that the state of the immune system as reflected in the distribution of cell types that contribute to RNA isolated from a blood sample and optionally additional RNA can change as a result of such conditions. In some embodiments, the RNA isolated from a blood sample and optionally additional RNA originated from a tumor cell, and the cancer is advanced adenoma (AA) or colorectal cancer (CRC). In some embodiments, the RNA isolated from a blood sample and optionally additional RNA did not originate from a tumor cell, and instead originated from an immune cell.[000182] In some embodiments, the disease or disorder is a cancer or precancer. In some embodiments, the cancer is a solid tumor cancer, e.g., colorectal cancer, or a hematological cancer. In some embodiments, the cancer is a carcinoma or sarcoma. Without wishing to be bound by theory, cancers, including solid tumor cancers such as carcinomas and sarcomas, may cause changes to immune cell type distribution, including with respect to differentiated immune cell types and immune cell activation states, relative to the immune cell distribution in a healthysubject or subject that does not have cancer. Such changes may be detected in the methods herein and can be useful in detecting cancer as well as determining cancer prognosis and / or treatment options.[000183] Some embodiments of the present disclosure comprise steps of isolating RNA from a sample, e.g., a blood sample. Other sample types that include immune and / or cancer-derived cells (e.g., a whole blood sample, a buffy coat sample, a leukapheresis sample, or a peripheral blood PBMC sample) may also be used in embodiments of the disclosed methods. The RNA may be isolated from the cells of any such sample, such as using a method described herein. [000184] The disclosed methods can be combined with analysis of one or more additional biomarkers. In some embodiments, the disclosed methods are combined with one or more methods, such as but not limited to, methods for assessing DNA methylation patterns, DNA mutations (such as somatic mutations), nucleic acid fragmentation patterns, non-coding RNA (such as micro RNAs (miRNAs), ribosomal RNAs, transfer RNAs, small nucleolar RNAs (snow RNAs), and / or small nuclear RNAs (snRNAs)) levels, and / or levels, cellular locations, and / or structural modifications of one or more proteins (such as in a sample from a subject). In some embodiments, the disclosed methods are combined with one or more analyses of genetic variations including mutations, rare mutations, indels, rearrangements, copy number variations, transversions, translocations, recombinations, inversion, deletions, aneuploidy, partial aneuploidy, polyploidy, chromosomal instability, chromosomal structure alterations, gene fusions, chromosome fusions, gene truncations, gene amplification, gene duplications, chromosomal lesions, DNA lesions, abnormal changes in nucleic acid chemical modifications, abnormal changes in epigenetic patterns, and / or abnormal changes in nucleic acid 5- methylcytosine.[000185] Some embodiments of the disclosed methods further comprise dividing a sample from a subject into at least first and second subsamples, wherein the first subsample comprises RNA and the second subsample comprises DNA (optionally wherein the RNA is isolated from the first subsample and the DNA is isolated from the second subsample). Some embodiments of the disclosed methods further comprise separately isolating DNA and RNA from the sample from the subject. In some embodiments, the methods further comprise capturing at least an epigenetic target region set from the DNA, as described elsewhere herein. In particular embodiments, the capturing comprises contacting the DNA with a plurality of target-specific probes specific for members of the epigenetic target region set, thereby providing captured DNA. Someembodiments of the disclosed methods further comprise determining a methylation level of the at least one of the plurality of epigenetic target regions. In some embodiments, sequence-variable target regions of the DNA are also (or alternatively) captured. In some such embodiments, the capturing comprises contacting the DNA with a plurality of target-specific probes specific for the sequence-variable target regions.[000186] In some embodiments, the DNA or a portion thereof is partitioned into a plurality of further sub samples by contacting the DNA with an agent that recognizes methyl cytosine in the DNA. In particular embodiments, the plurality comprises a first subsample and a second subsample, wherein the first subsample comprises DNA with a methyl cytosine in a greater proportion than the second subsample. In particular embodiments, the agent that recognizes methyl cytosine is a methyl binding reagent In particular embodiments, the methyl binding reagent is a methyl binding domain (MBD) protein or an antibody. In some embodiments, the methyl binding reagent specifically recognizes 5-methylcytosine. In some embodiments, DNA of a first subsample and DNA of a second subsample are differentially tagged.[000187] In some embodiments of the disclosed methods, the DNA or one or more subsamples thereof is subjected to a procedure that affects a first nucleobase in the DNA differently from a second nucleobase. In particular embodiments, the first nucleobase is a modified or unmodified nucleobase, the second nucleobase is a modified or unmodified nucleobase different from the first nucleobase, and the first nucleobase and the second nucleobase have the same base pairing specificity. In particular embodiments, the first nucleobase is an unmodified cytosine and the second nucleobase is a modified cytosine, optionally wherein the modified cytosine is 5- methylcytosine or 5 -hydroxymethylcytosine.[000188] In some embodiments, the procedure that affects a first nucleobase of the DNA differently from a second nucleobase of the DNA is a methylation-sensitive conversion. In particular embodiments, the methylation-sensitive conversion is bisulfite conversion, oxidative bisulfite (Ox-BS) conversion, Tet-assisted bisulfite (TAB) conversion, APOBEC-coupled epigenetic (ACE) conversion, enzymatic methyl-seq (EM-seq) conversion, single-enzyme 5- methylcytosine sequencing (SEM-seq) conversion, or direct methylation sequencing (DM-seq). [000189] In some embodiments, the DNA, or a portion thereof, is sequenced. In particular embodiments, the DNA or a portion thereof is sequenced in a manner that distinguishes the first nucleobase from the second nucleobase.[000190] Some embodiments of the disclosed methods further comprise contacting the DNA or at least one subsample thereof with at least one nuclease, such as prior to the capturing or prior to the sequencing. In some embodiments, the at least one nuclease comprises at least one restriction enzyme. In some embodiments, the at least one nuclease comprises at least one methylationsensitive restriction enzyme (MSRE) and / or at least one methylation-dependent restriction enzyme (MDRE).[000191] In some embodiments, the method further comprises ligating one or more adapters to the DNA, thereby producing adapter-ligated DNA. In particular embodiments, the adapter- ligated DNA is amplified prior to the sequencing.[000192] In some embodiments, the DNA sequencing comprises generating a plurality of sequencing reads, and wherein the method further comprises mapping the plurality of sequence reads to one or more reference sequences to generate mapped sequence reads, and processing the mapped sequence reads to determine the likelihood that the subject has cancer or precancer. [000193] In particular embodiments, the DNA is cfDNA.B. Target Gene Lists[000194] Embodiments of the present disclosure comprise sequencing RNA (such as RNA isolated from a blood sample) and determining expression levels for a target gene set. A target gene set comprises a plurality of target genes that are differentially expressed in a plurality of immune cell types and / or in samples from subjects with a disease or disorder (such as a cancer, such as CRC and / or AA) relative to samples from subjects that do not have the disease or disorder, e.g., healthy subjects (or relative to another control, such as a historical control or standard reference value or range of values (e.g., a group of subjects that represent baseline or normal values not associated with the disease or disorder or values that are associated with not having the disease or disorder)). Expression levels of the genes of the target gene set are determined. Additionally or alternatively, quantities of the immune cell types from which the RNA originated can be determined based on the expression levels of the genes of the target gene set, or on inferred levels of genes within each of a plurality of inferred cell types.[000195] In some embodiments, determining quantities of each of the plurality of immune cell types or sequencing comprises generating a plurality of sequencing reads, mapping the sequence reads to one or more reference sequences to generate mapped sequence reads. The mapped sequence reads can be processed to determine the presence or absence of a disease or disorder(such as a cancer, such as CRC and / or AA) in the subject, or the likelihood that the subject has the disease or disorder.1. RNA Extraction and Isolation[000196] RNA for use in the methods disclosed herein may be isolated from a blood sample or the cells of a sample comprising cells (such as a sample that includes immune and / or cancer- derived cells (e.g., a blood sample such as a whole blood sample, a buffy coat sample, a leukapheresis sample, or a peripheral blood PBMC sample)). General methods for RNA extraction and isolation (such as mRNA extraction and isolation) are known in the art and are disclosed in standard textbooks of molecular biology, including Ausubel et al., Current Protocols of Molecular Biology, John Wiley and Sons (1997). Methods for RNA extraction from paraffin embedded tissues are disclosed, for example, in Rupp and Locker, Lab Invest. 56:A67 (1987), and De Andres et al., BioTechniques 18:42044 (1995). In particular, RNA isolation can be performed using a purification kit, buffer set, and protease(s) from commercial manufacturers, such as PreAnalytix GmbH or Qiagen, according to the manufacturer’s instructions. For example, RNA can be extracted from whole blood samples using the PAXgene® Blood RNA Kit (PreAnalytix GmbH). Other commercially available RNA isolation kits include MasterPure™ Complete DNA and RNA Purification Kit (EPICENTRE®, Madison, WI), and Paraffin Block RNA Isolation Kit (Ambion, Inc.). Total RNA from tissue samples can be isolated using RNA Stat-60 (Tel-Test). RNA prepared from tumor tissue can be isolated, for example, by cesium chloride density gradient centrifugation.2. Library Preparation[000197] Following RNA extraction from a sample (such as a blood sample), a cDNA library is typically prepared in preparation for sequencing, e.g., as in RNA-Seq. In some embodiments, the cDNAs in a library, such as an RNA-Seq library, can comprise a cDNA insert flanked by adapter sequences, such as adapter sequences used for amplification and sequencing on a particular platform. Exemplary cDNA library preparation methods are discussed below; however, cDNA library preparation methods can vary depending on the RNA species under investigation, which can differ in size, sequence, structural features and abundance. One of ordinary skill in the art will be able to select cDNA library preparation methods suitable for cDNA library preparation using an RNA species of interest.a. RNA Depletion; Poly(A) Selection[000198] Ribosomal RNAs (rRNAs) are the most abundant RNA species in most cells. Globin mRNA is also abundant in certain cell types found in the blood. Thus, some embodiments of the present disclosure comprise a step of ribosomal RNA (rRNA) depletion and / or a step of globin mRNA depletion. Such steps can be performed, e.g., following RNA extraction from a sample, and prior to a step of RNA fragmentation or cDNA fragmentation, prior to a step preparing cDNA from the RNA, prior to a step of ligating adapters to the cDNA, and prior to a sequencing step. In some embodiments, the methods include a step of rRNA depletion. In other embodiments, the methods include a step of globin mRNA depletion. In yet other embodiments, the methods disclosed herein include both a step of rRNA depletion and a step of globin mRNA depletion.[000199] Any suitable rRNA depletion and / or globin mRNA depletion methods are of use in the present disclosure. One approach to eliminate rRNAs uses sequence-specific probes that can hybridize to rRNAs (Hrdlickova et al., Wiley Interdiscip Rev RNA.2017;8(l): 10.1002 / wrna.1364). Unwanted rRNAs or their cDNAs are hybridized with biotinylated DNA or locked nucleic acid (LNA) probes, followed by depletion with streptavidin beads. Alternatively, rRNAs can be targeted by anti-sense DNA oligos and digested by RNase H, a method also known as probe-directed degradation (PDD). Another approach for rRNA reduction uses specific, not-so-random (NSR) primers that bind to the RNA molecules of interest during reverse transcription, thus avoiding reverse transcription of the rRNAs. For example, a method known as Ovation RNA-Seq (NuGen) uses hexamer or heptamer primers whose sequences are not present in rRNAs. In addition to sequence-based approaches, some methods take advantage of certain features of rRNAs for their elimination. The CoT-hybridization method is based on heat denaturation, re-annealing, and selective degradation by a duplex-specific nuclease (DSN). Double-stranded cDNAs from abundant sequences are preferentially degraded because of their more rapid annealing kinetics compared to less abundant ones. Selective degradation has also been achieved using the enzyme terminator 5 ’-phosphate-dependent exonuclease (TEX), which recognizes RNA molecules with 5 ’-monophosphate, as with rRNAs and tRNAs. Further, commercial kits are available for rRNA and globin mRNA depletion, including, e.g., the Watchmaker Genomics RNA Library Prep Kit with Polaris Depletion.[000200] Other embodiments of the present disclosure comprise a step of poly(A) selection.Such a step can be performed, e.g., following RNA extraction from a sample, and prior to a step of RNA fragmentation or cDNA fragmentation, prior to a step preparing cDNA from the RNA, prior to a step obligating adapters to the cDNA, and prior to a sequencing step. In eukaryotic organisms, most protein coding RNAs (mRNAs) and many long noncoding RNAs (IncRNAs) (>200 nt) comprise a poly(A) tail (“polyadenylated RNAs”). The poly(A) tail may be used to enrich for polyadenylated RNAs from total cellular RNA, in which polyadenylated RNAs may account for approximately 1-5% of total cellular RNA (Hrdlickova et al., Wiley Interdiscip Rev RNA. 2017;8(l): 10.1002 / wrna.l364). Exemplary poly(A) selection methods include, but are not limited to, use of magnetic or cellulose beads coated with oligo-dT molecules. Alternatively, poly adenylated RNAs can be selected using oligo-dT priming for reverse transcription (RT). Poly(A) selection may be combined with globin mRNA depletion. a. Fragmentation[000201] In some embodiments, methods disclosed herein comprise fragmenting RNA isolated from a sample (such as RNA isolated from a sample comprising cells, such as a whole blood sample, a buffy coat sample, a leukapheresis sample, or a PBMC sample), such as following poly(A) selection or rRNA and / or globin mRNA depletion. RNA fragmentation methods can include physical fragmentation, chemical fragmentation, and / or enzymatic fragmentation. Physical fragmentation methods include, but are not limited to, acoustic shearing, hydrodynamic shearing (such as sonication or point-sink shearing), needle shearing, and nebulization.Enzymatic fragmentation methods can include use of a ribonuclease (such as RNase III). RNA may also be fragmented using chemical shearing methods. Chemical fragmentation methods can include, but are not limited to, heat digestion of RNA in the presence of a divalent metal cation (such as magnesium or zinc). In some embodiments, the fragmenting provides RNA (such as mRNA) fragments of 25-400, 25-300, 25-200, 50-400, 50-300, 50-250, 50-200, 100-400, 100- 300, 100-200, 125-400, 125-300, 125-200, 125-175, 150-400, 150-300, 200-400, 250-400, 300- 400, 200-350, 200-300, 225-375, 250-350, or 275-325 base pairs in length.[000202] Alternatively, non-fragmented RNAs can be reverse transcribed, and the resultant cDNA can be fragmented. cDNA fragmentation methods can include physical fragmentation, chemical fragmentation, and / or enzymatic fragmentation. Physical fragmentation methods include, but are not limited to, acoustic shearing, hydrodynamic shearing (such as sonication orpoint-sink shearing), needle shearing, and nebulization. Enzymatic fragmentation methods can include use of a restriction endonuclease (such as a 4-cutter or 5-cutter restriction endonuclease, e.g., Alul, Dpnl, Eco47I, Haelll, Hpall, Mbo I, Msel, MspI, PspGI, Rsal, Sse9I, or TaqI), a nonspecific nuclease (e.g., micrococcal nuclease), or a transposase (for example, when insertion of an adapter into a fragmented double-stranded cDNA molecule is desired). cDNA may also be fragmented using chemical shearing methods. Chemical fragmentation methods can include, but are not limited to, heat digestion of cDNA in the presence of a divalent metal cation (such as magnesium or zinc). In some embodiments, the fragmenting provides cDNA fragments of 25- 400, 25-300, 25-200, 50-400, 50-300, 50-250, 50-200, 100-400, 100-300, 100-200, 125-400, 125-300, 125-200, 125-175, 150-400, 150-300, 200-400, 250-400, 300-400, 200-350, 200-300, 225-375, 250-350, or 275-325 base pairs in length. b. cDNA Preparation[000203] Some embodiments of the disclosed methods comprise preparing cDNA from RNA (such as RNA extracted from a blood sample), such as by reverse transcription of the RNA template into cDNA. Reverse transcription is generally followed by exponential amplification of the cDNA, e.g., in a PCR reaction. Two commonly used reverse transcriptases are avian myeloblastosis vims reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MMLV-RT). The reverse transcription step is typically primed using specific primers, random hexamers, or oligo-dT primers, depending on the circumstances and the goal of expression profiling. For example, extracted RNA can be reverse transcribed using a Gene Amp RNA PCR kit (Perkin Elmer, Calif., USA), following the manufacturer's instructions. The derived cDNA can then be used as a template in the subsequent amplification (e.g., PCR) reaction. In some embodiments, RNA is converted to cDNA using random priming, followed by second strand synthesis, end repair, and optional A-tailing. Adapters comprising barcodes can then be ligated to the cDNA, which is then amplified.[000204] Amplification is typically primed by primers that anneal or bind to primer binding sites in adapters flanking a cDNA molecule to be amplified. Amplification methods can involve cycles of denaturation, annealing and extension, resulting from thermocycling or can be isothermal as in transcription-mediated amplification. Other amplification methods include the ligase chain reaction, strand displacement amplification, nucleic acid sequence-based amplification, and self-sustained sequence-based replication.[000205] Although a PCR step can use a variety of thermostable DNA-dependent DNA polymerases, it typically employs the Taq DNA polymerase. TaqMan® PCR typically utilizes the 5'-nuclease activity of Taq or Tth polymerase to hydrolyze a hybridization probe bound to its target amplicon, but any enzyme with equivalent 5’ nuclease activity can be used. Two oligonucleotide primers are used to generate an amplicon typical of a PCR reaction. A third oligonucleotide, or probe, is designed to detect nucleotide sequence located between the two PCR primers. The probe is non-extendible by Taq DNA polymerase enzyme, and is labeled with a reporter fluorescent dye and a quencher fluorescent dye. Any laser-induced emission from the reporter dye is quenched by the quenching dye when the two dyes are located close together as they are on the probe. During the amplification reaction, the Taq DNA polymerase enzyme cleaves the probe in a template-dependent manner. The resultant probe fragments disassociate in solution, and signal from the released reporter dye is free from the quenching effect of the second fluorophore. One molecule of reporter dye is liberated for each new molecule synthesized, and detection of the unquenched reporter dye provides the basis for quantitative interpretation of the data.[000206] The primers used for the amplification are selected so as to amplify a unique segment of the gene of interest, such as RNA (such as mRNA) encoding a gene of a target gene set described herein. In some embodiments, expression of other genes is also detected, such as other known disease markers (such as known cancer markers) or housekeeping genes. Primers that can be used to amplify disease-related molecules are commercially available or can be designed and synthesized. In some examples, the primers specifically hybridize to a promoter or promoter region of a disease-related molecule. An alternative quantitative nucleic acid amplification procedure is described in U.S. Pat. No. 5,219,727. In this procedure, the amount of a target sequence in a sample is determined by simultaneously amplifying the target sequence and an internal standard nucleic acid segment. The amount of amplified cDNA from each segment is determined and compared to a standard curve to determine the amount of the target nucleic acid segment that was present in the sample prior to amplification. In some embodiments, the expression of a “housekeeping” gene or “internal control” can also be evaluated. These terms include any constitutively or globally expressed gene whose presence enables an assessment of mRNA levels provided herein. Such an assessment includes a determination of the overall constitutive level of gene transcription and a control for variations in RNA recovery. Exemplaryhousekeeping genes include tubulin, glyceraldehyde-3-phosphate-dehydrogenase (GAPDH), beta-actin, and 18S ribosomal RNA. c. Adapter Ligation or Addition[000207] In some embodiments, adapters are added to RNA or to cDNA prepared from the RNA. This may be done concurrently with an amplification procedure, e.g., by providing the adapters in a 5’ portion of a primer (where PCR is used, this can be referred to as library prep- PCR or LP-PCR). In some embodiments, adapters are added by other approaches, such as ligation. In some such methods, prior to capturing, first adapters are added to the nucleic acids by ligation to the 3’ ends thereof, which may include ligation to single-stranded cDNA. The adapter can be used as a priming site for second-strand synthesis, e.g., using a universal primer and a DNA polymerase. A second adapter can then be ligated to at least the 3’ end of the second strand of the now double-stranded molecule. In some embodiments, the first adapter comprises an affinity tag, such as biotin, and nucleic acid ligated to the first adapter is bound to a solid support (e.g., bead), which may comprise a binding partner for the affinity tag such as streptavidin. For further discussion of a related procedure, see Gansauge et al., Nature Protocols 8:737-748 (2013). In some embodiments, after adapter ligation, nucleic acids are amplified.[000208] Preferably, the adapters include different tags of sufficient numbers that the number of combinations of tags results in a low probability e.g., less than or equal to 5%, such as 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, or less than 0.1% of two nucleic acids with the same start and stop points receiving the same combination of tags. Adapters, whether bearing the same or different tags, can include the same or different primer binding sites, but preferably adapters include the same primer binding site.[000209] In some embodiments, following attachment of adapters, the nucleic acids are subject to amplification. The amplification can use, e.g., universal primers that recognize primer binding sites in the adapters.[000210] In some embodiments, the nucleic acids are linked at both ends to Y-shaped adapters including primer binding sites and tags. The molecules are amplified.[000211] In some embodiments, e.g., where cDNA has been subjected to a treatment that renders some or all of the cDNA single-stranded, a library preparation procedure appropriate for samples comprising single-stranded cDNA may be used. See, e.g., Gansauge & Meyer, Nature Protocols 8, 737-748 (2013). For example, biotinylated adapters can be ligated to 3’ ends of cDNA,followed by immobilization on streptavidin-coated beads. Complementary strands can be synthesized using a primer that anneals to the adapter and a DNA polymerase. A second adapter can then be attached to the now-double stranded molecule, e.g., by blunt-ended ligation. The biotinylated adapters may comprise any embodiments of tags and / or barcodes as described elsewhere herein. The molecules can then be amplified, e.g., via PCR, and the amplification products can be sequenced. d. Tagging[000212] “Tagging” RNA or cDNA molecules is a procedure in which a tag is attached to or associated with the RNA or cDNA molecules. Tags can be molecules, such as nucleic acids, containing information that indicates a feature of the molecule with which the tag is associated. For example, molecules can bear a sample tag (which distinguishes molecules in one sample from those in a different sample) or a molecular tag / molecular barcode / barcode (which distinguishes different molecules from one another (in both unique and non-unique tagging scenarios). For methods that involve a partitioning step, a partition tag (which distinguishes molecules in one partition from those in a different partition) may be included. In some embodiments, adapters comprising tags are added to cDNA molecules, such as cDNA prepared from RNA extracted from a blood sample (such as a huffy coat sample, a whole blood sample, a leukapheresis sample, a PBMC sample) and / or additional cDNA. In certain embodiments, a tag can comprise one or a combination of barcodes. As used herein, the term “barcode” refers to a nucleic acid molecule having a particular nucleotide sequence, or to the nucleotide sequence, itself, depending on context. A barcode can have, for example, between 10 and 100 nucleotides. A collection of barcodes can have degenerate sequences or can have sequences having a certain hamming distance, as desired for the specific purpose. So, for example, a molecular barcode can be comprised of one barcode or a combination of two barcodes, each attached to different ends of a molecule. Additionally or alternatively, for different partitions and / or samples, different sets of molecular barcodes, or molecular tags can be used such that the barcodes serve as a molecular tag through their individual sequences and also serve to identify the partition and / or sample to which they correspond based the set of which they are a member.[000213] In some embodiments, two or more partitions, e.g., each partition, is / are differentially tagged. In some embodiments, the partitions comprise cDNA prepared from RNA extracted from a sample comprising cells or a blood sample (such as a buffy coat sample, a whole blood sample,a leukapheresis sample, or a PBMC sample). In some embodiments, the partitions comprise additional cDNA, such as cDNA prepared from RNA extracted from a tumor sample. Tags can be used to label the individual polynucleotide population partitions so as to correlate the tag (or tags) with a specific partition. Alternatively, tags can be used in embodiments that do not employ a partitioning step. In some embodiments, a single tag can be used to label a specific partition. In some embodiments, multiple different tags can be used to label a specific partition. In embodiments employing multiple different tags to label a specific partition, the set of tags used to label one partition can be readily differentiated for the set of tags used to label other partitions. In some embodiments, the tags may have additional functions, for example the tags can be used to index sample sources or used as unique molecular identifiers (which can be used to improve the quality of sequencing data by differentiating sequencing errors from mutations, for example as in Kinde et al., Proc Nat’l Acad Sci USA 108: 9530-9535 (2011), Kou et al., PloS 0NE,W. eO 146638 (2016)) or used as non-unique molecule identifiers, for example as described in US Pat. No. 9,598,731. Similarly, in some embodiments, the tags may have additional functions, for example the tags can be used to index sample sources or used as non-unique molecular identifiers (which can be used to improve the quality of sequencing data by differentiating sequencing errors from mutations).[000214] In some embodiments, partition tagging comprises tagging molecules in each partition with a partition tag. After re-combining partitions (e.g., to reduce the number of sequencing runs needed and avoid unnecessary cost) and sequencing molecules, the partition tags identify the source partition. In some embodiments, the partition tags can serve as identifiers of the source partition and the molecule, i.e., different partitions are tagged with different sets of molecular tags, e.g., comprised of a pair of barcodes. In this way, the one or more molecular barcodes attached to the molecule indicates the source partition as well as being useful to distinguish molecules within a partition. For example, a first set of 35 barcodes can be used to tag molecules in a first partition, while a second set of 35 barcodes can be used tag molecules in a second partition.[000215] In some embodiments, after partitioning and tagging with partition tags, the molecules may be pooled for sequencing in a single run. In some embodiments, a sample tag is added to the molecules, e.g., in a step subsequent to addition of partition tags and pooling. Sample tags can facilitate pooling material generated from multiple samples for sequencing in a single sequencing run.[000216] Alternatively, in some embodiments, partition tags may be correlated to the sample as well as the partition. As a simple example, a first tag can indicate a first partition of a first sample; a second tag can indicate a second partition of the first sample; a third tag can indicate a first partition of a second sample; and a fourth tag can indicate a second partition of the second sample.[000217] While tags may be attached to molecules already partitioned based on one or more characteristics, the final tagged molecules in the library may no longer possess that characteristic. For example, while single stranded cDNA molecules may be partitioned and tagged, the final tagged molecules in the library are likely to be double stranded. Accordingly, the tag attached to molecule in the library typically indicates the characteristic of the “parent molecule” from which the ultimate tagged molecule is derived, not necessarily to characteristic of the tagged molecule, itself.[000218] As an example, barcodes 1, 2, 3, 4, etc. are used to tag and label molecules in the first partition; barcodes A, B, C, D, etc. are used to tag and label molecules in the second partition; and barcodes a, b, c, d, etc. are used to tag and label molecules in the third partition.Differentially tagged partitions can be pooled prior to sequencing. Differentially tagged partitions can be separately sequenced or sequenced together concurrently, e.g., in the same flow cell of an Illumina sequencer.[000219] Tags comprising barcodes can be incorporated into or otherwise joined to adapters. Tags can be incorporated by ligation, overlap extension PCR among other methods. i. Molecular tagging strategies[000220] Molecular tagging refers to a tagging practice that allows one to differentiate among cDNA molecules from which sequence reads originated. Tagging strategies can be divided into unique tagging and non-unique tagging strategies. In unique tagging, all or substantially all of the molecules in a sample bear a different tag, so that reads can be assigned to original molecules based on tag information alone. Tags used in such methods are sometimes referred to as “unique tags”. In non-unique tagging, different molecules in the same sample can bear the same tag, so that other information in addition to tag information is used to assign a sequence read to an original molecule. Such information may include start and stop coordinate, coordinate to which the molecule maps, start or stop coordinate alone, etc. Tags used in such methods are sometimes referred to as “non-unique tags”. Accordingly, it is not necessary to uniquely tag every moleculein a sample. It suffices to uniquely tag molecules falling within an identifiable class within a sample. Thus, molecules in different identifiable families can bear the same tag without loss of information about the identity of the tagged molecule.[000221] In certain embodiments of non-unique tagging, the number of different tags used can be sufficient that there is a very high likelihood (e.g., at least 99%, at least 99.9%, at least 99.99% or at least 99.999% that all cDNA molecules of a particular group bear a different tag. It is to be noted that when barcodes are used as tags, and when barcodes are attached, e.g., randomly, to both ends of a molecule, the combination of barcodes, together, can constitute a tag. This number, in term, is a function of the number of molecules falling into the calls. For example, the class may be all molecules mapping to the same start-stop position on a reference genome. The class may be all molecules mapping across a particular genetic locus, e.g., a particular base or a particular region (e.g., up to 100 bases or a gene or an exon of a gene). In certain embodiments, the number of different tags used to uniquely identify a number of molecules, z, in a class can be between any of 2*z, 3*z, 4*z, 5*z, 6*z, 7*z, 8*z, 9*z, 10*z, 11 *z, 12*z, 13*z, 14*z, 15*z, 16*z, 17*z, 18*z, 19*z, 20*z or 100*z (e.g., lower limit) and any of 100,000*z, 10,000*z, 1000*z or 100*z (e.g., upper limit).[000222] For example, in a sample of about 5 ng to 30 ng of cDNA, one expects around 3000 molecules to map to a particular nucleotide coordinate, and between about 3 and 10 molecules having any start coordinate to share the same stop coordinate. Accordingly, about 50 to about 50,000 different tags (e.g., between about 6 and 220 barcode combinations) can suffice to uniquely tag all such molecules. To uniquely tag all 3000 molecules mapping across a nucleotide coordinate, about 1 million to about 20 million different tags would be required.[000223] Generally, assignment of unique or non-unique tags barcodes in reactions follows methods and systems described by US patent applications 20010053519, 20030152490, 201 10160078, and U.S. Pat. No. 6,582,908 and U.S. Pat. No. 7,537,898 and US Pat. No. 9,598,731. Tags can be linked to sample nucleic acids randomly or non-randomly.[000224] The unique tags may be loaded so that more than about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 50, 100, 500, 1000, 5000, 10000, 50,000, 100,000, 500,000, 1,000,000, 10,000,000, 50,000,000 or 1,000,000,000 unique tags are loaded per sample. In some cases, the unique tags may be loaded so that less than about 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 50, 100, 500, 1000, 5000, 10000, 50,000, 100,000, 500,000, 1,000,000, 10,000,000, 50,000,000 or 1,000,000,000 unique tags are loaded per sample. In some cases, the average number of unique tags loaded per sample is lessthan, or greater than, about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 50, 100, 500, 1000, 5000, 10000, 50,000, 100,000, 500,000, 1,000,000, 10,000,000, 50,000,000 or 1,000,000,000 unique tags per sample.[000225] A preferred format uses 20-50 different tags (e.g., barcodes) ligated to both ends of target nucleic acids. For example, 35 different tags (e.g., barcodes) ligated to both ends of target molecules creating 35 x 35 permutations, which equals 1225 for 35 tags. Such numbers of tags are sufficient so that different molecules having the same start and stop points have a high probability (e.g., at least 94%, 99.5%, 99.99%, 99.999%) of receiving different combinations of tags. Other barcode combinations include any number between 10 and 500, e.g., about 15x15, about 35x35, about 75x75, about 100x100, about 250x250, about 500x500.[000226] In some cases, unique tags may be predetermined or random or semi-random sequence oligonucleotides. In other cases, a plurality of barcodes may be used such that barcodes are not necessarily unique to one another in the plurality. In this example, barcodes may be ligated to individual molecules such that the combination of the barcode and the sequence it may be ligated to creates a unique sequence that may be individually tracked. As described herein, detection of non-unique barcodes in combination with sequence data of beginning (start) and end (stop) portions of sequence reads may allow assignment of a unique identity to a particular molecule. The length or number of base pairs, of an individual sequence read may also be used to assign a unique identity to such a molecule. As described herein, fragments from a single strand of nucleic acid having been assigned a unique identity, may thereby permit subsequent identification of fragments from the parent strand. e. Enriching / Capturing; Amplification[000227] Methods disclosed herein can comprise capturing RNA or cDNA, such as target regions, e.g., of RNA (or of cDNA prepared from the RNA) extracted from a sample comprising cells or a blood sample (e.g., a buffy coat sample, a whole blood sample, a leukapheresis sample, or a PBMC sample). In some embodiments, target regions of additional RNA (or of cDNA prepared from the RNA), such as RNA (or cDNA prepared from the RNA) from tumor cells, are also captured. Capturing of nucleic acids from a sample comprising cells or a blood sample (e.g., a buffy coat sample, a whole blood sample, a leukapheresis sample, or a PBMC sample) and / or from additional nucleic acids may be performed in parallel (e.g., on pooled and / or differentially tagged nucleic acids from a sample comprising cells or a blood sample (e.g., a buffy coat sample,a whole blood sample, a leukapheresis sample, or a PBMC sample) and / or additional nucleic acids) or separately. Any of the embodiments described herein relating to enrichment or capture may be performed on nucleic acids from a sample comprising cells or a blood sample (e.g., a buffy coat sample, a whole blood sample, a leukapheresis sample, or a PBMC sample) and / or additional nucleic acids.[000228] In some embodiments, the capturing comprises contacting the nucleic acids with probes (e g., oligonucleotides) specific for the target regions. Enrichment or capture may be performed on any sample or subsample described herein using any suitable approach known in the art.[000229] In some embodiments, enrichment or capture is performed after attachment of adapters to sample molecules. In some embodiments, enrichment or capture is performed after a partitioning step. In some embodiments, enrichment or capture is performed after an amplification step. In some embodiments, sample molecules are partitioned, then adapters are attached, then sample molecules are amplified, and then the amplified molecules are subjected to enrichment or capture. The enriched or captured molecules may then be subjected to another amplification and then sequenced.[000230] In some embodiments, the probes specific for the target regions comprise a capture moiety that facilitates the enrichment or capture of the nucleic acids hybridized to the probes. In some embodiments, the capture moiety is biotin. In some such embodiments, streptavidin attached to a solid support, such as magnetic beads, is used to bind to the biotin. Nonspecifically bound nucleic acids that do not comprise a target region are washed away from the captured nucleic acids. In some embodiments, the nucleic acid is then dissociated from the probes and eluted from the solid support using salt washes or buffers comprising another nucleic acid denaturing agent. In some embodiments, the probes are also eluted from the solid support by, e g., disrupting the biotin-streptavidin interaction. In some embodiments, captured nucleic acid is amplified following elution from the solid support. In some such embodiments, nucleic acids comprising adapters are amplified using PCR primers that anneal to the adapters. In some embodiments, captured nucleic acids are amplified while attached to the solid support. In some such embodiments, the amplification comprises use of a PCR primer that anneals to a sequence within an adapter and a PCR primer that anneals to a sequence within a probe annealed to the target region of the nucleic acid.[000231] The capturing step may be performed using conditions suitable for specific nucleic acid hybridization, which generally depend to some extent on features of the probes such as length, base composition, etc. Those skilled in the art will be familiar with appropriate conditions given general knowledge in the art regarding nucleic acid hybridization. In some embodiments, complexes of target-specific probes and nucleic acids are formed.[000232] In some embodiments, cDNA is amplified. In some embodiments, amplification is performed before the capturing step. In some embodiments, amplification is performed after the capturing step. In some embodiments, amplification is performed before and after the capturing step. In various embodiments, the methods further comprise sequencing the captured cDNA. [000233] In some embodiments, adapters are included in the cDNA as described herein. In some embodiments, tags, which may be or include barcodes, are included in the cDNA. In some embodiments, such tags are included in adapters. Tags can facilitate identification of the origin of a nucleic acid. For example, barcodes can be used to allow the origin (e.g., subject) whence the RNA (or cDNA prepared from the RNA) came to be identified following pooling of a plurality of samples for parallel sequencing. This may be done concurrently with an amplification procedure, e.g., by providing the barcodes in a 5’ portion of a primer, e.g., as described herein. In some embodiments, adapters and tags / barcodes are provided by the same primer or primer set. For example, the barcode may be located 3’ of the adapter and 5’ of the target-hybridizing portion of the primer. Alternatively, barcodes can be added by other approaches, such as ligation, optionally together with adapters in the same ligation substrate.[000234] Additional details regarding amplification, tags, and barcodes are discussed herein, which can be combined to the extent practicable with any of these embodiments. i. Captured Set; Target Regions[000235] In some embodiments, nucleic acids captured or enriched using a method described herein from RNA (or of cDNA prepared from the RNA) from a sample comprising cells or a blood sample (e.g., a buffy coat sample, a whole blood sample, a leukapheresis sample, or a PBMC sample) and / or from additional nucleic acids, comprise captured RNA (or of cDNA prepared from the RNA), such as one or more captured sets of RNA (or of cDNA prepared from the RNA). In some embodiments, the captured nucleic acids comprise target regions (or a target region set, such as a target region set comprising one or more genes of a target gene list disclosed herein, or comprising one or more genes of a target gene list generated using the methodsdisclosed herein) that are differentially expressed in different immune cell types or in a sample from a subject having a disease or disorder as compared to a sample from a subject that does not have the disease or disorder. In some embodiments, the immune cell types comprise rare or closely related immune cell types, such as activated and naive lymphocytes or myeloid cells at different stages of differentiation.[000236] Without wishing to be bound by any particular theory, in an individual with cancer, proliferating or activated immune cells (and potentially also cancer cells) may be present in different (e.g., greater or fewer) quantities in the bloodstream and / or may shed more nucleic acids into the bloodstream than immune cells in a healthy individual (and healthy cells of the same tissue type, respectively). As such, the distribution of cell type and / or tissue of origin of RNA (or of cDNA prepared from the RNA) and / or additional nucleic acids may change upon carcinogenesis. For example, the distribution of immune cell type of origin may change in a subject having cancer, precancer, infection, transplant rejection, or other disease or disorder directly or indirectly affecting the immune system. Thus, variations in such distributions can be an indicator of disease.3. Sequencing; Generating Target Gene Lists[000237] In the disclosed methods, nucleic acids, including nucleic acids flanked by adapters, with or without prior amplification are subject to sequencing, such as RNA sequencing (RNA- seq) (see Stark, et al., Nat Rev Genet. 2019;20, 631-656; Haque, et al, Genome Med.2017;9(75)). RNA-seq is most frequently used for analyzing differential gene expression between samples. In traditional RNA-seq analyses, the process of analyzing differential gene expression via RNA-seq begins with RNA extraction (such as from a blood sample as described herein), followed by polyadenylated (e.g., mRNA) enrichment or ribosomal RNA depletion and / or globin mRNA depletion. cDNA is then synthesized, and an adaptor-ligated sequencing library is prepared. The library is sequenced to a read depth of, for example, 10-60 million reads per sample (such as 50 million reads, with deduplication) on a high-throughput platform (such as an Illumina platform). The sequencing reads (most often in the form of FASTQ files) can be computationally aligned and / or assembled to a transcriptome. The reads are most often mapped to a known transcriptome or annotated genome, matching each read to one or more genomic coordinates. This process is often accomplished using alignment tools such as STAR, TopHat, orHISAT, which each rely on a reference genome. If no genome annotation containing known exon boundaries is available (such as if a reference genome annotation is missing or is incomplete), or if reads are to be associated with transcripts rather than genes, aligned reads can be used in a transcriptome assembly step using tools such as StringTie or SOAPdenovo-Trans. Tools such as Sailfish, Kallisto, and Salmon can associate sequencing reads directly with transcripts, without the need for a separate quantification step.[000238] Reads that have been mapped to transcriptomic or genomic locations can be quantified using tools such as RSEM, Cufflinks, MMSeq, or HTSeq, or the alignment-free direct quantification tools Sailfish, Kallisto, or Salmon. Quantification results are often combined into an expression matrix, with one row for each expression feature (gene or transcript) and one column for each sample, with values being read counts or estimated abundances. Samples are then filtered and normalized to account for differences in expression patterns, read depth, and / or technical biases. In some embodiments, the expression levels of a plurality of genes (such as target genes) are transcripts per million (TPM)-normalized, reads per kilobase million (RPKM)- normalized, or fragments per kilobase million (FPKM)-normalized. In some embodiments, the expression levels of the genes (such as the target genes) are mean-centered and / or are scaled to unit variance. As described elsewhere herein, short sequences or barcodes may be added during library preparation or by direct RNA ligation, before amplification, to mark a sequence read as coming from a specific starting molecule. In some embodiments, quantities of immune cell types (e.g., quantities of immune cell types from which the RNA originated based on expression levels of the RNAs) are mean-centered and / or are scaled to unit variance. In some embodiments, the quantities of the immune cell types are proportions of the immune cell types.[000239] Changes in expression of individual genes and or transcripts between sample groups can be statistically modeled using one or more of various tools and computational methods. For example, a logistic regression model can be used to determine whether the presence, absence, or likelihood of a disease or disorder (such as a cancer, such as AA and / or CRC) in s subject can be determined based on the quantities (e.g., proportions) of the expression levels of genes differentially expressed between sample groups (such as between a cohort comprising individuals having a disease or condition (such as a cancer) and a cohort comprising healthy individuals (e.g., individuals who do not have the disease or condition), or on the quantities (e.g., proportions) of the immune cell types from which the RNA originated.[000240] For example, in some embodiments of the present disclosure, a list of target genes (genes differentially expressed between sample groups (such as between a cohort comprising individuals having a disease or condition (such as a cancer) and a cohort comprising healthy individuals (e.g., individuals who do not have the disease or condition)), and / or genes that are differentially expressed in a plurality of immune cell types may be generated as described in Examples 1 and 2. Expression counts can be de-duplicated, restricted to protein coding genes only, and transcripts per million (TPM)-normalized. The TPM-normalized values can be further mean-centered and scaled to unit variance for each gene. In some embodiments, modeling features can include the estimated proportions of one or more cell types described herein, such as a quantity of one or more cell types relative to a quantity of a different one or more cell types (such as in the same sample or in different samples), or a quantity of one or more cell types in a first sample (such as a sample from a subject) relative to a quantity of the same one or more cell types in a second sample (such as a second sample from the same subject or a sample from a different subject). Some cell types may be difficult to quantify at low values; thus, in some embodiments, a pseudocount can be used, e.g., by adding the pseudocount to each feature (e.g., cell type or gene expression value), or as a minimum value that replaces any observed values of zero, or of zero or a value lower than the pseudocount value. For example, pseudocounts can be used for genes for which no transcript is detected or for which the expression value would otherwise be zero or substantially zero, e.g., before transforming (e.g., logit-transforming) the features, such as to minimize the effects of noise. In another example, pseudocounts can be used for cell types for which the detected value is zero, or a value lower than the pseudocount value. In some embodiments, pseudocount values are applied to both gene expression values and to cell type values. Use of such pseudocounts may improve model training (e.g., model performance using training data and / or subsequent test data after training), and / or may produce a more balanced overall distribution of output model probabilities than, for example, a model trained without using pseudocounts (e.g., without using pseudocounts for genes for which no transcript is detected or an expression value would otherwise be zero or substantially zero), or a model trained using an overly small pseudocount, such as 0.00001 (as a proportion of 1). In some embodiments, the pseudocount is approximately equal to (e.g., within 50%, 40%, 30%, 20%, 15%, 10%, or 5% of) a limit of detection, such as a limit of detection for cell types generally, for a particular cell type, for transcripts generally, or for a particular transcript. In some embodiments, the pseudocount (e.g., a constant value, or expressed as a proportion of total cellsor transcripts as the case may be) is greater than 0.00001. In some embodiments, the pseudocount is 0.00002-0.1, such as 0.0001-0.1, 0.0001-0.01, 0.0005-0.01, 0.0006-0.01, 0.0007- 0.01, 0.0008-0.01, 0.0009-0.01, 0.001-0.01 or 0.0005-0.005. In some embodiments, the pseudocount is 0.0001-0.1, 0.0005-0.01, or 0.0003-0.002. In some embodiments, the pseudocount is 0.0005, 0.0006, 0.0007, 0.0008, 0.0009, 0.001, 0.0015, 0.002, 0.005, or 0.01. In some embodiments, the pseudocount is 0.00075. In some embodiments, the pseudocount is 0.001. In some embodiments, the pseudocount is 0.0011. In some embodiments, the pseudocount is 0.0012.[000241] Model training can be performed, e.g., using the skleam (scikit-leam) package in python. Three folds of cross validation may be randomly generated, and the area under the curve (AUC) calculated for each test fold. The L2 and LI penalty corresponding with the best average AUC across all five test folds is taken, and a final refit is performed using the entire training dataset with the optimal penalty. Genes differentially expressed between sample groups can be ranked, and the top, e.g., 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, 250, 300, 400, 450, or 500 or more differentially expressed genes identified. Further, cell type deconvolution using the sequencing data (such as RNA-seq data) returns the cell type composition (quantities of cell types) of each sample.[000242] In some embodiments, the plurality of target genes comprises genes having above- average expression variance in a training set comprising gene expression data from samples from healthy subjects and from subjects with a disease or disorder (such as a cancer, such as AA and / or CRC). In some embodiments, the plurality of target genes having above-average expression variance comprise genes having an expression variance in the top 25th, top 20th, top 15th, top 10th, top 9th, top 8th, top 7th, top 6th, top 5th, top 4th, top 3rd, top 2nd, or top 1st percentile of the genes of the training set. In some embodiments, the plurality of target genes having above-average expression variance are genes with an expression variance ranking in the top 1000, top 750, top 500, top 250, top 200, top 150, top 100, top 90, top 80, top 70, top 60, top 50, top 40, top 30, top 25, top 20, top 15, top 10, or top 5 genes in the training set. In particular embodiments, the majority, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or all, of the target genes are protein-coding genes.[000243] In some embodiments, the target genes comprise one or more, or each, of ICA1, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209,GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL18RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80, TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CDA, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, N0D2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MR0H7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, HLA-DOB, PGLYRP1, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIM1, HSD3B7, OSM, UPB1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYOIO, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, 0RM1, STON1, CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MYO1B, LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1, PDGFD, NMUR1, NBEA, OLR1, PTPRM, PAWR, ABCA13, TAFA1 , KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1 Al, ZNF667, SHISA4, LI CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.PDCD1, ZNK222, CCR3, TRPM4, GPR19, LAG3, TMEM156, MAST1, TSHR, TNFRSF17, ASGR2, TRPM6, TNFRSF11A, CRISP3, RYR1, PLEKHG3, CD209, ACP5, OSM, and CSF1.[000244] In other embodiments, the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 ofICAl, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL18RAP, KYNU, FASLG, MYB, CCND2,TRPM6, FLVCR2, CD80, TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CD A, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, N0D2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MR0H7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, HLA-DOB, PGLYRP1, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIMl, HSD3B7, OSM, UPB1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYOIO, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, 0RM1, STON1, CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MYO1B, LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1, PDGFD, NMUR1, NBEA, OLR1, PTPRM, PAWR, ABCA13, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, L1CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.PDCD1, ZNK222, CCR3, TRPM4, GPR19, LAG3, TMEM156, MAST1, TSHR, TNFRSF17, ASGR2, TRPM6, TNFRSF11A, CRISP3, RYR1, PLEKHG3, CD209, ACP5, OSM, and CSF1.[0002451 In some embodiments, the target genes comprise one or more, or each, of PGLYRP1, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIMl, HSD3B7, OSM, UPB1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYOIO, RAB19, OLAH,ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, P0C1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, 0RM1, and STONE In other embodiments, the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 ofPGLYRPl, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIM1, HSD3B7, OSM, UPB1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYO10, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, ORM1, and STONE[000246] In some embodiments, the target genes comprise one or more, or each, of ICA1, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL18RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80, TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CDA, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, NOD2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MROH7, CSF1 , FAM174B, TNFRSF4, PDCD1 , RYR1, HLA-DQA1 , NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, and HLA-DOB. In other embodiments, the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 of ICA1, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL18RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80, TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX,SKA1, CLIC2, DUSP2, SLAMF8, CDA, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, N0D2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MR0H7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, and HLA- DOB.[000247] In some embodiments, the target genes comprise one or more, or each, of CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MYO1B, LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1, PDGFD, NMUR1, NBEA, OLR1, PTPRM, PAWR, ABCA13, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, L1CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.[000248] In other embodiments, the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 of CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MYO1B, LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1, PDGFD, NMUR1, NBEA, OLR1, PTPRM, PAWR, ABCA13, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, L1CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.[000249] In some embodiments, the target genes comprise one or more (such as 1 , 2, 3, 4, 5, 6,7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50, 60, 70, 80, more than 80, 1-10, 1-20, 1-30, 1-40, 1-50, 1-60, 1-70, 1-80, 5-80, 10-80, 20-80, 30-80, or each) of the genes listed in Table 1. In some embodiments, the target genes comprise one or more (such as 1, 2, 3, 4, 5, 6, 7,8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30, 40, 50, 60, 70, 80, more than 80, 1-10, 1-20, 1- 30, 1-40, 1-50, 1-60, 1-70, 1-80, 5-80, 10-80, 20-80, 30-80, or each) of GZMH, PATL2, FCRL6, ZNF600, IL10RA, DTHD1, PYHIN1, HDAC11, XCL1, GZMA, RAB37, ID2, SLC9A3R1, MOSPD3, TES, EML4, CD99, ACSL6, YPEL1, H2AC17, FGFBP2, TBX21, F2R, PTGDS,DDX3Y, SYNGR1, ZNF683, SERPIN86, PRSS23, ID2, SRSF2, PRR5, CST3, SHISA4, PLAC8, BRD2, BMF, NIPAL2, UTS2, RARS2, ZNF320, RBL2, CREB3L2, RNF38, CCDC88A, MEX3C, SLC38A11, C0L19A1, PNPLA7, AFF3, STEAP1B, CELSR1, GRAPL, CBX5, AKAP6, EVL, CRISP3, BPI, MMP8, 0LFM4, MPO, MR0H6, KDM5D, IDH2, ABB, S100A4, H2AC17, GIMAP4, PPP1CB, XAF1, RPL37, PTPRO, CD177, RPS13, NAIP, RPS12, ID2, SH3BP1, RAB37, PLEKHG3, AFDN, SLC9A3R1, FLNA, SSBP3, RHOB, LIPA, ISCA1, PAG1, DDX3X, KDM5C, PIM2, IL4R, ZFX, FCGR2B, KDM6A, SARAF, TTC39C, NCOR2, ATP5MD, ARHGD1A, TRAF5, SCAMP2, RPS26, GSTM4, MICAL3, TOMM20, SSBP3, RALGDS, ITGB1, DYRK1B, ARRB1, TRIMI 1, LFNG, PAXX, ACCS, and SLC2A6. [000250] In some embodiments, the target genes comprise one or more (or each) of GZMH, PATL2, FCRL6, ZNF600, IL10RA, DTHD1, PYHIN1, HDAC11, XCL1, GZMA, RAB37, ID2, SLC9A3R1, MOSPD3, TES, EML4, CD99, ACSL6, YPEL1, and H2AC17. In some embodiments, the target genes comprise one or more (or each) of FGFBP2, TBX21, F2R, PTGDS, DDX3Y, SYNGR1, ZNF683, SERPIN86, PRSS23, ID2, SRSF2, PRR5, CST3, SHISA4, PLAC8, and BRD2. In some embodiments, the target genes comprise one or more (or each) of BMF, NIPAL2, UTS2, RARS2, ZNF320, RBL2, CREB3L2, RNF38, CCDC88A, MEX3C, SLC38A11, COL19A1, PNPLA7, AFF3, STEAP1B, CELSR1, GRAPL, CBX5, AKAP6, and EVL. In some embodiments, the target genes comprise one or more (or each) of CRISP3, BPI, MMP8, OLFM4, MPO, MR0H6, KDM5D, IDH2, ABB, S100A4, H2AC17, GIMAP4, PPP1CB, XAF1, RPL37, PTPRO, CD177, RPS13, NAIP, RPS12. In some embodiments, the target genes comprise one or more (or each) of ID2, SH3BP1, RAB37, PLEKHG3, AFDN, SLC9A3R1, FLNA, SSBP3, RHOB, LIPA, ISCA1, PAG1, DDX3X, KDM5C, PIM2, IL4R, ZFX, FCGR2B, KDM6A, and SARAF. In some embodiments, the target genes comprise one or more (or each) of TTC39C, NCOR2, ATP5MD, ARHGD1A, TRAF5, SCAMP2, RPS26, GSTM4, MICAL3, TOMM20, SSBP3, RALGDS, ITGB1, DYRK1B, ARRB1, TRIM11, LFNG, PAXX, ACCS, SLC2A6.[000251] In some embodiments, the target genes comprise one or more (or each) of GZMH, PATL2, FCRL6, ZNF600, IL10RA, DTHD1, PYHIN1, HDAC11, XCL1, and GZMA. In some embodiments, the target genes comprise one or more (or each) of RAB37, ID2, SLC9A3R1, MOSPD3, TES, EML4, CD99, ACSL6, YPEL1, and H2AC17. In some embodiments, the target genes comprise one or more (or each) of FGFBP2, TBX21, F2R, PTGDS, DDX3Y, SYNGR1, ZNF683, SERPIN86, PRSS23, and ID2. In some embodiments, the target genes comprise one ormore (or each) of SRSF2, PRR5, CST3, SHISA4, PLAC8, and BRD2. In some embodiments, the target genes comprise one or more (or each) of BMF, NIPAL2, UTS2, RARS2, ZNF320, RBL2, CREB3L2, RNF38, CCDC88A, and MEX3C. In some embodiments, the target genes comprise one or more (or each) of SLC38A11, COL19A1, PNPLA7, AFF3, STEAP1B, CELSR1, GRAPL, CBX5, AKAP6, and EVL. In some embodiments, the target genes comprise one or more (or each) of CRISP3, BPI, MMP8, OLFM4, MPO, MR0H6, KDM5D, IDH2, ABB, and S100A4. In some embodiments, the target genes comprise one or more (or each) of H2AC17, GIMAP4, PPP1CB, XAF1, RPL37, PTPRO, CD177, RPS13, NAIP, and RPS12. In some embodiments, the target genes comprise one or more (or each) of ID2, SH3BP1, RAB37, PLEKHG3, AFDN, SLC9A3R1, FLNA, SSBP3, RHOB, and LIPA. In some embodiments, the target genes comprise one or more (or each) of ISCA1, PAG1, DDX3X, KDM5C, PIM2, IL4R, ZFX, FCGR2B, KDM6A, and SARAF. In some embodiments, the target genes comprise one or more (or each) of TTC39C, NC0R2, ATP5MD, ARHGD1A, TRAF5, SCAMP2, RPS26, GSTM4, MICAL3, and TOMM20. In some embodiments, the target genes comprise one or more (or each) of SSBP3, RALGDS, ITGB1, DYRK1B, ARRB1, TRIMI 1, LFNG, PAXX, ACCS, and SLC2A6.[000252] In some cases, a sample group may exhibit a sample imbalance, such as a sex imbalance or an age imbalance. For example, if a healthy subject group is mostly females, a model could potentially learn genes associated with sex differences rather than genes that are associated with a disease or condition (such as a cancer). In such instances, female healthy samples can be down-weighted, and male disease state samples, female disease state samples, and male healthy samples can each be up-weighted. Alternatively, in such examples, the number of female healthy samples can be downsampled, such that the numbers of male and female samples and / or the number of healthy and diseased samples are the same in each sample group. [000253] Thus, in some embodiments, determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of sex on gene expression. In some embodiments, compensating for effects of sex on gene expression comprises regressing out the effects of sex on gene expression. In some embodiments, determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of sex on cell type quantity or cell type proportion. In some embodiments, compensating for effects of sex on cell type quantity or cell type proportion comprises regressing out the effects of sex on cell type quantity or cell type proportion. The effect of sex can be learned for a particular sample group ona per-gene basis, such as using males and females from a healthy donor population, after which sex-specific differences in gene expression can be corrected for across all samples in the group (e.g., in a training set). In particular embodiments, the target genes comprise genes that are not differentially expressed according to sex. For example, a population of healthy and disease-state matched males and healthy females can be subjected to the methods described herein, genes that are not differentially expressed between males and females can be identified. Genes identified as differentially expressed between males and females (i.e., genes that are differentially expressed (such as above a specified threshold) according to sex, as opposed to, e.g., according to a disease state) are optionally removed from a target gene list. In particular embodiments, at least 50%, at least 60%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% of the target genes are not differentially expressed (e.g., are not differentially expressed above a specified threshold) according to sex. In some embodiments, the target genes are identified using a training set comprising samples from individuals of the same sex as a subject. In some embodiments, quantities of the immune cell types (e.g., quantities of immune cell types from which RNA originated based on the expression levels of the RNAs) are identified using a training set comprising samples from individuals of the same sex as the subject. In some embodiments, the subject is female. In some embodiments, the subject is male.[000254] In some embodiments, determining the presence, absence, or likelihood of a disease or disorder comprises compensating for effects of age on gene expression. In such embodiments, compensating for effects of age on gene expression can comprise regressing out the effects of age on gene expression, such as described herein for the effects of sex on gene expression. In some embodiments, determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of age on cell type quantity or cell type proportion. In some embodiments, compensating for effects of age on cell type quantity or cell type proportion comprises regressing out the effects of age on cell type quantity or cell type proportion. In particular examples, target genes comprise genes that are not differentially expressed (such as above a specified threshold) according to age. In specific, non-limiting examples, at least 50%, at least 60%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% of the target genes are not differentially expressed (e.g., are not differentially expressed above a specified threshold) according to age. In some examples, the target genes were identified using a training setcomprising samples from individuals that, at the time of sample collection from each individual, were of an age that is within 1 year, within 2 years, within 3 years, within 4 years, within 5 years, within 6 years, within 7 years, within 8 years, within 9 years, within 10 years, within 11 years, within 12 years, within 13 years, within 14 years, or within 15 years of the age of the subject at the time of sample collection from the subject.[000255] In other particular examples, quantities of immune cell types do not differ according to age. In some embodiments, at least 50%, at least 60%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% of the immune cell types do not differ in quantity according to age. In some embodiments, the quantities of the immune cell types were identified using a training set comprising samples from individuals that, at the time of sample collection from each individual, were of an age that is within 1 year, within 2 years, within 3 years, within 4 years, within 5 years, within 6 years, within 7 years, within 8 years, within 9 years, within 10 years, within 11 years, within 12 years, within 13 years, within 14 years, or within 15 years of the age of the subject at the time of sample collection from the subject.C. Immune Cell Type Identification and Quantification[000256] In some embodiments, methods disclosed herein comprise steps of sequencing RNA (e g., RNA from a sample comprising cells, such as a buffy coat sample, a whole blood sample, a leukapheresis sample, a PBMC sample, and / or additional RNA), and determining levels of each of a plurality of immune cell types from which the RNA originated. The levels of immune cell types may be expressed, e.g., as relative amounts or percentages for each cell type being quantified.[000257] The methods herein thus allow for detection and / or identification of immune cellspecific differentially expressed genes (such as CTD genes of the target gene list of Example 2, or the genes listed in Table 1 below) that can be used to identify and quantify different immune cell types from which RNA in a sample originated. The immune cell types may comprise immune cells of different origins, different differentiation types, different activation types, or any combination of different origins, different differentiation types, and different activation types. Indeed, differentiation status and activation status significantly overlap and often change together in a given immune cell. For example, activation of an immune cell may induce differentiation of the cell. Immune cells of different activation types include activated cells, such as cells activatedby inflammatory cytokines or antigens, and suppressed cells, such as cells suppressed by Tregs. The immune cell types include neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, eosinophils, T cells, CD4+ T cells, B cells, NK cells, megakaryocytes, CD8+ central memory cells, CD8+ effector memory cells, CD4+ central memory cells, CD4+ effector memory cells, immature neutrophils, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells; follicular helper T cells; regulatory T cells (Tregs); gamma delta T cells; resting NK cells; activated NK cells, MO macrophages, Ml macrophages, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, and activated mast cells.. In some embodiments, genes from such cell types may exhibit increased expression in samples, such as RNA from a buffy coat sample, a whole blood sample, a leukapheresis sample, a PBMC sample, and / or additional RNA samples from healthy individuals, but decreased expression in such samples from individuals with a disease or disorder such as cancer or a precancerous condition. In other embodiments, genes from such cell types may exhibit decreased expression in samples, such as RNA from a buffy coat sample, a whole blood sample, a leukapheresis sample, a PBMC sample, and / or additional RNA samples from healthy individuals, but increased expression in such samples from individuals with a disease or disorder such as cancer or a precancerous condition. In some embodiments, to distinguish RNA from closely related cell types, such as naive and activated B cells, naive and activated T cells, or different stages of myeloid lineages, differentially expressed genes (such as one or more genes of a plurality of target genes identified using the methods disclosed herein) may be detected. In some embodiments, at least some of the differentially expressed genes are exclusively expressed in only one cell type or in only one cell type within a cluster. In some embodiments, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10 differentially expressed genes are exclusively expressed in only one cell type that is being identified or quantified within a cluster.[0002581 Table 1. Genes observed to be differentially expressed in particular cell types, inferred as a component of bulk expression (See Example 3).[000259] In some embodiments, determining the levels of different immune cell types from which RNA in a sample originated facilitates disease diagnosis or identification of appropriate treatments. In some embodiments, a change in the levels of one or more immune cell types is indicative of the presence of a disease or disorder in a subject, such as cancer, precancer, an infection, transplant rejection, or other disorder that causes changes in the relative amounts of certain immune cell types relative to the amounts present in a healthy subject. In some embodiments, changes in both the levels of one or more immune cell types in combination with sequence-independent changes, such as epigenetic changes in DNA from the subject, are indicative of the presence of a disease or disorder in a subject, such as cancer, precancer, an infection, transplant rejection, or other disorder that causes changes in the relative amounts of certain immune cell types and epigenetic changes relative to a healthy subject. In some embodiments, the methods facilitate identification of appropriate treatments based on the likelihood that a subject will respond to the treatment. In some such embodiments, determining the levels of RNA from one or more immune cell types in a sample from a subject having a certain cancer type facilitates prediction of the clinical outcome for immunotherapy in the subject. Where determining the levels of different immune cell types facilitates disease diagnosis, identification of appropriate treatments and association with therapeutic response, thethresholds for disease diagnosis and for identification of appropriate treatments may be the same or different. The levels can be determined based on a count of molecules corresponding to different immune cell types, or the relative frequency of such molecules or any value or ratio based on a count of molecules corresponding to one or more different immune cell types. [000260] In some embodiments, expression levels are determined (such as using the methods described herein) for a target gene set comprising a plurality of target genes that are differentially expressed in a plurality of immune cell types, wherein the plurality of immune cell types comprises one or more, or each, of neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, eosinophils, T cells, CD4+ T cells, B cells, NK cells, megakaryocytes, CD8+ central memory cells, CD8+ effector memory cells, CD4+ central memory cells, CD4+ effector memory cells, immature neutrophils, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells; follicular helper T cells; regulatory T cells (Tregs); gamma delta T cells; resting NK cells; activated NK cells, MO macrophages, Ml macrophages, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, and activated mast cells. In some embodiments, the plurality of immune cell types comprises one or more of naive B cells, naive CD4+ T cells, CD8+ T cells, resting NK cells, Tregs, and monocytes. In some embodiments, the plurality of immune cell types comprises two or more, three or more, four or more, or five or more of naive B cells, naive CD4+ T cells, CD8+ T cells, resting NK cells, Tregs, and monocytes. In some embodiments, the plurality of immune cell types comprises naive B cells, naive CD4+ T cells, CD8+ T cells, resting NK cells, Tregs, and monocytes.[000261] In particular embodiments, the plurality of immune cell types comprises one or more, or each, of CD8+ T cells, resting CD4+ memory T cells, Tregs, and naive B cells. In other particular embodiments, the plurality of immune cell types comprises CD8+ T cells, resting CD4+ memory T cells, Tregs, and naive B cells. In another particular embodiment, the plurality of immune cell types comprises CD8+ T cells, resting CD4+ memory T cells, and T regs. In another particular embodiment, the plurality of immune cell types comprises CD8+ T cells, Tregs, and naive B cells. In another particular embodiment, the plurality of immune cell types comprises CD8+ T cells, resting CD4+ memory T cells, and naive B cells. In other particular embodiments, the plurality of immune cell types comprises resting CD4+ memory T cells, Tregs, and naive B cells. In another particular embodiment, the plurality of immune cell typescomprises CD8+ T cells. In another particular embodiment, the plurality of immune cell types comprises resting CD4+ memory T cells. In another particular embodiment, the plurality of immune cell types comprises Tregs. In another particular embodiment, the plurality of immune cell types comprises naive B cells. In yet other particular embodiments, the plurality of immune cell types comprises neutrophils. In another particular embodiment, the plurality of immune cell types comprises naive CD4+ T cells. In another particular embodiment, the plurality of immune cell types comprises resting NK cells. In another particular embodiment, the plurality of immune cell types comprises monocytes. In some embodiments, the plurality of immune cell types comprises In other particular embodiments, the plurality of immune cell types comprises T cells, B cells, and NK cells; neutrophils and lymphocytes; neutrophils, T cells, B cells, and NK cells; granulocytes and lymphocytes; or granulocytes, T cells, B cells, and NK cells.[000262] In some embodiments, determining the presence, absence, or likelihood of a disease or disorder (such as a cancer, such as AA and / or CRC) in the subject based on the quantities of the immune cell types comprises determining the levels of one or more, or each, of the plurality of immune cell types relative to total blood cells. In some embodiments, determining the presence, absence, or likelihood of a disease or disorder (such as a cancer, e.g., any type of cancer mentioned elsewhere herein, such as AA and / or CRC) in the subject based on the quantities of the immune cell types comprises determining the levels of one or more, or each, of the plurality of immune cell types relative to total white blood cells. In certain embodiments, determining the presence, absence, or likelihood of the disease or disorder (such as the cancer, e.g., any type of cancer mentioned elsewhere herein, such as AA and / or CRC) in the subject based on the quantities of the immune cell types comprises determining the levels of one or more, or each, of T, B, and NK cells relative to all lymphocytes. In certain embodiments, determining the presence, absence, or likelihood of the disease or disorder (such as the cancer, , e.g., any type of cancer mentioned elsewhere herein, such as AA and / or CRC) in the subject based on the quantities of the immune cell types comprises determining relative proportions of neutrophils and lymphocytes, or of neutrophils and one or more, or each, of T cells, B cells, and NK cells. [000263] In some embodiments, the plurality of target genes comprises genes differentially expressed in an activated cell type relative to the same cell type that is not activated. In some embodiments, the plurality of target genes comprises genes differentially expressed in at least (a) a first cell type that is activated relative to the same first cell type that is not activated, and (b) a second cell type that is activated relative to the same second cell type that is not activated. Insome embodiments, the activated cell type is neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, or eosinophils. In particular embodiments, the plurality of target genes comprises genes differentially expressed in neutrophils relative to a nonneutrophil cell type. In some embodiments, the non-neutrophil cell type is one or more, or each, of a non-immune cell type, a non-granulocyte cell type, a myeloid non-granulocyte cell type, a lymphoid cell type, lymphocytes, T cells, B cells, and NK cells.[000264] In some embodiments, the plurality of target genes comprises genes differentially expressed in lymphocytes relative to a non-lymphocyte cell type. In some embodiments, the plurality of target genes comprises genes differentially expressed in a first cell type relative to a second cell type different from the first cell type, and the first cell type is neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, eosinophils, T cells, CD4+ T cells, B cells, NK cells, megakaryocytes, CD8+ central memory cells, CD8+ effector memory cells, CD4+ central memory cells, CD4+ effector memory cells, immature neutrophils, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells; follicular helper T cells; regulatory T cells (Tregs); gamma delta T cells; resting NK cells; activated NK cells, MO macrophages, Ml macrophages, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, or activated mast cells. In some embodiments, the plurality of target genes comprises genes differentially expressed in a first cell type relative to a second cell type different from the first cell type, and the first cell type is B cells, T cells, or NK cells. In some embodiments, the second cell type is neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, eosinophils, T cells, CD4+ T cells, B cells, NK cells, megakaryocytes, CD8+ central memory cells, CD8+ effector memory cells, CD4+ central memory cells, CD4+ effector memory cells, immature neutrophils, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells; follicular helper T cells; regulatory T cells (Tregs); gamma delta T cells; resting NK cells; activated NK cells, MO macrophages, Ml macrophages, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, or activated mast cells.[000265] In some embodiments, the plurality of target genes comprises genes differentially expressed when the disease or disorder is present relative to when the disease or disorder is notpresent. In some embodiments, the plurality of target genes comprises genes differentially expressed in the disease or disorder cells relative to healthy cells of the same cell type as the disease or disorder cells. In some embodiments, the disease or disorder is a cancer or precancer. In particular embodiments, the cancer or precancer is advanced adenoma (AA) and / or colorectal cancer (CRC). In other particular embodiments, the cancer or precancer is a blood cancer, brain cancer, lung cancer, skin cancer, nose cancer, throat cancer, liver cancer, bone cancer, lymphoma, pancreatic cancer, skin cancer, bowel cancer, rectal cancer, thyroid cancer, bladder cancer, kidney cancer, mouth cancer, stomach cancer, solid state tumor, heterogeneous tumor, homogenous tumor, or the like. Specific examples of such cancers include biliary tract cancer, bladder cancer, transitional cell carcinoma, urothelial carcinoma, brain cancer, gliomas, astrocytomas, breast carcinoma, metaplastic carcinoma, cervical cancer, cervical squamous cell carcinoma, rectal cancer, colorectal carcinoma, colon cancer, hereditary nonpolyposis colorectal cancer, colorectal adenocarcinomas, gastrointestinal stromal tumors (GISTs), endometrial carcinoma, endometrial stromal sarcomas, esophageal cancer, esophageal squamous cell carcinoma, esophageal adenocarcinoma, ocular melanoma, uveal melanoma, gallbladder carcinomas, gallbladder adenocarcinoma, renal cell carcinoma, clear cell renal cell carcinoma, transitional cell carcinoma, urothelial carcinomas, Wilms tumor, leukemia, acute lymphocytic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myeloid leukemia (CML), chronic myelomonocytic leukemia (CMML), liver cancer, liver carcinoma, hepatoma, hepatocellular carcinoma, cholangiocarcinoma, hepatoblastoma, Lung cancer, non-small cell lung cancer (NSCLC), mesothelioma, B-cell lymphomas, non-Hodgkin lymphoma, diffuse large B-cell lymphoma, Mantle cell lymphoma, T cell lymphomas, nonHodgkin lymphoma, precursor T-lymphoblastic lymphoma / leukemia, peripheral T cell lymphomas, multiple myeloma, nasopharyngeal carcinoma (NPC), neuroblastoma, oropharyngeal cancer, oral cavity squamous cell carcinomas, osteosarcoma, ovarian carcinoma, pancreatic cancer, pancreatic ductal adenocarcinoma, pseudopapillary neoplasms, acinar cell carcinomas, prostate cancer, prostate adenocarcinoma, skin cancer, melanoma, malignant melanoma, cutaneous melanoma, small intestine carcinomas, stomach cancer, gastric carcinoma, gastrointestinal stromal tumor (GIST), uterine cancer, or uterine sarcoma. In some embodiments, the cancer is a hematological cancer. In other embodiments, the cancer is a type of cancer that is not a hematological cancer, e.g., a solid tumor cancer such as a carcinoma, adenocarcinoma, or sarcoma.[000266] In certain embodiments, the plurality of target genes comprises genes differentially expressed in the disease or disorder cells relative to healthy colon epithelial cells. In some embodiments, the plurality of target genes comprises genes differentially expressed in the disease or disorder cells relative to a myeloid cell type or an erythroid cell type. In some embodiments, the plurality of target genes comprises genes differentially expressed in colon epithelial cells relative to a myeloid cell type or an erythroid cell type.D. Analysis[000267] In some embodiments, a method described herein comprises sequencing RNA to determine the levels of particular immune cell types from which RNA originated, and / or expression levels of a plurality of target genes. The immune cell types may comprise naive and activated lymphocytes, myeloid cells at different points of differentiation, and / or other types described elsewhere herein. In some methods, the determination of levels of immune cell types and / or the determination of expression levels of a plurality of target genes facilitates determination of the likelihood that the subject from which the RNA was obtained has a disease or disorder related to the immune system, such as an infection, transplant rejection, or cancer or precancer.[000268] In some embodiments, a method described herein comprises identifying the presence of RNA produced by a tumor (or neoplastic cells, or cancer cells) or by precancer cells. In some embodiments, a method described herein comprises identifying the presence of RNA produced by immune cells that are not tumor cells, cancer cells, or precancer cells. In some such embodiments, determination of immune cell distribution facilitates detection or diagnosis or cancer or precancer, or determination of cancer prognosis or cancer treatment options. For example, determining the ratios of different immune cell types may facilitate such detection or determination. In some embodiments, the ratio numerator is the number or relative number of neutrophils, monocytes, or both, and the ratio denominator is the number or relative number of T cells, B cells, NK cells, or all lymphocytes. In some embodiments, the ratio numerator is the number or relative number of neutrophils, and the ratio denominator is the number or relative number of T cells, B cells, NK cells, or all lymphocytes. In some embodiments, the ratio numerator is the number or relative number of monocytes, and the ratio denominator is the number or relative number of T cells, B cells, NK cells, or all lymphocytes. In some embodiments, the ratio numerator is the number or relative number of neutrophils andmonocytes, and the ratio denominator is the number or relative number of T cells, B cells, NK cells, or all lymphocytes. In some embodiments, the ratio is a neutrophil to lymphocyte ratio. In some embodiments, the ratio is a monocyte to T cell ratio. In some embodiments, elevations in such ratios are associated with cancer. In other embodiments, reductions in such ratios are associated with cancer.[000269] The present methods can be used to determine (diagnose) the presence or absence of a disease or disorder, or determine the likelihood of the disease or disorder, particularly cancer or precancer, in a subject, to characterize conditions (e.g., staging cancer or determining heterogeneity of a cancer), monitor response to treatment of a condition, effect prognosis risk of developing a condition or subsequent course of a condition. The present disclosure can also be useful in determining the efficacy of a particular treatment option. Successful treatment options may increase the amount or change the distribution (type) of immune cells present in a subject's blood. In other examples, this may not occur. In another example, perhaps certain treatment options may be correlated with genetic profiles of cancers over time. This correlation may be useful in selecting a therapy.[000270] Additionally, if a cancer is observed to be in remission after treatment, the present methods can be used to monitor residual disease or recurrence of disease.[000271] The types and number of cancers that may be detected may include blood cancers, brain cancers, lung cancers, skin cancers, nose cancers, throat cancers, liver cancers, bone cancers, lymphomas, pancreatic cancers, skin cancers, bowel cancers, rectal cancers, thyroid cancers, bladder cancers, kidney cancers, mouth cancers, stomach cancers, solid state tumors, heterogeneous tumors, homogenous tumors and the like. Type and / or stage of cancer can be detected from genetic variations including mutations, rare mutations, indels, copy number variations, transversions, translocations, recombination, inversion, deletions, aneuploidy, partial aneuploidy, polyploidy, chromosomal instability, chromosomal structure alterations, gene fusions, chromosome fusions, gene truncations, gene amplification, gene duplications, chromosomal lesions, DNA lesions, abnormal changes in nucleic acid chemical modifications, abnormal changes in epigenetic patterns, and abnormal changes in nucleic acid 5- methylcytosine.[000272] In particular embodiments, the disease or disorder is a cancer. In specific, non-limiting embodiments, the cancer is advanced adenoma (AA) and / or colorectal cancer (CRC). In some examples, the method comprises determining the presence or absence of AA. In some examples,the method comprises determining the likelihood of AA. In some examples, the method comprises determining the presence or absence of CRC. In some examples, the method comprises determining the likelihood of CRC. In some examples, the method comprises determining the presence or absence of AA and CRC. In some examples, the method comprises determining the likelihood of AA and CRC.[000273] Genetic data can also be used for characterizing a specific form of cancer. Cancers are often heterogeneous in both composition and staging. Genetic profile data may allow characterization of specific sub-types of cancer that may be important in the diagnosis or treatment of that specific sub-type. This information may also provide a subject or practitioner clues regarding the prognosis of a specific type of cancer and allow either a subject or practitioner to adapt treatment options in accord with the progress of the disease. Some cancers can progress to become more aggressive and genetically unstable. Other cancers may remain benign, inactive or dormant. The system and methods of this disclosure may be useful in determining disease progression.[000274] Further, the methods of the disclosure may be used to characterize the heterogeneity of an abnormal condition in a subject. Such methods can include, e.g., generating a genetic profile of extracellular polynucleotides derived from the subject, wherein the genetic profile comprises a plurality of data resulting from copy number variation and rare mutation analyses. In some embodiments, an abnormal condition is cancer or precancer. In some embodiments, the abnormal condition may be one resulting in a heterogeneous genomic population. In the example of cancer, some tumors are known to comprise tumor cells in different stages of the cancer. In other examples, heterogeneity may comprise multiple foci of disease. Again, in the example of cancer, there may be multiple tumor foci, perhaps where one or more foci are the result of metastases that have spread from a primary site.[000275] The present methods can be used to generate a profile, fingerprint, or set of data that is a summation of genetic information derived from different cells in a heterogeneous disease. Such a set of data may comprise differential expression of one or more target genes identified using the methods disclosed herein, copy number variation, or other mutation analyses alone or in combination.[000276] The present methods can be used to diagnose, prognose, monitor or observe cancers, or other diseases. In some embodiments, the methods herein do not involve the diagnosing, prognosing or monitoring a fetus and as such are not directed to non-invasive prenatal testing. Inother embodiments, these methodologies may be employed in a pregnant subject to diagnose, prognose, monitor or observe cancers or other diseases in an unborn subject whose RNA and other polynucleotides may co-circulate with maternal molecules.[000277] In general, after sequencing, analysis of reads can be performed on a partition-by- partition level, as well as a whole RNA population level. Tags can be used to sort reads from, e.g., different partitions and / or from different samples.[000278] An exemplary method for determining quantities of the immune cell types from which RNA originated based on the expression levels, and / or determining expression levels of a plurality of target genes comprises the following steps:1. Preparing extracted RNA samples (e.g., RNA isolated from a sample comprising cells or a blood sample (e.g., a whole blood sample, a buffy coat sample, a leukapheresis sample, or a PBMC sample) and / or additional RNA) from samples of a training set comprising samples from healthy subjects and from subjects having a disease or disorder (such as a cancer, such as AA and / or CRC). In some embodiments, poly(A) selection or rRNA depletion and / or globin mRNA depletion are performed using the extracted RNA.2. Preparing an RNA-seq library from the RNA sample, including ligating adapters comprising molecular tags to the cDNA, and amplifying the cDNA. In some embodiments, such as embodiments wherein RNA isolated from a sample comprising cells or a blood sample (e.g., a whole blood sample, a buffy coat sample, a leukapheresis sample, or a PBMC sample) is used, RNA is fragmented prior to adapter ligation, e.g., by sonication or enzymatic digestion.3. Sequencing the adapter-ligated, amplified cDNA using RNA-seq.4. Analyzing the resulting expression dataset to identify genes differentially expressed between samples from the healthy subjects and from the subjects having the disease or disorder (such as a cancer, such as AA and / or CRC), and ranking the differentially expressed genes by expression variance between the two sample groups. Cell type deconvolution using the expression data returns the cell type composition (quantities of cell types) of each sample in the training set. In some embodiments, the 50-500 top-ranked differentially expressed genes are selected as the target gene list for use in determining the presence, absence, or likelihood of the disease or disorder in a subject based on the quantities of the immune cell types and / or the expression levels of the plurality of target genes.5. Repeating steps 1-2 using at least one sample (e.g., RNA isolated from a sample comprising cells or a blood sample (e g., a whole blood sample, a buffy coat sample, a leukapheresis sample,or a PBMC sample) and / or additional RNA) from a subject that may have or is at risk of having a disease or condition (such as a cancer, such as AA and / or CRC).6. Determining expression levels of one or more of the plurality genes of the target gene list (generated in step 4) in the sample from the subject, and / or determining quantities of the immune cell types in the sample from the subject, and determining, based on the quantities of the immune cell types and / or the expression levels of the one or more of the plurality of target genes, the presence, absence, or likelihood of the disease or disorder (such as a cancer, such as AA and / or CRC) in the subject.[000279] An exemplary workflow is described in Examples 1 and 2.[000280] An exemplary method for training a model for determining quantities of the immune cell types from which RNA originated based on the expression levels comprises the following steps:1. Preparing extracted RNA samples (e.g., RNA isolated from a sample comprising cells or a blood sample (e g., a whole blood sample, a buffy coat sample, a leukapheresis sample, or a PBMC sample) and / or additional RNA) from samples of a training set comprising samples from healthy subjects and from subjects having a disease or disorder (such as a cancer, such as AA and / or CRC). In some embodiments, poly(A) selection or rRNA depletion and / or globin mRNA depletion are performed using the extracted RNA.2. Preparing an RNA-seq library from the RNA sample, including ligating adapters comprising molecular tags to the cDNA, and amplifying the cDNA. In some embodiments, such as embodiments wherein RNA isolated from a sample comprising cells or a blood sample (e g., a whole blood sample, a buffy coat sample, a leukapheresis sample, or a PBMC sample) is used, RNA is fragmented prior to adapter ligation, e.g., by sonication or enzymatic digestion.3. Sequencing the adapter-ligated, amplified cDNA using RNA-seq.4. Analyzing the resulting expression dataset to identify genes differentially expressed between samples from the healthy subjects and from the subjects having the disease or disorder (such as a cancer, such as AA and / or CRC), and ranking the differentially expressed genes by expression variance between the two sample groups. Cell type deconvolution using the expression data returns the cell type composition (quantities of cell types) of each sample in the training set. In some embodiments, genes differentially expressed in particular cell types of interest are selected as the target gene list(s) for use in determining the presence, absence, or likelihood of the disease or disorder in a subject.[000281] An exemplary method for determining quantities of the immune cell types from which RNA originated based on the expression levels comprises the following steps:1. Preparing extracted RNA from at least one sample (e.g., RNA isolated from a sample comprising cells or a blood sample (e.g., a whole blood sample, a buffy coat sample, a leukapheresis sample, or a PBMC sample) and / or additional RNA) from a subject that may have or is at risk of having a disease or condition (such as a cancer, such as AA and / or CRC).In some embodiments, poly(A) selection or rRNA depletion and / or globin mRNA depletion are performed using the extracted RNA.2. Preparing an RNA-seq library from the at least one RNA sample, including ligating adapters comprising molecular tags to the cDNA, and amplifying the cDNA. In some embodiments, such as embodiments wherein RNA isolated from a sample comprising cells or a blood sample (e.g., a whole blood sample, a buffy coat sample, a leukapheresis sample, or a PBMC sample) is used, RNA is fragmented prior to adapter ligation, e.g., by sonication or enzymatic digestion.3. Sequencing the adapter-ligated, amplified cDNA using RNA-seq.4. Determining quantities and / or relative proportions of immune cell types in the at least one sample from the subject based on expression levels of one or more of a plurality genes of a target gene list (e.g., a target gene list generated by training a model, e.g., using the above “exemplary method for training a model for determining quantities of the immune cell types from which RNA originated based on the expression levels”) in the sample from the subject, and determining, based on the quantities and / or relative proportions of the immune cell types, the presence, absence, or likelihood of the disease or disorder (such as a cancer, such as AA and / or CRC) in the subject.[000282] An exemplary workflow is described in Example 3.E. Partitioning[000283] In some instances, a sample from a subject (e.g., heterogeneous sample) is divided into two or more subsamples. A sample can be any biological sample isolated from a subject. A sample can be a bodily sample. Samples can include body tissues, such as known or suspected solid tumors, whole blood, buffy coat, PBMCs, platelets, serum, plasma, stool, red blood cells, white blood cells or leukocytes, endothelial cells, tissue biopsies, cerebrospinal fluid synovial fluid, lymphatic fluid, ascites fluid, interstitial or extracellular fluid, the fluid in spaces between cells, including gingival crevicular fluid, bone marrow, pleural effusions, cerebrospinal fluid, saliva, mucous, sputum, semen, sweat, urine. Samples are preferably body fluids, particularlyblood and fractions thereof, and urine. A sample can be in the form originally isolated from a subject or can have been subjected to further processing to remove or add components, such as cells, or enrich for one component relative to another. Thus, preferred body fluids for analysis include body fluids comprising cells, such as whole blood, buffy coat separated from whole blood, PBMCs separated from whole blood, a leukapheresis sample, and / or plasma or serum. [000284] In some embodiments, RNA is isolated from at least a first subsample, and DNA is isolated from at least a second subsample. Alternatively, RNA and DNA can be separately isolated from the sample. RNA isolated from the sample or at least first subsample can be used in any of the methods disclosed herein. In particular embodiments, isolated DNA or a subsample comprising DNA is further partitioned, and each partition of the DNA subsample is differentially tagged. Tagged partitions can then be pooled together for collective sample prep and / or sequencing. The partitioning-tagging-pooling steps can occur more than once, with each round of partitioning occurring based on a different characteristics and tagged using differential tags that are distinguished from other partitions and partitioning means. In some embodiments, the separating comprises partitioning the DNA in the sample into a plurality of partitioned subsamples. In some embodiments, the plurality of partitioned subsamples comprises a first partitioned subsample and a second partitioned subsample. In some embodiments, the first partitioned subsample comprises methylated DNA (e g., methyl cytosine) in a greater proportion than the second partitioned subsample. In some embodiments, the partitioning the DNA into a plurality of subsamples comprises contacting the DNA with an agent that recognizes methyl cytosine in the DNA. The partitioning step can occur prior to or after capturing an epigenetic target region set of DNA or a sequence-variable target region of the DNA. The partitioning step can occur prior to capturing an epigenetic target region set of DNA or a sequence-variable target region of the DNA. The partitioning step can occur prior to or after capturing an epigenetic target region set of DNA or a sequence-variable target region of the DNA and prior to or after sequencing the DNA. The partitioning step can occur after capturing an epigenetic target region set of DNA or a sequence-variable target regions of the DNA and prior to sequencing the DNA. [000285] Disclosed methods herein comprise analyzing DNA in a sample or subsample, or isolated from a sample or subsample. In some embodiments described herein, the disclosed methods comprise partitioning DNA. In such methods, different forms of DNA (e.g., hypermethylated and hypomethylated DNA) can be physically partitioned based on one or more characteristics of the DNA. This approach can be used to determine, for example, whethercertain sequences are hypermethylated or hypomethylated. In some embodiments, a first subsample or aliquot of a sample is subjected to steps for making capture probes as described elsewhere herein and a second subsample or aliquot of a sample is subjected to partitioning. In some embodiments, a sample or subsample or aliquot thereof is subjected to partitioning and differential tagging, followed by a capture step using capture probes for rearranged sequences and optionally additional capture probes, e.g., for sequence-variable and / or epigenetic target regions.[000286] Methylation profiling can involve determining methylation patterns across different regions of the genome. For example, after partitioning molecules based on extent of methylation (e g., relative number of methylated nucleobases per molecule) and sequencing, the sequences of molecules in the different partitions can be mapped to a reference genome. This can show regions of the genome that, compared with other regions, are more highly methylated or are less highly methylated. In this way, genomic regions, in contrast to individual molecules, may differ in their extent of methylation.[000287] In some embodiments, the partitioning comprises contacting a subsample comprising DNA with an agent that recognizes a modification associated with (e.g., in) the DNA. In some embodiments, the agent that recognizes the modification is an antibody or a methyl binding domain (MBD) protein. In some embodiments, the agent is immobilized on a solid support. In some embodiments, the solid support comprises a bead. In some embodiments, the partitioning comprises immunoprecipitation, e.g., using the agent that recognizes the modification, such as an antibody or an MBD protein, immobilized on solid support.[000288] In some embodiments, the partitioning comprises precipitating methylated DNA. In some embodiments, the partitioning comprises precipitating the methylated DNA to separate it from the unmethylated DNA. In some embodiments, the precipitating the methylated DNA can be performed using any pair of binding partners. In some embodiments, one of the binding partners may be linked to the MBD protein or antibody, and the other binding partner may be linked to a solid support. In some embodiments, the binding partner comprises biotin and streptavidin. In some embodiments, the biotin may be linked to the MBD protein, and the streptavidin may be linked to a solid support. In some embodiments, the MBD protein is linked to a solid support, optionally using any pair of binding partners. In some embodiments, the partitioning comprises immunoprecipitating the methylated DNA. In some embodiments, thepartitioning comprises immunoprecipitating the methylated DNA separately from the unmethylated DNA.[000289] In some embodiments, the modification is methylation, and in some such embodiments, the partitioning comprises partitioning on the basis of methylation level. In some such embodiments, the agent is a methyl binding reagent. In some embodiments, the methyl binding reagent specifically recognizes 5-methylcytosine. In some such embodiments, the agent is a hydroxymethyl binding reagent. In some embodiments, the methyl binding reagent specifically recognizes 5-hydroxymethylcytosine, biotinylated 5-hydroxymethylcytosine, glucosylated 5-hydroxymethylcytosine, or sulfonylated 5-hydroxymethylcytosine. In some embodiments, the partitioning comprises partitioning on the basis of binding to a protein comprising contacting the sample comprising the DNA with a binding reagent specific for the protein. In some such embodiments, binding reagent specifically binds a methylated protein or an acetylated protein, such as a methylated or acetylated histone, or an unmethylated protein or an unacetylated protein such as an unmethylated or unacetylated histone. In some embodiments, the binding reagent specifically binds an unmethylated or unacetylated protein epitope.[000290] In some embodiments, the modification is hydroxymethylation, and in some such embodiments, the partitioning comprises partitioning on the basis of hydroxymethylation level. In some such embodiments, the agent is a hydroxymethyl binding reagent, such as an antibody. In some embodiments, the hydroxymethyl binding reagent (e.g., antibody) specifically recognizes 5-hydroxymethylcytosine (5-hmC). In some embodiments, a modification such as hydroxymethylation is labeled (e g., biotinylated, glucosylated, or sulfonated) before being contacted with an agent that recognizes the labeled form of the modification. For example, 5- hmC can be enzymatically glucosylated and then partitioned based on binding to J-binding protein 1. Exemplary methods of labeling and / or partitioning 5-hmC are provided, e g., in Song et al., Nat. Biotech. 29:68-72 (2010); Ko et al., Nature 468:839-843 (2010); and Robertson et al., Nucleic Acids Res. 39:e55 (2011).[000291] Where immunoprecipitation is used and involves an antibody that recognizes singlestranded DNA, the DNA may be converted to double-stranded form by complementary strand synthesis before a subsequent step. Such synthesis may use an adapter as a primer binding site, or can use random priming.[000292] Partitioning nucleic acid molecules in a sample can increase a rare signal, e.g., by enriching rare nucleic acid molecules that are more prevalent in one partition of the sample. Forexample, a genetic variation present in hypermethylated DNA but less (or not) present in hypomethylated DNA can be more easily detected by partitioning a sample into hypermethylated and hypomethylated nucleic acid molecules. By analyzing multiple partitions of a sample, a multi-dimensional analysis of a single molecule can be performed and hence, greater sensitivity can be achieved. Partitioning may include physically partitioning nucleic acid molecules into partitions or subsamples based on the presence or absence of one or more methylated nucleobases. A sample may be partitioned into subsamples (and / or further partitioned as described elsewhere herein, such as further partitioning of DNA isolated from a subsample) based on a characteristic that is indicative of differential gene expression or a disease state. A sample may be partitioned based on a characteristic, or combination thereof that provides a difference in signal between a normal and diseased state during analysis of nucleic acids, e.g., cell free DNA (cfDNA), non-cfDNA, tumor DNA, circulating tumor DNA (ctDNA) and cell free nucleic acids (cfNA).[000293] In some embodiments, hypermethylation and / or hypomethylation variable epigenetic target regions are analyzed to determine whether they show differential methylation characteristic of tumor cells or cells of a type that does not normally contribute to the DNA sample being analyzed (such as cfDNA), and / or particular immune cell types.[000294] In some instances, heterogeneous DNA in a sample is partitioned into two or more partitions (e.g., at least 3, 4, 5, 6 or 7 partitions). In some embodiments, each partition is differentially tagged. Tagged partitions can then be pooled together for collective sample prep and / or sequencing. The partitioning-tagging-pooling steps can occur more than once, with each round of partitioning occurring based on a different characteristic (examples provided herein), and tagged using differential tags that are distinguished from other partitions and partitioning means. In other instances, the differentially tagged partitions are separately sequenced.[000295] In some embodiments, sequence reads from differentially tagged and pooled DNA are obtained and analyzed in silico. After sequencing, analysis of reads can be performed on a partition-by-partition level, as well as a whole DNA population level. Tags are used to sort reads from different partitions. Analysis to detect genetic variants can be performed on a partition-by- partition level, as well as whole nucleic acid population level. For example, analysis can include in silico analysis to determine genetic variants, such as copy number variations (CNVs), single nucleotide variations (SNVs), insertions / deletions (indels), and / or fusions in nucleic acids in each partition. In some instances, in silico analysis can include analysis to determine epigeneticvariation (one or more of methylation chromatin structure, etc.). Analysis can include in silico analysis using sequence information, genomic coordinates length, coverage, and / or copy number. For example, coverage of sequence reads can be used to determine nucleosome positioning in chromatin. Tags can be used to sort reads from different partitions. Higher coverage can correlate with higher nucleosome occupancy in genomic region while lower coverage can correlate with lower nucleosome occupancy or nucleosome depleted region (NDR).[000296] Examples of characteristics that can be used for partitioning isolated DNA include sequence length, methylation level, nucleosome binding, sequence mismatch, immunoprecipitation, and / or proteins that bind to DNA. Resulting partitions can include one or more of the following nucleic acid forms: single-stranded DNA (ssDNA), double-stranded DNA (dsDNA), shorter DNA fragments and longer DNA fragments. In some embodiments, partitioning based on a cytosine modification (e.g., cytosine methylation) or methylation generally is performed and is optionally combined with at least one additional partitioning step, which may be based on any of the foregoing characteristics or forms of DNA. In some embodiments, a heterogeneous population of nucleic acids is partitioned into nucleic acids with one or more epigenetic modifications and without the one or more epigenetic modifications. Examples of epigenetic modifications include presence or absence of methylation; level of methylation; type of methylation (e.g., 5-methylcytosine versus other types of methylation, such as adenine methylation and / or cytosine hydroxymethylation); and association and level of association with one or more proteins, such as histones. Alternatively or additionally, a heterogeneous population of nucleic acids can be partitioned into nucleic acid molecules associated with nucleosomes and nucleic acid molecules devoid of nucleosomes. Alternatively or additionally, a heterogeneous population of nucleic acids may be partitioned into single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA). Alternatively, or additionally, a heterogeneous population of nucleic acids may be partitioned based on nucleic acid length (e.g., molecules of up to 160 bp and molecules having a length of greater than 160 bp).[000297] In some cases, different procedures are applied to different partitions to determine different characteristics of the initial sample. In some embodiments, the DNA of at least one partition is subjected to end repair and sequencing. In some embodiments at least one partition is not subjected to the end repair and sequencing procedure. In cases where the method comprises a conversion procedure, corresponding sequences from the converted and non-converted partitionscan be compared to identify single nucleotides that have undergone conversion and therefore identify corresponding modified nucleosides in the initial sample.[000298] In some embodiments, partition tagging comprises tagging molecules in each partition with a partition tag. After re-combining partitions (e.g., to reduce the number of sequencing runs needed and avoid unnecessary cost) and sequencing molecules, the partition tags identify the source partition. In another embodiment, different partitions are tagged with different sets of molecular tags, e.g., comprised of a pair of barcodes. In this way, each molecular barcode indicates the source partition as well as being useful to distinguish molecules within a partition. For example, a first set of 35 barcodes can be used to tag molecules in a first partition, while a second set of 35 barcodes can be used tag molecules in a second partition.[000299] In some embodiments, after partitioning and tagging with partition tags, the molecules may be pooled for sequencing in a single run. In some embodiments, a sample tag is added to the molecules, e.g., in a step subsequent to addition of partition tags and pooling. Sample tags can facilitate pooling material generated from multiple samples for sequencing in a single sequencing run.[000300] Alternatively, in some embodiments, partition tags may be correlated to the sample as well as the partition. As a simple example, a first tag can indicate a first partition of a first sample; a second tag can indicate a second partition of the first sample; a third tag can indicate a first partition of a second sample; and a fourth tag can indicate a second partition of the second sample.[000301] While tags may be attached to molecules already partitioned based on one or more characteristics, the final tagged molecules in the library may no longer possess that characteristic. For example, while single-stranded DNA molecules may be partitioned and tagged, the final tagged molecules in the library are likely to be double stranded. Similarly, while DNA may be subject to partition based on different levels of methylation, in the final library, tagged molecules derived from these molecules are likely to be unmethylated. Accordingly, the tag attached to a molecule in the library typically indicates the characteristic of the “parent molecule” from which the ultimate tagged molecule is derived, not necessarily to characteristic of the tagged molecule, itself.[000302] As an example, barcodes 1, 2, 3, 4, etc. are used to tag and label molecules in the first partition; barcodes A, B, C, D, etc. are used to tag and label molecules in the second partition; and barcodes a, b, c, d, etc. are used to tag and label molecules in the third partition.Differentially tagged partitions can be pooled prior to sequencing. Differentially tagged partitions can be separately sequenced or sequenced together concurrently, e.g., in the same flow cell of an Illumina sequencer.[000303] After sequencing, analysis of reads can be performed on a partition-by-partition level, as well as a whole DNA population level. Tags are used to sort reads from different partitions. Analysis can include in silico analysis to determine genetic and epigenetic variation (one or more of methylation, chromatin structure, etc.) using sequence information, genomic coordinates length, coverage, and / or copy number. In some embodiments, higher coverage can correlate with higher nucleosome occupancy in a genomic region, while lower coverage can correlate with lower nucleosome occupancy or a nucleosome depleted region (NDR).[000304] The agents used to partition populations of nucleic acids within a sample can be affinity agents, such as antibodies with the desired specificity, natural binding partners or variants thereof (Bock et al., Nat Biotech 28: 1106-1114 (2010); Song et al., Nat Biotech 29: 68- 72 (2011)), or artificial peptides selected e.g., by phage display to have specificity to a given target. In some embodiments, the agent used in the partitioning is an agent that recognizes a modified nucleobase. In some embodiments, the modified nucleobase recognized by the agent is a modified cytosine, such as a methylcytosine (e.g., 5-methylcytosine). In some embodiments, the modified nucleobase recognized by the agent is a product of a procedure that affects the first nucleobase in the DNA differently from the second nucleobase in the DNA of the sample. In some embodiments, the modified nucleobase may be a “converted nucleobase,” meaning that its base pairing specificity was changed by a procedure. For example, certain procedures convert unmethylated or unmodified cytosine to dihydrouracil, or more generally, at least one modified or unmodified form of cytosine undergoes deamination, resulting in uracil (considered a modified nucleobase in the context of DNA) or a further modified form of uracil. Examples of partitioning agents include antibodies, such as antibodies that recognize a modified nucleobase, which may be a modified cytosine, such as a methylcytosine (e.g., 5-methylcytosine). In some embodiments, the partitioning agent is an antibody that recognizes a modified cytosine other than 5-methylcytosine, such as 5-carboxylcytosine (5-caC). Alternative partitioning agents include methyl binding domain (MBDs) and methyl binding proteins (MBPs) as described herein, including proteins such as MeCP2, MBD2, and antibodies preferentially binding to 5- methylcytosine. Where an antibody is used to immunoprecipitate methylated DNA, the methylated DNA may be recovered in single-stranded form. In such embodiments, a secondstrand can be synthesized. Hypermethylated (and optionally intermediately methylated) subsamples may then be contacted with a methylation sensitive nuclease that does not cleave hemi-methylated DNA, such as Hpall, BstUI, or Hin6i. Alternatively or in addition, hypomethylated (and optionally intermediately methylated) subsamples may then be contacted with a methylation dependent nuclease that cleaves hemi-methylated DNA.[000305] Additional, non-limiting examples of partitioning agents are histone binding proteins which can separate nucleic acids bound to histones from free or unbound nucleic acids. Examples of histone binding proteins that can be used in the methods disclosed herein include RBBP4, RbAp48 and SANT domain peptides.[000306] In some embodiments, partitioning can comprise both binary partitioning and partitioning based on degree / level of modifications. For example, methylated fragments in a DNA sample can be partitioned by methylated DNA immunoprecipitation (MeDIP), or all methylated fragments can be partitioned from unmethylated fragments using methyl binding domain proteins (e.g., MethylMinder Methylated DNA Enrichment Kit (ThermoFisher Scientific). Subsequently, additional partitioning may involve eluting fragments having different levels of methylation by adjusting the salt concentration in a solution with the methyl binding domain and bound fragments. As salt concentration increases, fragments having greater methylation levels are eluted.[000307] Analyzing DNA may comprise detecting or quantifying DNA of interest. Analyzing DNA can comprise detecting genetic variants and / or epigenetic features (e.g., DNA methylation and / or DNA fragmentation). In some embodiments, the DNA of interest is one or more differentially methylated regions of the DNA. In some embodiments, the detecting or quantifying the DNA of interest comprises quantifying and / or detecting a level of methylation at one or more differentially methylated regions of the DNA. In some embodiments, quantifying and / or detecting the level of methylation at one or more differentially methylated regions of the DNA comprises sequencing at least a portion of the amplified DNA or quantitative PCR (qPCR). In some embodiments, the DNA of interest is a copy number variant. In some embodiments, the detecting or quantifying the DNA of interest comprises quantifying and / or detecting a level of a copy number variant of the DNA. In some embodiments, quantifying and / or detecting the level of a copy number variant of the DNA comprises quantitative PCR (qPCR).[000308] In some embodiments, methylation levels can be determined using partitioning, modification-sensitive conversion such as bisulfite conversion, direct detection duringsequencing, methylation-sensitive restriction enzyme digestion, methylation-dependent restriction enzyme digestion, or any other suitable approach. For example, different forms of DNA (e.g., hypermethylated and hypomethylated DNA) can be physically partitioned based on one or more characteristics of the DNA. For example, a methylated DNA binding protein (e.g., an MBD such as MBD2, MBD4, or MeCP2) or an antibody specific for 5-methylcytosine (as in MeDIP) can be used to partition the DNA. This approach can be used to determine, for example, whether certain sequences are hypermethylated or hypomethylated. In some embodiments, a DNA fragmentation pattern can be determined based on endpoints and / or centerpoints of DNA molecules, such as cfDNA molecules.[000309] In some instances, the final partitions are enriched in nucleic acids having different extents of modifications (overrepresentative or underrepresentative of modifications). Overrepresentation and underrepresentation can be defined by the number of modifications bom by a nucleic acid relative to the median number of modifications per strand in a population. For example, if the median number of 5-methylcytosine residues in nucleic acid in a sample is 2, a nucleic acid including more than two 5-methylcytosine residues is overrepresented in this modification and a nucleic acid with 1 or zero 5-methylcytosine residues is underrepresented. The effect of affinity separation is to enrich for nucleic acids overrepresented in a modification in a bound phase and for nucleic acids underrepresented in a modification in an unbound phase (i.e. in solution). The nucleic acids in the bound phase can be eluted before subsequent processing.[000310] When using MeDIP or MethylMiner®Methylated DNA Enrichment Kit (ThermoFisher Scientific) various levels of methylation can be partitioned using sequential elutions. For example, a hypomethylated partition (no methylation) can be separated from a methylated partition by contacting the nucleic acid population with the MBD from the kit, which is attached to magnetic beads. The beads are used to separate out the methylated nucleic acids from the non- methylated nucleic acids. Subsequently, one or more elution steps are performed sequentially to elute nucleic acids having different levels of methylation. For example, a first set of methylated nucleic acids can be eluted at a salt concentration of 160 mM or higher, e.g., at least 150 mM, at least 200 mM, 300 mM, 400 mM, 500 mM, 600 mM, 700 mM, 800 mM, 900 mM, 1000 mM, or 2000 mM. After such methylated nucleic acids are eluted, magnetic separation is once again used to separate higher level of methylated nucleic acids from those with lower level of methylation. The elution and magnetic separation steps can be repeated tocreate various partitions such as a hypomethylated partition (enriched in nucleic acids comprising no methylation), a methylated partition (enriched in nucleic acids comprising low levels of methylation), and a hyper methylated partition (enriched in nucleic acids comprising high levels of methylation).[000311] In some methods, nucleic acids bound to an agent used for affinity separation-based partitioning are subjected to a wash step. The wash step washes off nucleic acids weakly bound to the affinity agent. Such nucleic acids can be enriched in nucleic acids having the modification to an extent close to the mean or median (i.e., intermediate between nucleic acids remaining bound to the solid phase and nucleic acids not binding to the solid phase on initial contacting of the sample with the agent).[000312] The affinity separation results in at least two, and sometimes three or more partitions of nucleic acids with different extents of a modification. While the partitions are still separate, the nucleic acids of at least one partition, and usually two or three (or more) partitions are linked to nucleic acid tags, usually provided as components of adapters, with the nucleic acids in different partitions receiving different tags that distinguish members of one partition from another. The tags linked to nucleic acid molecules of the same partition can be the same or different from one another. But if different from one another, the tags may have part of their code in common so as to identify the molecules to which they are attached as being of a particular partition.[000313] For further details regarding portioning nucleic acid samples based on characteristics such as methylation, see WO2018 / 119452, which is incorporated herein by reference.[000314] In some embodiments, the nucleic acid molecules can be partitioned into different partitions based on the nucleic acid molecules that are bound to a specific protein or a fragment thereof and those that are not bound to that specific protein or fragment thereof.[000315] Nucleic acid molecules can be partitioned based on DNA-protein binding. Protein- DNA complexes can be partitioned based on a specific property of a protein. Examples of such properties include various epitopes, modifications (e.g., histone methylation or acetylation) or enzymatic activity. Examples of proteins which may bind to DNA and serve as a basis for fractionation may include, but are not limited to, protein A and protein G. Any suitable method can be used to partition the nucleic acid molecules based on protein bound regions. Examples of methods used to partition nucleic acid molecules based on protein bound regions include, but are not limited to, SDS-PAGE, chromatin-immuno-precipitation (ChIP), heparin chromatography, and asymmetrical field flow fractionation (AF4).[000316] In some embodiments, the partitioning comprises contacting the DNA with a methylation sensitive restriction enzyme (MSRE) and / or a methylation dependent restriction enzyme (MDRE). Following the treatment of the DNA with a MSRE or a MDRE, the DNA may be partitioned based on size to generate hypermethylated (longest DNA molecules following MSRE treatment and shortest DNA fragments following MDRE treatment), intermediate (intermediate length DNA molecules following MSRE or MDRE treatment), and hypomethylated (shortest DNA molecules following MSRE treatment and longest DNA fragments following MDRE treatment) subsamples.[000317] In some embodiments, the partitioning is performed by contacting the nucleic acids with a methyl binding domain (“MBD”) of a methyl binding protein (“MBP”). In some such embodiments, the nucleic acids are contacted with an entire MBP. In some embodiments, an MBD binds to 5-methylcytosine (5mC), and an MBP comprises an MBD and is referred to interchangeably herein as a methyl binding protein or a methyl binding domain protein. In some embodiments, MBD is coupled to paramagnetic beads, such as Dynabeads® M-280 Streptavidin via a biotin linker. Partitioning into fractions with different extents of methylation can be performed by eluting fractions by increasing the NaCl concentration.[000318] In some embodiments, bound DNA is eluted by contacting the antibody or MBD with a protease, such as proteinase K. This may be performed instead of or in addition to elution steps using NaCl as discussed above.[000319] Examples of agents that recognize a modified nucleobase contemplated herein include, but are not limited to:(a) MeCP2 is a protein that preferentially binds to 5-methyl-cytosine over unmodified cytosine.(b) RPL26, PRP8 and the DNA mismatch repair protein MHS6 preferentially bind to 5- hydroxymethyl -cytosine over unmodified cytosine.(c) FOXK1, FOXK2, FOXP1, FOXP4 and FOXI3 preferably bind to 5-formyl-cytosine over unmodified cytosine (lurlaro et al., Genome Biol. 14: R119 (2013)).(d) Antibodies specific to one or more methylated or modified nucleobases or conversion products thereof, such as 5mC, 5-caC, or DHU.[000320] In general, elution is a function of the number of modifications, such as the number of methylated sites per molecule, with molecules having more methylation eluting under increased salt concentrations. To elute the DNA into distinct populations based on the extent of methylation, one can use a series of elution buffers of increasing NaCl concentration. Saltconcentration can range from about 100 nm to about 2500 mM NaCl. In one embodiment, the process results in three (3) partitions. Molecules are contacted with a solution at a first salt concentration and comprising a molecule comprising an agent that recognizes a modified nucleobase, which molecule can be attached to a capture moiety, such as streptavidin. At the first salt concentration a population of molecules will bind to the agent and a population will remain unbound. The unbound population can be separated as a “hypomethylated” population. For example, a first partition enriched in hypomethylated form of DNA is that which remains unbound at a low salt concentration, e.g., 100 mM or 160 mM. A second partition enriched in intermediate methylated DNA is eluted using an intermediate salt concentration, e.g., between 100 mM and 2000 mM concentration. This is also separated from the sample. A third partition enriched in hypermethylated form of DNA is eluted using a high salt concentration, e.g., at least about 2000 mM.[000321] In some embodiments, a monoclonal antibody raised against 5-methylcytidine (5mC) is used to purify methylated DNA. DNA is denatured, e.g., at 95°C in order to yield singlestranded DNA fragments. Protein G coupled to standard or magnetic beads as well as washes following incubation with the anti-5mC antibody are used to immunoprecipitate DNA bound to the antibody. Such DNA may then be eluted. Partitions may comprise unprecipitated DNA and one or more partitions eluted from the beads.[000322] In some embodiments, the partitions of DNA are desalted and concentrated in preparation for enzymatic steps of library preparation.[000323] Sequences that comprise aberrantly high copy numbers may tend to be hypermethylated. Accordingly, in some embodiments, the DNA contacted with target-specific probes specific for members of an epigenetic target region set comprising a plurality of target regions that are both type-specific differentially methylated regions and copy number variants comprises at least a portion of a hypermethylated partition. The DNA from or comprising at least a portion of the hypermethylated partition may or may not be combined with DNA from or comprising at least a portion of one or more other partitions, such as an intermediate partition or a hypomethylated partition.[000324] In some cases, different procedures are applied to different partitions to determine different characteristics of the initial sample. In some embodiments, the DNA of at least one partition is subjected to an end repair and sequencing procedure. In some embodiments at least one partition is not subjected to the end repair and sequencing procedure. In cases where thesequencing procedure comprises a conversion procedure, corresponding sequences from the converted and non-converted partitions can be compared to identify single nucleotides that have undergone conversion and therefore identify corresponding modified nucleosides in the initial sample.[000325] Disclosed methods herein can comprise analyzing DNA in a sample. In some embodiments described herein, the disclosed methods comprise partitioning DNA. In such methods, different forms of DNA (e.g., hypermethylated and hypom ethylated DNA) can be physically partitioned based on one or more characteristics of the DNA. This approach can be used to determine, for example, whether certain sequences are hypermethylated or hypomethylated and whether certain hypermethylated regions overlap with regions with copy number variants. In some embodiments, a first subsample or aliquot of a sample is subjected to steps for making capture probes as described elsewhere herein and a second subsample or aliquot of a sample is subjected to partitioning. In some embodiments, a sample or subsample or aliquot thereof is subjected to partitioning and differential tagging, followed by a capture step using capture probes for rearranged sequences and optionally additional capture probes, e.g., for sequence-variable and / or epigenetic target regions.[000326] Methylation profiling can involve determining methylation patterns across different regions of the genome. For example, after partitioning molecules based on extent of methylation (e.g., relative number of methylated nucleobases per molecule) and sequencing, the sequences of molecules in the different partitions can be mapped to a reference genome. This can show regions of the genome that, compared with other regions, are more highly methylated or are less highly methylated. In this way, genomic regions, in contrast to individual molecules, may differ in their extent of methylation.F. Conversion, Contacting DNA with a Deaminase[000327] The methods disclosed herein can comprise subjecting DNA, such as DNA isolated from a sample or one or more subsamples or DNA contained in one or more subsamples, to a procedure that affects a first nucleobase in the DNA differently from a second nucleobase. In some embodiments, the first nucleobase is a modified or an unmodified nucleobase, and the second nucleobase is a modified or an unmodified nucleobase different from the first nucleobase. In some embodiments, the first nucleobase and the second nucleobase have the same base pairing specificity. In some embodiments, the procedure that affects a first nucleobase in theDNA differently from a second nucleobase comprises a conversion procedure that changes the base pairing specificity of the base or does not change the base pairing specificity of the base, depending on the modification status of the base. In some embodiments, the first nucleobase is an unmodified cytosine and the second nucleobase is a modified cytosine (e.g., 5-methylcytosine or 5-hydroxymethylcytosine).[000328] In some embodiments, the procedure that affects a first nucleobase of the DNA differently from a second nucleobase of the DNA is conversion. In some embodiments, the procedure that affects a first nucleobase of the DNA differently from a second nucleobase of the DNA is methylation-sensitive conversion. The methods disclosed herein can comprise contacting DNA in a sample with a deaminase, thereby providing a converted sample. In some embodiments, the deaminase is a methyl-sensitive deaminase or a methyl-insensitive deaminase. In some embodiments, the deaminase is a dsDNA deaminase and / or a ssDNA deaminase. This step of contacting the DNA in the sample with a deaminase can be referred to as, or be included in, a conversion procedure, such as any of the conversion procedures described elsewhere herein. For an exemplary description of conversion using a deaminase, see, e.g., Schutsky et al., Nature Biotechnology 2018; 36: 1083-1090. In some embodiments, the DNA in the converted sample is then sequenced, and a level or methylation at one or more differentially methylated regions of the DNA is quantified, or a variation of the copy number at one or more regions of the DNA is quantified.[000329] Table 1 summarizes exemplary methods of deamination with the type of modified bases detectable with these methods. These are described in more detail below. A gene is considered to comprise a DMR when the DMR is located within an untranslated region (UTR), intron, or exon of the gene, or within 500 nucleotides of either the 5’ end of the sense strand of the 5’ UTR or the 3’ end of the sense strand of the 3’ UTR.[000330] As outlined below, there are various methods of detecting and / or identifying modified nucleosides that rely on a conversion procedure that changes the base-pairing specificity of a nucleoside, based on the modification status of the nucleosides. These changes of base-pairing specificity can then be detected, and thus the modification status of the nucleoside inferred, by sequencing.[000331] In some embodiments, the conversion procedure used in the methods of the disclosure is one that changes the base pairing specificity of a modified nucleoside (e.g. methylated cytosine), but does not change the base pairing specificity of the corresponding unmodified nucleoside (e.g. cytosine) or does not change the base pairing specificity of any un-modified nucleoside (e.g. cytosine, adenosine, guanosine and thymidine (or uracil)). Advantages of methods that do not convert the base-pairing specificity of unmodified nucleosides include reduced loss of sequence complexity, higher sequencing efficiency and reduced alignment losses. Additionally, methods such as TAPS may in some cases be preferred over methods such as bisulfite sequencing and EM-seq because they are less destructive (especially important for low yield samples such as cfDNA or FFPE samples) and do not require denaturation, meaning that non-conversion errors are theoretically more likely to be random. In methods that require denaturation for conversion, failure to denature a DNA molecule will result in non-conversion of all bases in the DNA molecule. As biological changes in methylation are predominantly concerted to a localized regions of interest, these non-random (localized) non-conversion events can appear as false negatives (non-methylated regions). Random non-conversion methods can maximally affect a low percent of bases within a region, and thus the specificity of methylation change detection can be maximized (reduce false positives) by placing a threshold on percentage of bases within a region that are methylated / non-methylated. Hence, in some cases, a conversion procedure that does not involve denaturation is preferred.[000332] In other cases, the conversion procedure used in the methods of the disclosure is one that changes the base pairing specificity of an unmodified nucleoside (e.g. cytosine), but does notchange the base pairing specificity of the corresponding modified nucleoside (e.g. methylated cytosine such as 5hmC and / or 5mC). Such methods include, for example, bisulfite sequencing. [000333] The skilled person can select a suitable method according to their needs, including which nucleoside modifications are to be detected and / or identified and which type of modified base is used in an end repair reaction.[000334] In some embodiments, the conversion procedure converts modified nucleosides. In some embodiments, the conversion procedure which converts modified nucleosides comprises Tet-assisted conversion with a substituted borane reducing agent, optionally wherein the substituted borane reducing agent is 2-picoline borane, borane pyridine, tert-butylamine borane, ammonia borane or pyridine borane. In Tet-assisted pic-borane conversion with a substituted borane reducing agent conversion, a TET protein is used to convert 5mC and 5hmC to 5caC, without affecting unmodified C. 5caC, and 5fC if present, are then converted to dihydrouracil (DHU) by treatment with 2-picoline borane (pic-borane) or another substituted borane reducing agent such as borane pyridine, tert-butylamine borane, or ammonia borane, also without affecting unmodified C. See, e.g., Liu et al., Nature Biotechnology 2019; 37:424-429 (e.g., at Supplementary Fig. 1 and Supplementary Note 7). Thus, when this type of conversion is used, the first nucleobase comprises one or more of 5mC, 5fC, 5caC, or 5hmC, and the second nucleobase comprises unmodified cytosine. DHU is read as a T in sequencing. Sequencing of the converted DNA identifies positions that are read as cytosine as being unmodified C positions. Meanwhile, positions that are read as T are identified as being T, 5mC, 5fC, 5caC, or 5hmC. Performing TAP conversion, such as on a DNA sample as described herein, thus facilitates identifying positions containing unmodified C using the sequence reads obtained.[000335] Hence, in these embodiments, an end repair reaction can be performed with dNTPs, wherein the at least one type of dNTP comprises a 5mC or 5hmC, and regions synthesized during an end repair reaction can be identified as those regions comprising 5mC or 5hmC (via T being called at positions which are C in the reference) at non-CpG positions. This procedure encompasses Tet-assisted pyridine borane sequencing (TAPS), described in further detail in Liu et al. 2019, supra. In this method Tet enzyme is used to progressively oxidize 5mC and 5hmC to 5fC or 5caC, then pyridine borane deaminates 5fC, 5CaC to DHU, amplified as T.[000336] Alternatively, protection of 5hmC (e.g., using GT or 5-hydroxymethylcytosine carbamoyltransferase) can be combined with Tet-assisted conversion with a substituted borane reducing agent, e.g. as described above. In this method (TAPS- ), 5hmC can be protected fromconversion, for example through glucosylation using P-glucosyl transferase (PGT), forming (forming 5-glucosylhydroxymethylcytosine) 5ghmC, or through carbamoylation using 5- hydroxymethylcytosine carbamoyltransferase, forming 5cmC. This is described in Yu et al., Cell 2012; 149: 1368-80. Treatment with a TET protein such as mTetl then converts 5mC to 5caC but does not convert C, 5ghmC, or 5cmC. 5caC is then converted to DHU by treatment with pic- borane or another substituted borane reducing agent such as borane pyridine, tert-butylamine borane, or ammonia borane, also without affecting ghmC, 5cmC, or unmodified C. Thus, when Tet-assisted conversion with a substituted borane reducing agent is used, the first nucleobase comprises mC, and the second nucleobase comprises one or more of unmodified cytosine or hmC, such as unmodified cytosine and optionally hmC, fC, and / or caC. Sequencing of the converted DNA identifies positions that are read as cytosine as being either 5hmC or unmodified C positions. Meanwhile, positions that are read as T are identified as being T, 5fC, 5caC, or 5mC. Performing TAPSp conversion on a sample as described herein thus facilitates distinguishing positions containing unmodified C or 5hmC on the one hand from positions containing 5mC using the sequence reads obtained. Hence, in these embodiments, an end repair reaction can be performed with dNTPs, wherein the at least one type of dNTP comprises a 5mC, and regions synthesized during an end repair reaction can be identified as those regions comprising 5mC (via T being called at positions which are C in the reference) at non-CpG positions. For an exemplary description of this type of conversion, see, e.g., Liu et al., Nature Biotechnology 2019; 37:424-429. 5-hydroxymethylcytosine carbamoyltransferase is described in Yang et al., Bio-protocol, 2023; 12(17): e4496.[000337] In some embodiments, the conversion procedure converts modified nucleosides. In some embodiments, the conversion procedure which converts modified nucleosides comprises chemical-assisted conversion with a substituted borane reducing agent, optionally wherein the substituted borane reducing agent is 2-picoline borane, borane pyridine, tert-butylamine borane, borane pyridine or ammonia borane. In chemical-assisted conversion with a substituted borane reducing agent, an oxidizing agent such as potassium perruthenate (KRuCh) (also suitable for use in ox-BS conversion) is used to specifically oxidize 5hmC to 5fC. Treatment with pic-borane or another substituted borane reducing agent such as borane pyridine, tert-butylamine borane, or ammonia borane converts 5fC and 5caC to DHU but does not affect 5mC or unmodified C. Thus, when this type of conversion is used, the first nucleobase comprises one or more of hmC, fC, and caC, and the second nucleobase comprises one or more of unmodified cytosine or mC, such asunmodified cytosine and optionally mC. Sequencing of the converted DNA identifies positions that are read as cytosine as being either 5mC or unmodified C positions. Meanwhile, positions that are read as T are identified as being T, 5fC, 5caC, or 5hmC. Performing this type of conversion as described herein thus facilitates distinguishing positions containing unmodified C or 5mC on the one hand from positions containing 5hmC using the sequence reads obtained. Hence, in these embodiments, an end repair reaction can be performed with dNTPs, wherein at least one type of dNTP comprises a 5hmC, and regions synthesized during an end repair reaction can be identified as those regions comprising 5hmC (via T being called at positions which are C in the reference) at non-CpG positions. For an exemplary description of this type of conversion, see, e.g., Liu et al., Nature Biotechnology 2019; 37:424-429.[000338] Exemplary conversion procedures that change the base-pairing specificity of modified cytosines have been described. However, the methods described herein could in principle use any modified nucleoside and suitable conversion procedure (i.e. single-base epigenetic conversion assay) that changes the base-pairing specificity of the modified nucleoside and thereby allows the modified base to be distinguished from the corresponding unmodified nucleoside and / or other types of modification when sequenced. For example, any conversion procedure could be used allowing any one of N6-methyladenine (6mA), N6- hydroxymethyladenine (6hmA), or N6-formyladenine (6fA) to be distinguished from unmodified adenosine.[000339] In some embodiments, the conversion procedure converts unmodified nucleosides. In some embodiments, the conversion procedure which converts unmodified nucleosides comprises bisulfite conversion. Treatment with bisulfite converts unmodified cytosine and certain modified cytosine nucleotides (e.g. 5-formyl cytosine (5fC) or 5-carboxylcytosine (5caC)) to uracil whereas other modified cytosines (e.g., 5mC and 5hmC) are not converted. Thus, where bisulfite conversion is used, the first nucleobase comprises one or more of unmodified cytosine, 5fC, 5caC, or other cytosine forms affected by bisulfite, and the second nucleobase may comprise one or more of 5mC and 5hmC, such as 5mC and optionally 5hmC. Sequencing of bisulfite-treated DNA identifies positions that are read as cytosine as being 5mC or 5hmC positions. Meanwhile, positions that are read as T are identified as being T or a bisulfite-susceptible form of C, such as unmodified cytosine, 5fC, or 5caC. Thus, performing bisulfite conversion, such as on a DNA sample as described herein facilitates identifying positions containing 5mC or 5hmC. Hence, in these embodiments, an end repair reaction can be performed with dNTPs, wherein at least onetype of dNTP comprises a 5mC and / or a 5hmC, and regions synthesized during an end repair reaction can be identified as those regions comprising 5mC or a 5hmC (via C being called at these positions) at non-CpG positions. For an exemplary description of bisulfite conversion, see, e.g., Moss et al., Nat Commnn. 2018; 9: 5068.[000340] In some embodiments, the procedure which converts unmodified nucleosides comprises oxidative bisulfite (Ox-BS) conversion. This procedure first converts 5hmC to 5fC, which is bisulfite susceptible, followed by bisulfite conversion. Thus, when oxidative bisulfite conversion is used, the first nucleobase comprises one or more of unmodified cytosine, 5fC, 5caC, 5hmC, or other cytosine forms affected by bisulfite, and the second nucleobase comprises 5mC. Sequencing of Ox-BS converted DNA identifies positions that are read as cytosine as being 5mC positions. Meanwhile, positions that are read as T are identified as being T or a bisulfite-susceptible form of C, such as unmodified cytosine, 5fC, or 5hmC. Hence, in these embodiments, an end repair reaction can be performed with dNTPs, wherein at least one type of dNTP comprises a 5mC, and regions synthesized during an end repair reaction can be identified as those regions comprising 5mC (via C being called at these positions) at non-CpG positions. Performing Ox-BS conversion thus facilitates identifying positions containing mC. For an exemplary description of oxidative bisulfite conversion, see, e.g., Booth et al., Science 2012; 336: 934-937.[000341] In some embodiments, the procedure which converts unmodified nucleosides comprises Tet-assisted bisulfite (TAB) conversion. In TAB conversion, 5hmC is protected from conversion and 5mC is oxidized in advance of bisulfite treatment, so that positions originally occupied by 5mC are converted to U while positions originally occupied by 5hmC remain as a protected form of cytosine. For example, as described in Yu et al., Cell 2012; 149: 1368-80, 0- glucosyl transferase can be used to protect 5hmC (forming 5-glucosylhydroxymethylcytosine (5ghmC)), then a TET protein such as mTetl can be used to convert 5mC to 5caC, and then bisulfite treatment can be used to convert C and 5caC to U while 5ghmC remains unaffected. [000342] Alternatively, a carbamoyltransferase enzyme, such as 5-hydroxymethylcytosine carbamoyltransferase as described in Yang et al., Bio-protocol, 2023; 12(17): e4496, can be used to protect hmC (by converting hmC to 5-carbamoyloxymethylcytosine (5cmC)), then a TET protein such as mTetl can be used to convert mC to caC, and then bisulfite treatment can be used to convert C and caC to U while 5cmC remains unaffected. Thus, when TAB conversion is used, the first nucleobase comprises one or more of unmodified cytosine, 5fC, 5caC, 5mC, or othercytosine forms affected by bisulfite, and the second nucleobase comprises 5hmC. Sequencing of TAB-converted DNA identifies positions that are read as cytosine as being 5hmC positions. Meanwhile, positions that are read as T are identified as being T, or a bisulfite-susceptible form of C, such as unmodified cytosine, 5mC, 5fC, or 5caC. Performing TAB conversion on a first subsample as described herein thus facilitates identifying positions containing 5hmC. Hence, in these embodiments, an end repair reaction can be performed with dNTPs, wherein at least one type of dNTP comprises a 5hmC, and regions synthesized during an end repair reaction can be identified as those regions comprising 5hmC (via C being called at these positions) at non-CpG positions.[000343] In some embodiments, the conversion procedure which converts unmodified cytosines comprises APOBEC-coupled epigenetic (ACE) conversion. In ACE conversion, an AID / APOBEC family DNA deaminase enzyme such as APOBEC3A (A3 A) is used to deaminate an unmodified cytosine and 5mC without deaminating 5hmC, 5fC, or 5-caC. Thus, when ACE conversion is used, the first nucleobase comprises unmodified C and / or mC (e.g., unmodified C and optionally mC), and the second nucleobase comprises hmC. Sequencing of ACE-converted DNA identifies positions that are read as cytosine as being 5hmC, 5fC, or 5-caC positions. Meanwhile, positions that are read as T are identified as being T, unmodified C, or 5mC. Performing ACE conversion as described herein thus facilitates distinguishing positions containing 5hmC from positions containing 5mC or unmodified C using the sequence reads obtained from the first subsample. In some embodiments, an end repair reaction can be performed with dNTPs, wherein at least one type of dNTP comprises a 5hmC, and regions synthesized during an end repair reaction can be identified as those regions comprising 5hmC (via C being called at these positions) at non-CpG positions. For an exemplary description of ACE conversion, see, e.g., Schutsky et aL, Nature Biotechnology 2018; 36: 1083-1090.[000344] In some embodiments, the procedure that affects a first nucleobase in the DNA differently from a second nucleobase in the DNA of the first subsample comprises enzymatic conversion of the first nucleobase, e.g., as in EM-Seq. See, e.g., Vaisvila R, et al. (2019) EM- seq: Detection of DNA methylation at single base resolution from picograms of DNA. bioRxiv, DOE 10.1101 / 2019.12.20.884692, available at www.biorxiv.org / content / 10.1101 / 2019.12.20.884692vl . For example, TET2 and T4-PGT or 5-hydroxymethylcytosine carbamoyltransferase (described in Yang et al., Bio-protocol, 2023; 12(17): e4496) can be used to convert 5mC and 5hmC into substrates that cannot be deaminatedby a deaminase (e.g., AP0BEC3A), and then a deaminase (e.g., AP0BEC3A) can be used to deaminate unmodified cytosines, converting them to uracils.[000345] In some embodiments, the procedure that affects a first nucleobase in the DNA differently from a second nucleobase in the DNA comprises enzymatic conversion of the first nucleobase using a non-specific, modification-sensitive double-stranded DNA deaminase, e.g., as in SEM-seq. See, e.g., Vaisvila et al. (2023) Discovery of novel DNA cytosine deaminase activities enables a nondestructive single-enzyme methylation sequencing method for base resolution high-coverage methylome mapping of cell-free and ultra-low input DNA. bioRxiv; DOI: 10.1101 / 2023.06.29.547047, available at https: / / www.biorxiv.org / content / 10.1101 / 2023.06.29.547047vl. SEM-Seq employs a nonspecific, modification-sensitive double-stranded DNA deaminase (MsddA) in a nondestructive single-enzyme 5-methylctyosine sequencing (SEM-seq) method that deaminates unmodified cytosines. Accordingly, SEM-seq does not require the TET2 and T4-PGT or 5- hydroxymethylcytosine carbamoyltransferase protection and denaturing steps that are of use, e.g., in APOEC3A-based protocols. Additionally, MsddA does not deaminate 5-formylated cytosines (5fC) or 5-carboxylated cytosines (5-caC). In SEM-seq, unmodified cytosines in the DNA are deaminated to uracil and is read as “T” during sequencing. Modified cytosines (e.g., 5mC) are not converted and are read as “C” during sequencing. Cytosines that are read as thymines are identified as unmodified (e.g., unmethylated) cytosines or as thymines in the DNA. Performing SEM-seq conversion thus facilitates identifying positions containing 5mC using the sequence reads obtained. In some embodiments, the procedure that affects a first nucleobase in the DNA differently from a second nucleobase in the DNA comprises enzymatic conversion of unmodified cytosine using MsddA.[000346] In some embodiments, the conversion procedure converts modified nucleosides. In some embodiments, the conversion procedure which converts modified nucleosides comprises enzymatic conversion, such as DM-seq, for example, as described in WO2023 / 288222A1. In DM-seq, unmodified cytosines in the DNA are enzymatically protected from a subsequent deamination step wherein 5mC in 5mCpG is converted to T. The enzymatically protected unmodified (e.g., unmethylated) cytosines are not converted and are read as “C” during sequencing. Cytosines that are read as thymines (in a CpG context) are identified as methylated cytosines in the DNA.[000347] Thus, when this type of conversion is used, the first nucleobase comprises unmodified (such as unmethylated) cytosine, and the second nucleobase comprises modified (such as methylated) cytosine. Sequencing of the converted DNA identifies positions that are read as cytosine as being unmodified C positions. Meanwhile, positions that are read as T are identified as being T or 5mC. Performing DM-seq conversion thus facilitates identifying positions containing 5mC using the sequence reads obtained.[000348] Exemplary cytosine deaminases for use herein include APOBEC enzymes, for example, APOBEC3A. Generally, AID / APOB EC family DNA deaminase enzymes such as APOBEC3A (A3 A) are used to deaminate (unprotected) unmodified cytosine and 5mC. For an exemplary description of APOBEC conversion, see, e.g., Schutsky et al., Nature Biotechnology 2018; 36: 1083-1090.[000349] The enzymatic protection of unmodified cytosines in the DNA comprises addition of a protective group to the unmodified cytosines. Such protective groups can comprise an alkyl group, an alkyne group, a carboxyl group, a carboxyalkyl group, an amino group, a hydroxymethyl group, a glucosyl group, a glucosylhydroxymethyl group, an isopropyl group, or a dye. For example, DNA can be treated with a methyltransferase, such as a CpG-specific methyltransferase, which adds the protective group to unmodified cytosines. The term methyltransferase is used broadly herein to refer to enzymes capable of transferring a methyl or substituted methyl (e.g., carboxymethyl) to a substrate (e.g., a cytosine in a nucleic acid). In some embodiments, the DNA is contacted with a CpG-specific DNA methyltransferase (MTase), such as a CpG-specific carboxymethyltransferase (CxMTase), and a substituted methyl donor, such as a carboxymethyl donor (e.g., carboxymethyl-S-adenosyl-L-methionine). See, e.g., WO2021 / 236778A2. In particular embodiments, the CxMTase can facilitate the addition of a protective carboxymethyl group to an unmethylated cytosine. In some embodiments, the unmethylated cytosine is unmodified cytosine. The carboxymethyl group can prevent deamination of the cytosine during a deamination step (such as a deamination step using an APOBEC enzyme, such as A3 A). Substituted methyl or carboxymethyl donors useful in the disclosed methods include but are not limited to, S-adenosyl-L-methionine (SAM) analogs, optionally wherein the SAM analog is carboxy-S-adenosyl-L-methionine (CxSAM). SAM analogs are described, for example, in WO2022 / 197593A1. The MTase may be, for example, a CpG methyltransferase from Spiroplasma sp. strain MQ1 (M.SssI), DNA-methyltransferase 1 (DNMT1), DNA-methyltransferase 3 alpha (DNMT3A), DNA-methyltransferase 3 beta(DNMT3B), or DNA adenine methyltransferase (Dam). The CxMTase may be a CpG methyltransferase from Mycoplasma penetrans (M.Mpel). In a particular embodiment, the methyltransferase enzyme is a variant of M.Mpel having SEQ ID NO: 1 or SEQ ID NO: 2, or a sequence at least 90%, at least 92%, at least 94%, at least 96%, at least 97%, at least 98%, or at least 99% identical thereto, optionally wherein the amino acid corresponding to position 374 is R or K.[000350] In one embodiment, the methyltransferase enzyme is a variant of M.Mpel having an N374R substitution or an N374K substitution. The methyltransferase of SEQ ID NO: 1 or SEQ ID NO: 2 can further comprise one or more amino acid substitutions selected from a) substitution of one or both residues T300 and E305 with S, A, G, Q, D, or N; b) substitution of one or more residues A323, N306, and Y299 with a positively charged amino acid selected from K, R or H; and / or c) substitution of S323 with A, G, K, R or H, which may enhance the activity of the enzyme.[000351] Optionally, the conversion procedure further includes enzymatic protection of 5hmCs, such as by glucosylation of the 5hmCs (e.g., using 0GT) or by carbamoylation of the 5hmCs (e.g., using 5-hydroxymethylcytosine carbamoyltransferase), in the DNA prior to the deamination of unprotected modified cytosines. In this method, 5hmC can be protected from conversion, for example through glucosylation using [B-glucosyl transferase (PGT), forming (5- glucosylhydroxymethylcytosine) 5ghmC, or through carbamoylation using 5- hydroxymethylcytosine carbamoyltransferase, forming 5cmC. This is described, for example, in Yu et al., Cell 2012; 149: 1368-80, and in Yang et al., Bio-protocol, 2023; 12(17): e4496. Glucosylation or carbamoylation of 5hmC can reduce or eliminate deamination of 5hmC by a deaminase such as APOBEC3A. Treatment with an MTase or CxMTase then adds a protecting group to unmodified (unmethylated) cytosines in the DNA. 5mC (but not protected, unmodified cytosine and not 5ghmC or 5cmC) is then deaminated (converted to T in the case of 5mC) by treatment with a deaminase, for example, an APOBEC enzyme (such as APOBEC3A).Sequencing of the converted DNA identifies positions that are read as cytosine as being either 5hmC or unmodified C positions. Meanwhile, positions that are read as T are identified as being T or 5mC. Performing DM-seq conversion with glucosylation of 5hmC on a sample as described herein thus facilitates distinguishing positions containing unmodified C or 5hmC on the one hand from positions containing 5mC using the sequence reads obtained.[000352] Also provided herein are methods in which alternative base conversion schemes are used. For example, unmethylated cytosines can be left intact while methylated cytosines and hydroxymethylcytosines are converted to a base read as a thymine (e.g., uracil, thymine, or dihydrouracil).[000353] In some embodiments, methylating a cytosine in at least one first complementary strand or second complementary strand comprises contacting the cytosine with a methyltransferase such as DNMT1 or DNMT5. In such embodiments, the step of oxidizing a 5- hydroxymethylated cytosine to 5-formylcytosine (such as by contacting the 5 -hydroxymethyl cytosine in a first strand and a second strand with KRuO i) can be optional.[000354] In some embodiments, converting the modified cytosine in at least one first or second strand to a thymine or a base read as thymine comprises oxidizing a hydroxymethyl cytosine, e.g., the hydroxymethyl cytosine is oxidized to formylcytosine. In some embodiments, oxidizing the hydroxymethyl cytosine to formylcytosine comprises contacting the hydroxymethyl cytosine with a ruthenate, such as potassium ruthenate (KRuC ).[000355] In some embodiments, the modified cytosine is converted to thymine, uracil, or dihydrouracil. In any such embodiments, amplification methods may comprise uracil- and / or dihydrouracil-tolerant amplification methods, such as PCR using a uracil- and / or dihydrouracil - tolerant DNA polymerase.[000356] In some embodiments, the method comprises converting a formylcytosine and / or a methylcytosine to carboxylcytosine as part of converting the modified cytosine in at least one first or second strand to a thymine or a base read as thymine. For example, converting the formylcytosine and / or the methylcytosine to carboxylcytosine can comprise contacting the formylcytosine and / or the methylcytosine with a TET enzyme, such as TET1, TET2, or TET3. In some embodiments, the method comprises reducing the carboxylcytosine as part of converting the modified cytosine in at least one first or second strand to a thymine or a base read as thymine, and / or the carboxylcytosine is reduced to dihydrouracil. In some embodiments, reducing the carboxylcytosine comprises contacting the carboxylcytosine with a borane or borohydride reducing agent.[000357] In some embodiments, the borane or borohydride reducing agent comprises pyridine borane, 2-picoline borane, borane, tert-butylamine borane, ammonia borane, sodium borohydride, sodium cyanoborohydride (NaBHaCN), lithium borohydride (LiBEU), ethylenediamine borane, dimethylamine borane, sodium triacetoxyborohydride, morpholineborane, 4-methylmorpholine borane, trimethylamine borane, dicyclohexylamine borane, or a salt thereof. In other embodiments, the reducing agent comprises lithium aluminum hydride, sodium amalgam, amalgam, sulfur dioxide, dithionate, thiosulfate, iodide, hydrogen peroxide, hydrazine, diisobutylaluminum hydride, oxalic acid, carbon monoxide, cyanide, ascorbic acid, formic acid, dithiothreitol, beta-mercaptoethanol, or any combination thereof.[000358] As discussed above, in some embodiments, a TET protein can be used to convert 5mC and optionally 5hmC (but not unmodified C) into substrates (e.g., 5caC) that cannot be deaminated by a deaminase, and then a deaminase (e.g., APOBEC3A) can be used to deaminate unmodified cytosines, converting them to uracils. Various TET enzymes may be used in the disclosed methods as appropriate. In some embodiments, the one or more TET enzymes comprise TETv. TETv is described in US Patent 10,260,088 and its sequence is SEQ ID NO: 1 therein (SEQ ID NO: 3 in the present application). In some embodiments, the one or more TET enzymes comprise TETcd. TETcd is described in US Patent 10,260,088 and its sequence is SEQ ID NO: 3 therein (SEQ ID NO: 4 in the present application). In some embodiments, the one or more TET enzymes comprise TET1. In some embodiments, the one or more TET enzymes comprise TET2. TET2 may be expressed and used as a fragment comprising TET2 residues 1129-1480 joined to TET2 residues 1844-1936 by a linker (SEQ ID NO: 5 of the present application) as described, e.g., in US Patent 10,961,525. In some embodiments, the one or more TET enzymes comprise TET1 and TET2. In some embodiments, the one or more TET enzymes comprise a T1372 TET mutant, such as T1372S. In some embodiments, the one or more TET enzymes comprise a VI 900 TET mutant, such as a VI 900 A, V1900C, V1900G, VI 9001, or V1900P TET mutant. In some embodiments, the one or more TET enzymes comprise a VI 900 TET2 mutant, such as a V1900A, V1900C, V1900G, VI 9001, or V1900P TET2 mutant. Examples of VI 900 A, V1900C, V1900G, VI 9001, and V1900P TET2 mutants are provided as SEQ ID NOs: 6-10. In some embodiments, the VI 900 TET mutant has at least 80%, 85%, 90%, 95%, 96%, 97%, 98%, or 99% sequence identity to SEQ ID NO: 6, 7, 8, 9, or 10. Position 1900 of the wild-type TET2 sequence corresponds to position 438 in each of SEQ ID NOs: 5-10. It can be beneficial to use a TET enzyme that maximizes formation of 5-carboxylcytosine (5-caC) relative to less oxidized modified cytosines, particularly 5-formylcytosine, because 5-caC is not a substrate for enzymatic deamination, e.g., by APOBEC enzymes such as APOBEC3A. Maximizing formation of 5-caC thus reduces the risk of false calls in which a base is identified as unmethylated because it underwent deamination even though it was methylated (orhydroxymethylated) in the original sample. Accordingly, in some embodiments, the TET enzyme comprises a mutation that increases formation of 5-caC. Exemplary mutations are set forth above. “A mutation that increases formation of 5-caC” means that the TET enzyme having the mutation produces more 5-caC than a TET enzyme that lacks the mutation but is otherwise identical. 5-caC production can be measured as described, e.g., in Liu et al., Nat Chem Biol 13: 181-187 (2017) (see Online Methods section, TET reactions in vitro subsection, “driving” conditions). Any variants and / or mutants described in Liu et al. (2017) can be used in the disclosed methods as appropriate.[000359] In some embodiments, the one or more TET enzymes comprise a TET2 enzyme comprising a T1372S mutation, such as TET2-CS-T1372S and TET2-CD-T1372S. Examples of TET2-CS-T1372S and TET2-CD-T1372S are provided as SEQ ID NOs: 11 and 12. A TET2 comprising a T1372S mutation is described in US Patent 10,961,525 and may be expressed and used as a fragment comprising TET2 residues 1129-1480 joined to TET2 residues 1844-1936 by a linker. Position 1372 of TET2 corresponds to position 258 of SEQ ID NO: 21 (wild type TET2 catalytic domain) of US Patent 10,961,525. Thus, the sequence of a T1372S TET2 catalytic domain may be obtained by changing the threonine at position 258 of SEQ ID NO: 21 of US Patent 10,961,525 to serine. TET2 comprising a T1372S mutation is also described in Liu et al., Nat Chem Biol. 2017 February; 13(2): 181-187. As demonstrated in Liu et al., TET2 comprising a T1372S mutation can more efficiently oxidize 5mC to produce 5-carboxylcytosine (5-caC) than other versions of TET2 such as TET2 lacking a T1372S mutation. In some embodiments, the TET2 enzyme comprises SEQ ID NO: 14 or optionally a variant of SEQ ID NO: 14 in which at least 5, 6, 7, or 8 positions match SEQ ID NO: 14 including position 5 of SEQ ID NO: 14. In some embodiments, the TET2 enzyme is a human TET2 enzyme comprising a T1372S mutation. In some embodiments, the TET2 enzyme comprises the sequence of SEQ ID NO: 11. In some embodiments, the TET2 enzyme comprises a sequence having at least 80%, 85%, 90%, 95%, 96%, 97%, 98%, or 99% identity to SEQ ID NO: 11. In some embodiments, the TET2 enzyme comprises a sequence having at least 80%, 85%, 90%, 95%, 96%, 97%, 98%, or 99% identity to SEQ ID NO: 12. In some embodiments, the TET2 enzyme comprises the sequence of SEQ ID NO: 12. The sequences of SEQ ID NOs: 11 and 12 are shown below.[000360] In some embodiments, the deaminase is thermally inactivated after contacting DNA with the deaminase. In some embodiments, the thermal inactivation comprises heating or cooling of the deaminase to a temperature at which the deaminase has reduced or inhibited activityrelative to a deaminase that has not been subjected to heating or cooling. In some embodiments, the thermal inactivation completely inhibits the activity of the deaminase or reduces the activity of the deaminase by at least about 5%, about 10%, about 15%, about 20%, about 25%, about 50%, about 75%, about 90%, about 95%, about 98%, about 99%, or 100% relative to a deaminase that has not been subjected to heating or cooling.G. Contacting DNA with a Methylation-sensitive or Methylation-dependent Nuclease[000361] In some embodiments, DNA or a subsample thereof (e.g., a first, second, or third subsample prepared by partitioning a DNA sample as described herein, such as on the basis of a level of a cytosine modification, such as methylation, e.g., 5-methylation, such as of cytosine) or DNA contained in a sample is contacted with a methylation-dependent nuclease or methylationsensitive nuclease. The contacting can be performed using a sample that has been divided into a plurality of subsamples as disclosed herein, and / or using a sample that has been partitioned into a plurality of subsamples as disclosed herein. Unless otherwise indicated, where partitioning is performed on the basis of a cytosine modification, the first subsample of DNA is the subsample with a higher level of the modification; the second subsample is the subsample with a lower level of the modification; and, when present, the third subsample has a level of the modification intermediate between the first and second subsamples has a level of the modification intermediate between the first and second subsamples.[000362] In some embodiments, methods herein comprise contacting DNA with a methylationsensitive nuclease, thereby degrading DNA comprising unmethylated sequences or sequences having low levels of methylation. In some such embodiments, the methylation-sensitive nuclease is a methylation-sensitive restriction enzyme (MSRE), thereby degrading DNA comprising an unmethylated recognition site of the MSRE. Methylation-sensitive nucleases can thus be used in methods herein comprising one or more steps that deplete unmodified or unmethylated sequences, such as those that are prevalent in cfDNA from a subject.[000363] In some embodiments, methods herein comprise contacting DNA with a methylationdependent nuclease, thereby degrading DNA comprising methylated sequences or sequences having high levels of methylation. In some such embodiments, the methylation-dependent nuclease is a methylation-dependent restriction enzyme (MDRE), thereby degrading DNA comprising a methylated recognition site of the MDRE. Methylation-dependent nucleases canthus be used in methods herein comprising one or more steps that deplete modified or methylated sequences, such as those that are prevalent in cfDNA from a subject.[000364] As discussed above, partitioning procedures may result in imperfect sorting of DNA molecules among the subsamples. The choice of a methylation-dependent nuclease or methylation-sensitive nuclease can be made so as to degrade nonspecifically partitioned DNA. For example, the second subsample can be contacted with a methylation-dependent nuclease, such as a methylation-dependent restriction enzyme. This can degrade nonspecifically partitioned DNA in the second subsample (e.g., methylated DNA) to produce a treated second subsample. Alternatively or in addition, the first subsample can be contacted with a methylationsensitive endonuclease, such as a methylation-sensitive restriction enzyme, thereby degrading nonspecifically partitioned DNA in the first subsample to produce a treated first subsample. Degradation of nonspecifically partitioned DNA in either or both of the first or second subsamples is proposed as an improvement to the performance of methods that rely on accurate partitioning of DNA on the basis of a cytosine modification, e.g., to detect the presence of aberrantly modified DNA in a sample, to determine the tissue of origin of DNA, and / or to determine whether a subject has cancer. For example, such degradation may provide improved sensitivity and / or simplify downstream analyses. In general, where nonspecifically partitioned DNA would be hypermethylated, such as in a hypomethylated partition, a methylation-dependent nuclease, such as a methylation-dependent restriction enzyme, should be used. Conversely, where nonspecifically partitioned DNA would be hypomethylated, such as in a hypermethylated partition, a methylation-sensitive nuclease, such as a methylation-sensitive restriction enzyme, should be used. Methylation-dependent nucleases, such as methylation-dependent restriction enzymes, preferentially cut methylated DNA relative to unmethylated DNA, while methylationsensitive nucleases, such as methylation-sensitive restriction enzymes, preferentially cut unmethylated DNA relative to methylated DNA.[000365] In contacting a DNA sample or subsample with a nuclease, one or more nucleases can be used. In some embodiments, a subsample is contacted with a plurality of nucleases. The subsample may be contacted with the nucleases sequentially or simultaneously. Simultaneous use of nucleases may be advantageous when the nucleases are active under similar conditions (e.g., buffer composition) to avoid unnecessary sample manipulation. Contacting the second subsample with more than one methylation-dependent restriction enzyme can more completely degrade nonspecifically partitioned hypermethylated DNA. Similarly, contacting the firstsubsample with more than one methylation- sensitive restriction enzyme can more completely degrade nonspecifically partitioned hypomethylated and / or unmethylated DNA.[000366] In some embodiments, a methylation-dependent nuclease comprises one or more of MspJI, LpnPI, FspEI, or McrBC. In some embodiments, at least two methylation-dependent nucleases are used. In some embodiments, at least three methylation-dependent nucleases are used. In some embodiments, the methylation-dependent nuclease comprises FspEI. In some embodiments, the methylation-dependent nuclease comprises FspEI and MspJI, e.g., used sequentially.[000367] In some embodiments, a methylation-sensitive nuclease comprises one or more of Aatll, AccII, Acil, Aorl3HI, Aorl5HI, BspT104I, BssHII, BstUI, CfrlOI, Clal, Cpol, Eco52I, Haell, HapII, Hhal, Hin6I, Hpall, HpyCH4IV, Mlul, MspI, Nael, Notl, Nrul, Nsbl, PmaCI, Psp 14061, Pvul, SacII, Sall, Smal, and SnaBI. In some embodiments, at least two methylationsensitive nucleases are used. In some embodiments, at least three methylation-sensitive nucleases are used. In some embodiments, the methylation-sensitive nucleases comprise BstUI and Hpall. In some embodiments, the two methylation-sensitive nucleases comprise Hhal and AccII. In some embodiments, the methylation-sensitive nucleases comprise BstUI, Hpall and Hin6I. [000368] In some embodiments, FspEI is used for digesting the nucleic acid molecules in at least one subsample (e.g., a hypomethylated partition). In some embodiments, BstUI, Hpall and Hin6I are used for digesting the nucleic acid molecules in at least one subsample (e.g., a hypermethylated partition) and FspEI is used for digesting the nucleic acid molecules in at least one other subsample (e.g., a hypomethylated partition). In embodiments involving an intermediately methylated partition, the nucleic acid molecules therein may be digested with a methylation-sensitive nuclease or a methylation-dependent nuclease. In some embodiments, the nucleic acid molecules in an intermediately methylated partition are digested with the same nuclease(s) as the hypermethylated partition. For example, the intermediately methylated partition may be pooled with the hypermethylated partition and then the pooled partitions may be subjected to digestion. In some embodiments, the nucleic acid molecules in an intermediately methylated partition are digested with the same nuclease(s) as the hypomethylated partition. For example, the intermediately methylated partition may be pooled with the hypomethylated partition and then the pooled partitions may be subjected to digestion.[000369] In some embodiments, a subsample is contacted with a nuclease as described above after a step of tagging or attaching adapters to both ends of the DNA. The tags or adapters can beresistant to cleavage by the nuclease using any of the approaches described above. In this approach, cleavage can prevent the nonspecifically partitioned molecule from being carried through the analysis because the cleavage products lack tags or adapters at both ends.[000370] Alternatively, a step of tagging or attaching adapters can be performed after cleavage with a nuclease as described above. Cleaved molecules can be then identified in sequence reads based on having an end (point of attachment to tag or adapter) corresponding to a nuclease recognition site. Processing the molecules in this way can also allow the acquisition of information from the cleaved molecule, e.g., observation of somatic mutations. When tagging or attaching adapters after contacting the subsample with a nuclease, and low molecular weight DNA such as cfDNA is being analyzed, it may be desirable to remove high molecular weight DNA (such as contaminating genomic DNA) from the sample before the contacting step. It may also be desirable to use nucleases that can be heat-inactivated at a relatively low temperature (e g., 65°C or less, or 60°C or less) to avoid denaturing DNA, in that denaturation may interfere with subsequent ligation steps.[000371] Where a DNA sample is partitioned into three subsamples, including a third subsample containing intermediately methylated molecules, the third subsample is in some embodiments contacted with a methylation-sensitive nuclease. Such a step may have any of the features described elsewhere herein with respect to contacting steps, and may be performed before or after a step of tagging or attaching adapters as discussed above. In some embodiments, the first and third subsamples are combined before being contacted with a methylation-sensitive nuclease. Such a step may have any of the features described elsewhere herein with respect to contacting steps, and may be performed before or after a step of tagging or attaching adapters as discussed above. In some embodiments, the first and third subsamples are differentially tagged before being combined.[000372] Alternatively, where a DNA sample is partitioned into three subsamples, including a third subsample containing intermediately methylated molecules, the third subsample is in some embodiments contacted with a methylation-dependent nuclease. Such a step may have any of the features described elsewhere herein with respect to contacting steps, and may be performed before or after a step of tagging or attaching adapters as discussed above. In some embodiments, the second and third subsamples are combined before being contacted with a methylationdependent nuclease. Such a step may have any of the features described elsewhere herein with respect to contacting steps, and may be performed before or after a step of tagging or attachingadapters as discussed above. In some embodiments, the second and third subsamples are differentially tagged before being combined.[000373] In some embodiments, the DNA is purified after being contacted with the nuclease, e.g., using SPRI beads. Such purification may occur after heat inactivation of the nuclease. Alternatively, purification can be omitted; thus, for example, a subsequent step such as amplification can be performed on the subsample containing heat-inactivated nuclease. In another embodiment, the contacting step can occur in the presence of a purification reagent such as SPRI beads, e.g., to minimize losses associated with tube transfers. After cleavage and heat inactivation, the SPRI beads can be re-used for cleanup by adding molecular crowding reagents (e g., PEG) and salt.[000374] In some embodiments, DNA fragmentation is detected by determining the endpoints and / or midpoints of sequenced fragments of DNA (e.g., cfDNA). For example, differences in fragmentation patterns may occur depending on whether the fragments originated from a tumor or from healthy cells. To detect tumor-cell derived DNA of cfDNA based on fragmentation, the presence or absence of an increased level of abnormal fragments can be determined at regions with copy-number amplifications, (e.g., proportional to the degree of amplification), e.g., where the increase and abnormality are relative to control or healthy samples.[000375] In some embodiments, where a modification sensitive conversion is performed on a DNA sample or subsample, the subsequent capturing of one or more target region sets (e.g., at least an epigenetic target region set) from that sample or subsample uses target-specific probes that comprise probes specific for a modification state (e.g., of at least one base in the sequence to which the probe hybridizes), e.g., complementary to target sequences that have undergone conversion (e.g., conversion of modified or unmodified cytosines to uracils or analogs thereof, such as DHU, that preferentially pair with adenine) or that have not undergone conversion, as desired. As such, the probes can be specific for sequences in which a modification of interest, such as methylation, was or was not present. In some embodiments, where a modification sensitive conversion is performed on a sample or subsample, the subsequent capturing of one or more target region sets (e.g., at least an epigenetic target region set) from that sample or subsample uses target-specific probes that comprise probes that can hybridize to target sequences regardless of modification state (e.g., comprise a promiscuously pairing nucleobase at a position that may or may not have undergone conversion of modified or unmodified cytosines to uracilsor analogs thereof, such as DHU, that preferentially pair with adenine; for example, inosine can pair with C or U).[000376] In some embodiments, the methods comprise preparing a pool comprising at least a portion of the DNA of the second subsample (also referred to as the hypomethylated partition) and at least a portion of the DNA of the first subsample (also referred to as the hypermethylated partition). Target regions, e.g., including epigenetic target regions and / or sequence-variable target regions, may be captured from the pool. The steps of capturing a target region set from at least a portion of a subsample described elsewhere herein encompass capture steps performed on a pool comprising DNA from the first and second subsamples. A step of amplifying DNA in the pool may be performed before capturing target regions from the pool. The capturing step may have any of the features described elsewhere herein.[000377] The epigenetic target regions may show differences in methylation levels and / or fragmentation patterns depending on whether they originated from a tumor or from healthy cells, or what type of tissue they originated from, as discussed elsewhere herein. The sequencevariable target regions may show differences in sequence depending on whether they originated from a tumor or from healthy cells.[000378] Analysis of epigenetic target regions from the hypomethylated partition may be less informative in some applications than analysis of sequence-variable target-regions from the hypermethylated and hypomethylated partitions and epigenetic target regions from the hypermethylated partition. As such, in methods where sequence-variable target-regions and epigenetic target regions are being captured, the latter may be captured to a lesser extent than one or more of the sequence-variable target-regions from the hypermethylated and hypomethylated partitions and epigenetic target regions from the hypermethylated partition. For example, sequence-variable target regions can be captured from the portion of the hypomethylated partition not pooled with the hypermethylated partition, and the pool can be prepared with some (e g., a majority, substantially all, or all) of the DNA from the hypermethylated partition and none or some (e.g., a minority) of the DNA from the hypomethylated partition. Such approaches can reduce or eliminate sequencing of epigenetic target regions from the hypomethylated partition, thereby reducing the amount of sequencing data that suffices for further analysis. [000379] In some embodiments, including a minority of the DNA of the hypomethylated partition in the pool facilitates quantification of one or more epigenetic features (e.g.,methylation or other epigenetic feature(s) discussed in detail elsewhere herein), e.g., on a relative basis.[000380] In some embodiments, the pool comprises a minority of the DNA of the hypomethylated partition, e.g., less than about 50% of the DNA of the hypomethylated partition, such as less than or equal to about 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, or 5% of the DNA of the hypomethylated partition. In some embodiments, the pool comprises about 5%-25% of the DNA of the hypomethylated partition. In some embodiments, the pool comprises about 10%-20% of the DNA of the hypomethylated partition. In some embodiments, the pool comprises about 10% of the DNA of the hypomethylated partition. In some embodiments, the pool comprises about 15% of the DNA of the hypomethylated partition. In some embodiments, the pool comprises about 20% of the DNA of the hypomethylated partition.[000381] In some embodiments, the pool comprises a portion of the hypermethylated partition, which may be at least about 50% of the DNA of the hypermethylated partition. For example, the pool may comprise at least about 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% of the DNA of the hypermethylated partition. In some embodiments, the pool comprises 50-55%, 55- 60%, 60-65%, 65-70%, 70-75%, 75-80%, 80-85%, 85-90%, 90-95%, or 95-100% of the DNA of the hypermethylated partition. In some embodiments, the second pool comprises all or substantially all of the hypermethylated partition.[000382] In some embodiments, the methods comprise preparing a first pool comprising at least a portion of the DNA of the hypomethylated partition. In some embodiments, the methods comprise preparing a second pool comprising at least a portion of the DNA of the hypermethylated partition. In some embodiments, the first pool further comprises a portion of the DNA of the hypermethylated partition. In some embodiments, the second pool further comprises a portion of the DNA of the hypomethylated partition. In some embodiments, the first pool comprises a majority of the DNA of the hypomethylated partition, and optionally and a minority of the DNA of the hypermethylated partition. In some embodiments, the second pool comprises a majority of the DNA of the hypermethylated partition and a minority of the DNA of the hypomethylated partition. In some embodiments involving an intermediately methylated partition, the second pool comprises at least a portion of the DNA of the intermediately methylated partition, e.g., a majority of the DNA of the intermediately methylated partition. In some embodiments, the first pool comprises a majority of the DNA of the hypomethylatedpartition, and the second pool comprises a majority of the DNA of the hypermethylated partition and a majority of the DNA of the intermediately methylated partition.[000383] In some embodiments, the methods comprise capturing at least a first set of target regions from the first pool, e.g., wherein the first pool is as set forth in any of the embodiments above. In some embodiments, the first set comprises sequence-variable target regions. In some embodiments, the first set comprises hypomethylation variable target regions and / or fragmentation variable target regions. In some embodiments, the first set comprises sequencevariable target regions and fragmentation variable target regions. In some embodiments, the first set comprises sequence-variable target regions, hypomethylation variable target regions and fragmentation variable target regions. A step of amplifying DNA in the first pool may be performed before this capture step. In some embodiments, capturing the first set of target regions from the first pool comprises contacting the DNA of the first pool with a first set of targetspecific probes. In some embodiments, the first set of target-specific probes comprises targetbinding probes specific for the sequence-variable target regions. In some embodiments, the first set of target-specific probes comprises target-binding probes specific for the sequence-variable target regions, hypomethylation variable target regions and / or fragmentation variable target regions.[000384] In some embodiments, the methods comprise capturing a second set of target regions or plurality of sets of target regions from the second pool, e.g., wherein the first pool is as set forth in any of the embodiments above. In some embodiments, the second plurality comprises epigenetic target regions, such as hypermethylation variable target regions and / or fragmentation variable target regions. In some embodiments, the second plurality comprises sequence-variable target regions and epigenetic target regions, such as hypermethylation variable target regions and / or fragmentation variable target regions. A step of amplifying DNA in the second pool may be performed before this capture step. In some embodiments, capturing the second plurality of sets of target regions from the second pool comprises contacting the DNA of the first pool with a second set of target-specific probes, wherein the second set of target-specific probes comprises target-binding probes specific for the sequence-variable target regions and target-binding probes specific for the epigenetic target regions. In some embodiments, the first set of target regions and the second set of target regions are not identical. For example, the first set of target regions may comprise one or more target regions not present in the second set of target regions. Alternatively or in addition, the second set of target regions may comprise one or more target regions notpresent in the first set of target regions. In some embodiments, at least one hypermethylation variable target region is captured from the second pool but not from the first pool. In some embodiments, a plurality of hypermethylation variable target regions are captured from the second pool but not from the first pool. In some embodiments, the first set of target regions comprises sequence-variable target regions and / or the second set of target regions comprises epigenetic target regions. In some embodiments, the first set of target regions comprises sequence-variable target regions, and fragmentation variable target regions; and the second set of target regions comprises epigenetic target regions, such as hypermethylation variable target regions and fragmentation variable target regions. In some embodiments, the first set of target regions comprises sequence-variable target regions, fragmentation variable target regions, and comprises hypomethylation variable target regions; and the second set of target regions comprises epigenetic target regions, such as hypermethylation variable target regions and fragmentation variable target regions.[000385] In some embodiments, the first pool comprises a majority of the DNA of the hypomethylated partition and a portion of the DNA of the hypermethylated partition (e.g., about half), and the second pool comprises a portion of the DNA of the hypermethylated partition (e.g., about half). In some such embodiments, the first set of target regions comprises sequencevariable target regions and / or the second set of target regions comprises epigenetic target regions. The sequence-variable target regions and / or the epigenetic target regions may be as set forth in any of the embodiments described elsewhere herein.H. Ligation to Adapters[000386] In some embodiments, the methods comprise ligating adapters to DNA. In some embodiments, the ligating adapters to DNA produces adapter-ligated DNA. In some embodiments, DNA molecules can be subjected to blunt-end ligation with blunt-ended adapters. In some embodiments, DNA molecules can be subjected to sticky-end ligation with sticky-ended adapters. DNA molecules can be ligated to adapters at either one end or both ends. DNA molecules can be ligated with at least partially double stranded adapter (e.g., a Y shaped or bellshaped adapter).[000387] In some embodiments, the ligation step can take place prior to or after sequencing the DNA. In some embodiments, the ligation step can take place prior to sequencing the DNA. In some embodiments, the ligation step can take place prior to or after capturing the DNA. In someembodiments, the ligation step can take place prior to capturing the DNA. In some embodiments, the ligation step can take place prior to or after capturing the DNA and prior to or after sequencing the DNA. In some embodiments, the ligation step can take place after capturing the DNA and prior to sequencing the DNA. In some embodiments, the ligation step can take place prior to or after partitioning the DNA into a plurality of subsamples. In some embodiments, the ligation step can take place prior to partitioning the DNA into a plurality of subsamples. In some embodiments, the ligation step can take place prior to or after partitioning the DNA into a plurality of subsamples and prior to or after sequencing the DNA. In some embodiments, the ligation step can take place after partitioning the DNA into a plurality of subsamples and prior to the sequencing the DNA. In some embodiments, the ligation step can take place prior to or after subjecting the sample or one or more subsamples to a procedure that affects a first nucleobase in the DNA differently from a second nucleobase. In some embodiments, the ligation step can take place prior to subjecting the sample or one or more subsamples to a procedure that affects a first nucleobase in the DNA differently from a second nucleobase. In some embodiments, the ligation step can take place prior to or after the subjecting the sample or one or more subsamples to a procedure that affects a first nucleobase in the DNA differently from a second nucleobase and prior to or after the sequencing the DNA. In some embodiments, the ligation step can take place after subjecting the sample or one or more subsamples to a procedure that affects a first nucleobase in the DNA differently from a second nucleobase and prior to the sequencing the DNA.[000388] In some embodiments, the procedure that affects a first nucleobase in the DNA differently from a second nucleobase is a conversion step. In some embodiments, the ligation step can take place before or after the conversion step. In general, “conversion step” or “conversion procedure” refers to any step or procedure that changes the base pairing specificity of one or more nucleotides. In some embodiments, the conversion step comprises contacting DNA with a deaminase.[000389] DNA ligase and adapters are added to ligate DNA molecules in the sample with an adapter on one or both ends, i.e. to form adapted DNA. As used herein, “adapter” refers to short nucleic acids (e.g., less than about 500, less than about 100 or less than about 50 nucleotides in length, or be 20-30, 20-40, 30-50, 30-60, 40-60, 40-70, 50-60, 50-70, 20-500, or 30-100 bases from end to end) that are typically at least partially double-stranded and can be ligated to the endof a given sample DNA molecule. In some instances, two adapters can be ligated to a single sample DNA molecule, with one adapter ligated to each end of the sample nucleic acid molecule. [000390] In some embodiments, the ligase used in ligation reactions can act on both single strand DNA nicks and double stranded DNA ends. In some cases, the ligase is T4 DNA ligase or T3 DNA ligase. Adapters can include nucleic acid primer binding sites to permit amplification of a sample DNA molecule flanked by adapters at both ends, and / or a sequencing primer binding site, including primer binding sites for sequencing applications, such as various next generation sequencing (NGS) applications. Adapters can include a sequence for hybridizing to a solid support, e.g., a flow cell sequence. Adapters can also include binding sites for capture probes, such as an oligonucleotide attached to a flow cell support or the like. Adapters can also include sample indexes and / or molecular barcodes. These are typically positioned relative to amplification primer and sequencing primer binding sites, such that the sample index and / or molecular barcode is included in amplicons and sequencing reads of a given DNA molecule. Adapters of the same or different sequence can be linked to the respective ends of a sample DNA molecule. In some cases, adapters of the same or different sequence are linked to the respective ends of the DNA molecule except that the sample index and / or molecular barcode differs in its sequence. In some embodiments, the adapter is a Y-shaped adapter in which one end is blunt ended or tailed as described herein, for joining to a nucleic acid molecule, which is also blunt ended or tailed with one or more complementary nucleotides to those in the tail of the adapter. In another exemplary embodiment, an adapter is a bell-shaped adapter that includes a blunt or tailed end for joining to a DNA molecule to be analyzed. Other exemplary adapters include T-tailed, C- tailed or hairpin shaped adapters. For example, a hairpin shaped adapter can comprise a complementary double stranded portion and a loop portion, where the double stranded portion can be attached (e.g. ligated) to a double-stranded polynucleotide. Hairpin shaped sequencing adapters can be attached to both ends of a polynucleotide fragment to generate a circular molecule, which can be sequenced multiple times. The adapters used in the methods of the present disclosure comprise one or more known modified nucleosides, such as methylated nucleosides. In some embodiments, the modified nucleosides comprise modification resistant cytosines. In some embodiments, each cytosine in each adapter is a modification resistant cytosine. In some embodiments, the modification resistant cytosine is a deamination resistant cytosine. In some embodiments, the deamination resistant cytosine comprises 5-propynylC (5pyC), 5-pyrrolo-dC (5pyrC), 5-hydroxymethylcytosine (5hmC), glucosylated5-hydroxymethylcytosine (5ghmC), cytosine 5-methylenesulfonate (CMS), or N4-modified cytosine. In some embodiments, the adapters are resistant to digestion by a (methylation resistant restriction enzyme) MSRE. In some embodiments, the MSRE digestion-resistant adapters comprise one or more methylated nucleotides (e.g., 5-methylcytosine, 5-hydroxymethylcytosine, or a combination thereof), comprise one or more nucleotide analogs resistant to methylation sensitive restriction enzymes, or do not comprise a nucleotide sequence recognized by the MSRE. In some embodiments, the one or more methylated nucleotides in the MSRE digestionresistant adapters comprise 5-methylcytosine and / or 5-hydroxymethylcytosine. In some embodiments, the adapters are resistant to digestion by a methylation dependent restriction enzyme (MDRE). In some embodiments, the MDRE digestion-resistant adapters comprise one or more unmethylated nucleotides, comprise one or more nucleotide analogs resistant to methylation dependent restriction enzymes, or do not comprise a nucleotide sequence recognized by the MDRE.[000391] In instances where two adapters are ligated to a sample nucleic acid (one at each end), either or both of the adapters may comprise one or more known modified nucleosides. Typically, the primer binding site(s), sequencing primer binding site(s), sample index(es) and / or molecular barcode(s), if present, do not comprise the known modified nucleosides that change base pairing specificity as a result of the conversion procedure.[000392] In some embodiments, adapters may be added to the DNA or a subsample thereof. Adapters can be ligated to DNA at any point in the methods herein. In some embodiments, adapters are ligated to the DNA in a sample. In some embodiments, adapters are ligated to the DNA of a sample or subsample thereof prior to annealing primers to the DNA for capture probe generation. In some such embodiments, the adapter-ligated DNA is amplified prior to annealing primers to the DNA for capture probe generation. In some embodiments, adapters are ligated to the DNA of a sample or subsample thereof before the DNA is contacted with the capture probes. In some embodiments, the DNA to which the adapters are ligated is in the same sample or subsample as the DNA used as a template to generate capture probes. In some embodiments, the DNA to which the adapters are ligated is in a different sample or subsample, e.g., a second sample or a second subsample of a first sample, than the DNA used as a template to generate capture probes. In some embodiments, the adapters ligated to DNA captured by the capture probes.[000393] In some embodiments, the primers used to generate capture probes are not complementary to adapters, and the resulting capture probes therefore do not comprise adapters. Adapter-ligated DNA can therefore be selectively amplified in the presence of capture probes that do not comprise adapters. Similarly, adapter-ligated DNA can be separated from DNA that does not comprise adapters.[000394] In some embodiments, the disclosed methods comprise analyzing DNA in a sample. In such methods, adapters may be added to the DNA. This may be done concurrently with an amplification procedure, e.g., by providing the adapters in a 5’ portion of a primer (where PCR is used, this can be referred to as library prep-PCR or LP-PCR), before, or after an amplification step. In some embodiments, adapters are added by other approaches, such as ligation. In some such methods, first adapters are added to the 3’ ends of the nucleic acids by ligation, which may include ligation to single- stranded DNA. In some embodiments, prior to any partitioning or capturing steps, first adapters are added to the nucleic acids by ligation, which may include ligation to single-stranded DNA (e.g., to the 3’ ends thereof). In some embodiments, the capture probes can be isolated after partitioning and ligation. For example, the hypomethylated partition can be ligated with adapters and a portion of the ligated hypomethylated partition can then be used to generate the capture probes for rearrangements. The adapter can be used as a priming site for second-strand synthesis, e.g., using a universal primer and a DNA polymerase. A second adapter can then be ligated to at least the 3’ end of the second strand of the now double-stranded molecule. In some embodiments, the first adapter comprises an affinity tag, such as biotin, and nucleic acid ligated to the first adapter is bound to a solid support (e.g., bead), which may comprise a binding partner for the affinity tag such as streptavidin. For further discussion of a related procedure, see Gansauge et al., Nature Protocols 8:737-748 (2013). Commercial kits for sequencing library preparation compatible with single-stranded nucleic acids are available, e.g., the Accel-NGS® Methyl-Seq DNA Library Kit from Swift Biosciences. In some embodiments, after adapter ligation, nucleic acids are amplified.[000395] In some embodiments, the single-stranded DNA library preparation is performed in a one-step combined phosphorylation / ligation reaction, e.g., as described in Troll et al., BMC Genomics, 20: 1023 (2019), available at https: / / doi.org / 10.1186 / sl2864-019-6355-0. This method, called Single Reaction Single-stranded LibrarY (“SRSLY,”) can be performed without end-polishing. SRSLY may be useful for converting short and fragmented DNA molecules, e.g., cfDNA fragments, into sequencing libraries while retaining native lengths and ends. The SRSLYmethod can create sequencing libraries (e.g., Illumina sequencing libraries) from fragmented or degraded template (input) DNA. In particular embodiments, template DNA is first heat denatured and then immediately cold shocked to render the template DNA molecules singlestranded. The DNA can be maintained as single-stranded throughout the ligation reaction by the inclusion of a thermostable single-stranded binding protein (SSB). Next, the template DNA, which at this point can be single-stranded and coated with SSB, is placed in a phosphorylation / ligation dual reaction with directional dsDNA NGS adapters that contain singlestranded overhangs. Both the forward and reverse sequencing adapters can share similar structures but differ in which termini is unblocked in order to facilitate proper ligations. Both sequencing adapters can comprise a dsDNA portion and a single-stranded splint overhang of random nucleotides that occurs on the 3 -prime terminus of the bottom strand of the forward adapter and the 5-prime terminus of the bottom strand of the reverse adapter. In this way, the forward adapter (e g., (P5) Illumina adapter) can be delivered to the 5-prime end of template molecules and the reverse adapter (e.g., (P7) Illumina adapter) is delivered to the 3-prime end of template molecules. Thus, the native polarity of input DNA molecules can be retained.[000396] During the dual phosphorylation / ligation reaction, T4 Polynucleotide Kinase (PNK) can be used to prepare template DNA termini for ligation by phosphorylating 5-prime termini and dephosphorylating 3-prime termini. T4 PNK works on both ssDNA and dsDNA molecules and has no activity on the phosphorylation state of proteins. Simultaneously, the random nucleotides of the splint adapter can be annealed to the single- stranded template molecule. This creates a short, localized dsDNA molecule, enabling ligation of template to adapter with a ligase such as T4 DNA ligase, which has high ligation efficiency on dsDNA templates but low efficiency on ssDNA. After the single phosphorylation / ligation reaction is complete, the library DNA can be, e.g., purified and placed directly into standard NGS indexing PCR, compatible with both traditional single or dual index primers.[000397] In some embodiments, the adapters include different tags of sufficient numbers that the number of combinations of tags results in a low probability e.g., 95, 99 or 99.9% of two nucleic acids with the same start and stop points receiving the same combination of tags. Adapters, whether bearing the same or different tags, can include the same or different primer binding sites, but preferably adapters include the same primer binding site.[000398] In some embodiments, following attachment of adapters, the nucleic acids are subject to amplification. The amplification can use, e.g., universal primers that recognize primer binding sites in the adapters.[000399] In some embodiments, following attachment of adapters, the DNA or a subsample or portion of the DNA is partitioned, comprising contacting the DNA with an agent that preferentially binds to nucleic acids bearing an epigenetic modification. The nucleic acids are partitioned into at least two partitioned subsamples differing in the extent to which the nucleic acids bear the modification from binding to the agents. For example, if the agent has affinity for nucleic acids bearing the modification, nucleic acids overrepresented in the modification (compared with median representation in the population) preferentially bind to the agent, whereas nucleic acids underrepresented for the modification do not bind or are more easily eluted from the agent. The nucleic acids can then be amplified from primers binding to the primer binding sites within the adapters. Partitioning may be performed instead before adapter attachment, in which case the adapters may comprise differential tags that include a component that identifies which partition a molecule occurred in.[000400] In some embodiments, the nucleic acids are linked at both ends to Y-shaped adapters including primer binding sites and tags. The molecules are amplified.I. Molecular Tagging[000401] In some embodiments, the DNA molecules may be tagged with sample indexes and / or molecular barcodes (referred to generally as “tags”). In some embodiments, the DNA molecules of the sample comprise barcodes. Tags can be molecules, such as nucleic acids, containing information that indicates a feature of the molecule with which the tag is associated. For example, DNA molecules can bear a sample tag or sample index (which distinguishes molecules in one sample from those in a different sample), a partition tag (which distinguishes molecules in one partition from those in a different partition) and / or a molecular tag / molecular barcode (which distinguishes different molecules from one another (in both unique and non-unique tagging scenarios).[000402] Tagging strategies can be divided into unique tagging and non-unique tagging strategies. In unique tagging, all or substantially all of the molecules in a sample bear a different tag, so that reads can be assigned to original molecules based on tag information alone. Tags used in such methods are sometimes referred to as “unique tags”. In non-unique tagging,different molecules in the same sample can bear the same tag, so that other information in addition to tag information is used to assign a sequence read to an original molecule. Such information may include start and stop coordinate, coordinate to which the molecule maps, start or stop coordinate alone, etc. Tags used in such methods are sometimes referred to as “nonunique tags”. Accordingly, it is not necessary to uniquely tag every molecule in a sample. It suffices to uniquely tag molecules falling within an identifiable class within a sample. Thus, molecules in different identifiable families can bear the same tag without loss of information about the identity of the tagged molecule.[000403] In certain embodiments, a tag can comprise one or a combination of barcodes. As used herein, the term “barcode” refers to a nucleic acid molecule having a particular nucleotide sequence, or to the nucleotide sequence, itself, depending on context. A barcode can have, for example, between 10 and 100 nucleotides. A collection of barcodes can have degenerate sequences or can have sequences having a certain Hamming distance, as desired for the specific purpose. So, for example, a molecular barcode can be comprised of one barcode or a combination of two barcodes, each attached to different ends of a molecule. Additionally or alternatively, for different partitions and / or samples, different sets of molecular barcodes, molecular tags, or molecular indexes can be used such that the barcodes serve as a molecular tag through their individual sequences and also serve to identify the partition and / or sample to which they correspond based the set of which they are a member.[000404] For example, barcodes can be used to allow the origin of the DNA (e.g., the subject, biological sample (e g., samples collected at various time points), enriched DNA sample (e.g., enriched DNA comprising an epigenetic target region set or enriched DNA comprising a sequence-variable target region set), partition, or similar) to be identified, e.g., following pooling of a plurality of samples for parallel sequencing. Tags comprising barcodes can be incorporated into or otherwise joined to adapters. Tags can be incorporated by ligation, overlap extension PCR among other methods. Tags can be used to label the individual polynucleotide population partitions so as to correlate the tag (or tags) with a specific partition. Alternatively, tags can be used in embodiments of the disclosure that do not employ a partitioning step. In some embodiments, a single tag can be used to label a specific partition. In some embodiments, multiple different tags can be used to label a specific partition. In embodiments employing multiple different tags to label a specific partition, the set of tags used to label one partition can be readily differentiated for the set of tags used to label other partitions. In some embodiments,the tags may have additional functions, for example the tags can be used to index sample sources or used as unique molecular identifiers (which can be used to improve the quality of sequencing data by differentiating sequencing errors from mutations, for example as in Kinde et al., Proc Nat’ 1 Acad Sci USA 108: 9530-9535 (2011), Kou et al., PLoS ONE,11 e0146638 (2016)) or used as non-unique molecule identifiers, for example as described in US Pat. No. 9,598,731. Similarly, in some embodiments, the tags may have additional functions, for example the tags can be used to index sample sources or used as non-unique molecular identifiers (which can be used to improve the quality of sequencing data by differentiating sequencing errors from mutations).[000405] Tags may be incorporated into or otherwise joined to adapters by chemical synthesis, ligation (e.g., as described above, e.g. by blunt-end ligation or sticky-end ligation), or overlap extension polymerase chain reaction (PCR), among other methods. Such adapters are ultimately joined to the sample DNA molecule. In other embodiments, one or more rounds of amplification cycles (e.g., PCR amplification) may be applied to introduce sample indexes to a nucleic acid molecule using conventional nucleic acid amplification methods. The amplifications may be conducted in one or more reaction mixtures (e.g., a plurality of microwells in an array). Molecular barcodes and / or sample indexes may be introduced simultaneously, or in any sequential order. In some embodiments, molecular barcodes and / or sample indexes are introduced prior to and / or after any conversion procedure. In the case of molecular barcodes and / or sample indexes being introduced through amplification processes, the conversion step will occur before the molecular barcodes and / or sample indexes are introduced. In some embodiments, molecular barcodes and / or sample indexes are introduced prior to and / or after sequence capturing steps, if present, are performed. In some embodiments, only the molecular barcodes are introduced prior to probe capturing and the sample indexes are introduced after sequence capturing steps are performed. In some embodiments, both the molecular barcodes and the sample indexes are introduced prior to performing probe-based capturing steps, if present. In some embodiments, the sample indexes are introduced after sequence capturing steps are performed, if present. In some embodiments, sample indexes are incorporated through overlap extension polymerase chain reaction (PCR).[000406] In some embodiments, the tags may be located at one end or at both ends of the sample DNA molecule. In some embodiments, tags are predetermined or random or semi-random sequence oligonucleotides. In some embodiments, the tag(s) may together be less than about 500,200, 100, 50, 20, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 nucleotides in length. Typically tags are about 5 to 20 or 6 to 15 nucleotides in length. The tags may be linked to sample DNA molecules randomly or non-randomly.[000407] In some embodiments, each sample or partition (discussed below) is uniquely tagged with a sample index or a combination of sample indexes. In some embodiments, each nucleic acid molecule of a sample or sub-sample is uniquely tagged with a molecular barcode or a combination of molecular barcodes. In other embodiments, a plurality of molecular barcodes may be used such that molecular barcodes are not necessarily unique to one another in the plurality (e.g., non-unique molecular barcodes). In these embodiments, molecular barcodes are generally attached (e.g., by ligation as part of an adapter) to individual molecules such that the combination of the molecular barcode and the sequence it may be attached to creates a unique sequence that may be individually tracked. Detection of non-unique molecular barcodes in combination with endogenous sequence information (e.g., the beginning (start) and / or end (stop) genomic location / position corresponding to the sequence of the original DNA molecule in the sample, start and stop genomic positions corresponding to the sequence of the original DNA molecule in the sample, the beginning (start) and / or end (stop) genomic location / position of the sequence read that is mapped to the reference sequence, start and stop genomic positions of the sequence read that is mapped to the reference sequence, sub -sequences of sequence reads at one or both ends, length of sequence reads, and / or length of the original DNA molecule in the sample) typically allows for the assignment of a unique identity to a particular molecule. In some embodiments, beginning region comprises the first 1, first 2, the first 5, the first 10, the first 15, the first 20, the first 25, the first 30 or at least the first 30 base positions at the 5' end of the sequencing read that align to the reference sequence. In some embodiments, the end region comprises the last 1, last 2, the last 5, the last 10, the last 15, the last 20, the last 25, the last 30 or at least the last 30 base positions at the 3' end of the sequencing read that align to the reference sequence. The length, or number of base pairs, of an individual sequence read are also optionally used to assign a unique identity to a given molecule. As described herein, fragments from a single strand of nucleic acid having been assigned a unique identity, may thereby permit subsequent identification of fragments from the parent strand, and / or a complementary strand. [000408] In certain embodiments of non-unique tagging, the number of different tags used can be sufficient that there is a very high likelihood (e.g., at least 99%, at least 99.9%, at least 99.99% or at least 99.999% that all DNA molecules of a particular group bear a different tag. Itis to be noted that when barcodes are used as tags, and when barcodes are attached, e.g., randomly, to both ends of a molecule, the combination of barcodes, together, can constitute a tag. This number, in term, is a function of the number of molecules falling into the calls. For example, the class may be all molecules mapping to the same start-stop position on a reference genome. The class may be all molecules mapping across a particular genetic locus, e.g., a particular base or a particular region (e.g., up to 100 bases or a gene or an exon of a gene). [000409] In certain embodiments, the number of different tags used to uniquely identify a number of molecules, z, in a class can be between any of 2*z, 3*z, 4*z, 5*z, 6*z, 7*z, 8*z, 9*z, 10*z, 11 *z, 12*z, 13*z, 14*z, 15*z, 16*z, 17*z, 18*z, 19*z, 20*z or 100*z (e.g., lower limit) and any of 100,000*z, 10,000*z, 1000*z or 100*z (e.g., upper limit).[000410] In some embodiments, molecular barcodes are introduced at an expected ratio of a set of identifiers (e.g., a combination of unique or non-unique molecular barcodes) to molecules in a sample. One example format uses from about 2 to about 1,000,000 different molecular barcode sequences, or from about 5 to about 150 different molecular barcode sequences, or from about 20 to about 50 different molecular barcode sequences, ligated to both ends of a target molecule. Alternativ...

Claims

What is claimed is:

1. A method of analyzing RNA in a sample from a subject, the method comprising: a) sequencing the RNA and determining expression levels for a target gene set comprising a plurality of target genes that are differentially expressed in a plurality of immune cell types and / or in samples from subjects with a disease or disorder relative to samples from healthy subjects; and b) determining(1) quantities of the immune cell types from which the RNA originated based on the expression levels; and / or(2) expression levels of the plurality of target genes; and c) determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types and / or the expression levels of the plurality of target genes.

2. The method of claim 1, wherein the plurality of immune cell types comprises one or more, or each, of neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, eosinophils, T cells, CD4+ T cells, B cells, NK cells, megakaryocytes, CD8+ central memory cells, CD8+ effector memory cells, CD4+ central memory cells, CD4+ effector memory cells, immature neutrophils, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells, follicular helper T cells; regulatory T cells (Tregs), gamma delta T cells, resting NK cells, activated NK cells, MO macrophages, Ml macrophages, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, and activated mast cells.

3. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises one or more, two or more, or three or more of CD8+ T cells, resting CD4+ memory T cells, Tregs, and naive B cells.

4. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises CD8+ T cells, resting CD4+ memory T cells, Tregs, and naive B cells.

5. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises CD8+ T cells, resting CD4+ memory T cells, and T regs.

6. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises CD8+ T cells, Tregs, and naive B cells.

7. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises CD8+ T cells, resting CD4+ memory T cells, and naive B cells.

8. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises resting CD4+ memory T cells, Tregs, and naive B cells.

9. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises CD8+ T cells.

10. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises resting CD4+ memory T cells.

11. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises Tregs.

12. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises naive B cells.

13. The method of claim 1 or claim 2, wherein the plurality of immune cell types comprises neutrophils.

14. The method of any one of the preceding claims, wherein the plurality of immune cell types comprises: a) T cells, B cells, and NK cells; b) neutrophils and lymphocytes; c) neutrophils, T cells, B cells, and NK cells;d) granulocytes and lymphocytes; or e) granulocytes, T cells, B cells, and NK cells.

15. The method of any one of the preceding claims, wherein determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types comprises determining the levels of one or more, or each, of the plurality of immune cell types relative to total blood cells.

16. The method of any one of the preceding claims, wherein determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types comprises determining the levels of one or more, or each, of the plurality of immune cell types relative to total white blood cells.

17. The method of any one of the preceding claims, wherein determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types comprises determining the levels of one or more, or each, of T, B, and NK cells relative to all lymphocytes.

18. The method of any one of the preceding claims, wherein determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types comprises determining relative proportions of neutrophils and lymphocytes.

19. The method of any one of the preceding claims, wherein determining the presence, absence, or likelihood of the disease or disorder in the subject based on the quantities of the immune cell types comprises determining relative proportions of neutrophils and one or more, or each, of T cells, B cells, and NK cells.

20. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed in an activated cell type relative to the same cell type that is not activated.

21. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed in at least (a) a first cell type that is activated relative to the same first cell type that is not activated, and (b) a second cell type that is activated relative to the same second cell type that is not activated.

22. The method of claim 20 or claim 21, wherein the activated cell type is neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, or eosinophils.

23. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed in neutrophils relative to a non-neutrophil cell type.

24. The method of the immediately preceding claim, wherein the non-neutrophil cell type is one or more, or each, of a non-immune cell type, a non-granulocyte cell type, a myeloid nongranulocyte cell type, a lymphoid cell type, lymphocytes, T cells, B cells, and NK cells.

25. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed in lymphocytes relative to a non-lymphocyte cell type.

26. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed in a first cell type relative to a second cell type different from the first cell type, and the first cell type is neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells, eosinophils, T cells, CD4+ T cells, B cells, NK cells, megakaryocytes, CD8+ central memory cells, CD8+ effector memory cells, CD4+ central memory cells, CD4+ effector memory cells, immature neutrophils, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells; follicular helper T cells; regulatory T cells (Tregs); gamma delta T cells; resting NK cells; activated NK cells, MO macrophages, Ml macrophages, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, or activated mast cells.

27. The method of the immediately preceding claim, wherein the second cell type is neutrophils, lymphocytes, plasma cells, monocytes, macrophages, dendritic cells, mast cells,eosinophils, T cells, CD4+ T cells, B cells, NK cells, megakaryocytes, CD8+ central memory cells, CD8+ effector memory cells, CD4+ central memory cells, CD4+ effector memory cells, immature neutrophils, precursor B cells, plasma cells, memory-switched B cells, plasma cells, basophils, naive B cells, memory B cells, CD8+ T cells, naive CD4+ T cells, resting CD4+ memory T cells, activated CD4+ memory T cells; follicular helper T cells; regulatory T cells (Tregs); gamma delta T cells; resting NK cells; activated NK cells, MO macrophages, Ml macrophages, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, or activated mast cells.

28. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed in a first cell type relative to a second cell type different from the first cell type, and the first cell type is B cells, T cells, or NK cells.

29. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed when the disease or disorder is present relative to when the disease or disorder is not present.

30. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed in the disease or disorder cells relative to healthy cells of the same cell type as the disease or disorder cells.

31. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed in the disease or disorder cells relative to healthy colon epithelial cells.

32. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed in the disease or disorder cells relative to a myeloid cell type or an erythroid cell type.

33. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes differentially expressed in colon epithelial cells relative to a myeloid cell type or an erythroid cell type.

34. The method of any one of the preceding claims, wherein the plurality of target genes comprises genes having above-average expression variance in a training set comprising gene expression data from samples from healthy subjects and from subjects with the disease or disorder.

35. The method of claim 34, wherein the genes having above-average expression variance comprise genes having an expression variance in the top 25th, top 20th, top 15th, top 10th, top 9th, top 8th, top 7th, top 6th, top 5th, top 4th, top 3rd, top 2nd, or top 1stpercentile of the genes of the training set.

36. The method of claim 35, wherein the genes having above-average expression variance are genes with an expression variance ranking in the top 1000, top 750, top 500, top 250, top 200, top 150, top 100, top 90, top 80, top 70, top 60, top 50, top 40, top 30, top 25, top 20, top 15, top 10, or top 5 genes in the training set.

37. The method of any one of the preceding claims, wherein one or more, a majority, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or all, of the target genes are protein-coding genes.

38. The method of any one of the preceding claims, wherein the expression levels of the plurality of target genes are transcripts per million (TPM)-normalized, reads per kilobase million (RPKM)-normalized, or fragments per kilobase million (FPKM)-normalized.

39. The method of any one of the preceding claims, wherein the expression levels of the plurality of target genes are mean-centered and / or are scaled to unit variance.

40. The method of any one of the preceding claims, comprising: a) determining the presence or absence of the disease or disorder; or b) determining the likelihood of the disease or disorder.

41. The method of any one of the preceding claims, wherein determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of sex on gene expression.

42. The method of the immediately preceding claim, wherein compensating for effects of sex on gene expression comprises regressing out the effects of sex on gene expression.

43. The method of any one of the preceding claims, wherein determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of sex on cell type quantity or cell type proportion.

44. The method of the immediately preceding claim, wherein compensating for effects of sex on cell type quantity or cell type proportion comprises regressing out the effects of sex on cell type quantity or cell type proportion.

45. The method of any one of the preceding claims, wherein the target genes comprise genes that are not differentially expressed according to sex.

46. The method of the immediately preceding claim, wherein at least 50%, at least 60%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% of the target genes are not differentially expressed according to sex.

47. The method of any one of the preceding claims, wherein the target genes were identified using a training set comprising samples from individuals of the same sex as the subject.

48. The method of any one of the preceding claims, wherein the subject is female.

49. The method of any one of the preceding claims, wherein the subject is male.

50. The method of any one of the preceding claims, wherein determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of age on gene expression.

51. The method of the immediately preceding claim, wherein compensating for effects of age on gene expression comprises regressing out the effects of age on gene expression.

52. The method of any one of the preceding claims, wherein determining the presence, absence, or likelihood of the disease or disorder comprises compensating for effects of age on cell type abundance or cell type proportion.

53. The method of the immediately preceding claim, wherein compensating for effects of age on cell type abundance or cell type proportion comprises regressing out the effects of age on cell type abundance or cell type proportion.

54. The method of any one of the preceding claims, wherein the target genes comprise genes that are not differentially expressed according to age.

55. The method of the immediately preceding claim, wherein at least 50%, at least 60%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% of the target genes are not differentially expressed according to age.

56. The method of any one of the preceding claims, wherein the target genes were identified using a training set comprising samples from individuals that, at the time of sample collection from each individual, were of an age that is within 1 year, within 2 years, within 3 years, within 4 years, within 5 years, within 6 years, within 7 years, within 8 years, within 9 years, within 10 years, within 11 years, within 12 years, within 13 years, within 14 years, or within 15 years of the age of the subject at the time of sample collection from the subject.

57. The method of any one of the preceding claims, wherein the target genes comprise one or more, or each, of GZMH, PATL2, FCRL6, ZNF600, IL10RA, DTHD1, PYHIN1, HDAC11,XCL1, GZMA, RAB37, ID2, SLC9A3R1, M0SPD3, TES, EML4, CD99, ACSL6, YPEL1, H2AC17, FGFBP2, TBX21, F2R, PTGDS, DDX3Y, SYNGR1, ZNF683, SERPIN86, PRSS23, ID2, SRSF2, PRR5, CST3, SHISA4, PLAC8, BRD2, BMF, NIPAL2, UTS2, RARS2, ZNF320, RBL2, CREB3L2, RNF38, CCDC88A, MEX3C, SLC38A11, C0L19A1, PNPLA7, AFF3, STEAP1B, CELSR1, GRAPL, CBX5, AKAP6, EVL, CRISP3, BPI, MMP8, 0LFM4, MPO, MR0H6, KDM5D, IDH2, ABB, S100A4, H2AC17, GIMAP4, PPP1CB, XAF1, RPL37, PTPRO, CD177, RPS13, NAIP, RPS12, ID2, SH3BP1, RAB37, PLEKHG3, AFDN, SLC9A3R1, FLNA, SSBP3, RHOB, LIPA, ISCA1, PAG1, DDX3X, KDM5C, PIM2, IL4R, ZFX, FCGR2B, KDM6A, SARAF, TTC39C, NCOR2, ATP5MD, ARHGD1A, TRAF5, SCAMP2, RPS26, GSTM4, MICAL3, TOMM20, SSBP3, RALGDS, ITGB1, DYRK1B, ARRB1, TRIMI 1, LFNG, PAXX, ACCS, and SLC2A6.

58. The method of any one of the preceding claims, wherein the target genes comprise one or more, or each, of ICA1, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL18RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80, TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CD A, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, N0D2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MR0H7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, HLA-DOB, PGLYRP1, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIM1, HSD3B7, OSM, UPB1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYOIO, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, 0RM1, STON1, CFH,HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, C0L19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MY01B, LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1, PDGFD, NMUR1, NBEA, OLR1, PTPRM, PAWR, ABCA13, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, LI CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.

59. The method of the immediately preceding claim, wherein the target genes comprise 2, 3,4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 of ICAl, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL18RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80, TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CDA, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, NOD2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MR0H7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, HLA- DOB, PGLYRP1, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIM1, HSD3B7, OSM, UPB1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYO10, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, ORM1, STON1, CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MYO1B,LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1, PDGFD, NMUR1, NBEA, 0LR1, PTPRM, PAWR, ABCA13, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, L1CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.

60. The method of any one of the preceding claims, wherein the target genes comprise one or more, or each, of PGLYRP1, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIM1, HSD3B7, OSM, UPB1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYO10, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATCI, MAFG, IL27, ENTPD7, PLIN5, FAM228B, ORM1, and STON1.

61. The method of the immediately preceding claim, wherein the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 ofPGLYRPl, HGF, ATP9A, ATP2C2, JMJD6, DHRS9, SLC1A3, CEACAM1, DUSP13, CRISP3, ABLIM1, HSD3B7, OSM, UPB1, BIK, MMP9, SLCO4A1, BMX, KLF5, RETN, GRB10, PRUNE2, ERLIN1, TP53I3, IL1R2, EPAS1, LRRC42, GADD45A, PHTF1, RCAN3, ARG1, CYSTM1, DACH1, FKBP9, G0S2, PFKFB2, CDH26, ARMC7, PPP1R3D, ECHDC3, RDH5, ACVR1B, CKAP4, MTHFS, IL10, MFSD13A, GPR84, MYLK3, ZNF787, MYO10, RAB19, OLAH, ANKRD22, RABGEF1, SAMSN1, CACNA1D, RGL4, TFF3, GYG1, ZDHHC19, SLC51A, POC1A, HPGD, FBN1, CLEC4D, SEMA6B, PFKFB3, PAQR8, SH3PXD2B, FOSL1, MSRA, LRRN1, KCNE5, B3GNT5, CD163, CRACR2B, OPLAH, EXOSC4, KCNE1, UPP1, ST6GALNAC3, SEPTIN5, FCAR, SPATC1, MAFG, IL27, ENTPD7, PLIN5, FAM228B, ORM1, and STON1.

62. The method of any one of the preceding claims, wherein the target genes comprise one or more, or each, of ICA1, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL18RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80, TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CD A, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, N0D2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MR0H7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, and HLA-DOB.

63. The method of the immediately preceding claim, wherein the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 of ICAl, CD38, ABCB4, TNFRSF17, RRP12, CHI3L2, MAP3K13, IL4R, IL12RB2, ACHE, LAG3, CD209, GGT5, DEPDC5, UPK3A, GZMH, BPI, ACP5, CD37, MAST1, RASSF4, MS4A6A, PPFIBP1, MAK, IL18RAP, KYNU, FASLG, MYB, CCND2, TRPM6, FLVCR2, CD80, TMEM156, BHLHE41, NFE2, TREM1, TMEM255A, IL1B, PLEKHG3, VPREB3, TEP1, TRPM4, SMPDL3B, LILRB2, CHI3L1, IL2RA, TLR2, BMP2K, TNFRSF11A, PLA2G7, EPHA1, ABCB9, ZFP36L2, HHEX, SKA1, CLIC2, DUSP2, SLAMF8, CDA, ZNF222, ASGR2, PBXIP1, NIPSNAP3B, TSHR, NOD2, CD300A, NAALADL1, ADRB2, SCN9A, CEACAM3, COL8A2, CLEC7A, CTSW, HPSE, CD7, P2RY14, HIC1, P2RY13, GPR19, CCR3, MR0H7, CSF1, FAM174B, TNFRSF4, PDCD1, RYR1, HLA-DQA1, NCR3, ZBTB10, APOBEC3G, LILRA2, TNFRSF13B, and HLA- DOB.

64. The method of any one of the preceding claims, wherein the target genes comprise one or more, or each, of CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MYO IB, LARGE 1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1, PDGFD,NMUR1, NBEA, 0LR1, PTPRM, PAWR, ABC Al 3, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, L1CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.

65. The method of the immediately preceding claim, wherein the target genes comprise 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 of CFH, HS3ST1, DBNDD1, CD22, SLC25A39, KCNG1, TGFBR3, ADD2, COL19A1, CD200, TCL1A, PROCR, CD40, NME4, TSPAN13, RGS9, FAM184A, KHDRBS2, ENPP5, MMP8, SATB2, GPR68, CEACAM8, MY01B, LARGE1, NT5E, RAPGEF5, ABHD17C, ZNF365, GRTP1, IGFBP3, LCN2, GLB1L2, CNKSR2, PRSS23, RASGRP3, SCN3A, C16orf74, RETREG1, ERG, SNX22, CXCR5, BEND5, SLC1A7, LEXM, CAMK2N1, SPRY1, CDCA7L, SPIB, DLC1, DIPK1B, MTCL1, PARM1, MZB1, SLC23A1, PDGFD, NMUR1, NBEA, OLR1, PTPRM, PAWR, ABCA13, TAFA1, KCNH8, EFNA5, PRSS57, PTCHI, PRTN3, SULT1A1, ZNF667, SHISA4, L1CAM, RASGEF1A, DDR1, GPC2, PATL2, and IGLL5.

66. The method of any one of the preceding claims, wherein the method comprises preparing cDNA from the RNA and ligating adapters to the cDNA, thereby producing adapter-ligated cDNA.

67. The method of the immediately preceding claim, wherein the adapters comprise barcodes.

68. The method of claim 66 or claim 67, wherein the adapter-ligated cDNA is amplified prior to the sequencing.

69. The method of any one of the preceding claims, further comprising enriching for at least one target region set from the RNA, cDNA prepared from the RNA, or a subsample thereof, comprising contacting the RNA, cDNA prepared from the RNA, or a subsample thereof with target-specific probes specific for the at least one target region set.

70. The method of any one of the preceding claims, further comprising a step of ribosomal RNA depletion.

71. The method of any one of the preceding claims, further comprising a step of globin mRNA depletion.

72. The method of any one of claims 1-69 or 71, further comprising a step of selection of poly adenylated RNA (poly(A)) transcripts.

73. The method of any one of the preceding claims, further comprising a step of RNA fragmentation prior to the sequencing.

74. The method of the immediately preceding claim, wherein the fragmenting provides RNA fragments of 25-400, 25-300, 25-200, 50-400, 50-300, 50-250, 50-200, 100-400, 100-300, 100- 200, 125-400, 125-300, 125-200, 125-175, 150-400, 150-300, 200-400, 250-400, 300-400, 200- 350, 200-300, 225-375, 250-350, or 275-325 base pairs in length.

75. The method of any one of the preceding claims, wherein the sample is a whole blood sample.

76. The method of any one of the preceding claims, wherein the RNA comprises RNA isolated from intact cells originally present in the sample.

77. The method of any one of the preceding claims, wherein the determining quantities of each of the plurality of immune cell types or sequencing comprises generating a plurality of sequencing reads, and wherein the method further comprises mapping the plurality of sequence reads to one or more reference sequences to generate mapped sequence reads, and processing the mapped sequence reads to determine the presence or absence of the disease or disorder in the subject, or the likelihood that the subject has the disease or disorder.

78. The method of any one of the preceding claims, wherein the disease or disorder is a cancer or precancer.

79. The method of the immediately preceding claim, wherein the cancer or precancer is advanced adenoma (AA) and / or colorectal cancer (CRC).

80. The method of the immediately preceding claim, comprising: a) determining the presence or absence of AA; b) determining the likelihood of AA; c) determining the presence or absence of CRC; d) determining the likelihood of CRC; e) determining the presence or absence of AA and CRC; or f) determining the likelihood of AA and CRC.

81. The method of any one of claims 78-80, wherein the sample is obtained from a subject who was previously diagnosed with the cancer and received one or more previous cancer treatments, optionally wherein the sample is obtained at one or more preselected time points following the one or more previous cancer treatments.

82. The method of any one of claims 78-80, wherein the sample is obtained from a subject who was previously diagnosed with the cancer, and the sample is obtained from the subject before the subject receives a cancer treatment.

83. The method of any one of claims 80-82, further comprising determining a cancer recurrence score, optionally wherein a cancer recurrence status of the subject is determined to be at risk for cancer recurrence when the cancer recurrence score is determined to be at or above a predetermined threshold or the cancer recurrence status of the subject is determined to be at lower risk for cancer recurrence when the cancer recurrence score is below the predetermined threshold.

84. The method of the immediately preceding claim, further comprising comparing the cancer recurrence score of the subject with a predetermined cancer recurrence threshold, wherein the subject is classified as a candidate for a subsequent cancer treatment when the cancer recurrence score is above the cancer recurrence threshold or not a candidate for a subsequent cancer treatment when the cancer recurrence score is below the cancer recurrence threshold.

85. The method of any one of the preceding claims, further comprising evaluating or monitoring a response to a treatment in the subject.

86. The method of the immediately preceding claim, wherein the evaluating or monitoring the response to the treatment in the subject comprises comparing the expression levels for the target gene set comprising a plurality of target genes that are differentially expressed in a sample from the subject collected at at least a first time point and a sample from the subject collected at at least a second time point.

87. The method of claim 85, wherein the evaluating or monitoring the response to the treatment in the subject comprises comparing the quantities of the immune cell types in a sample from the subject collected at at least a first time point and a sample from the subject collected at at least a second time point, optionally wherein the quantities of the immune cell types are cell type abundances or cell type proportions.

88. The method of claim 86 or 87, wherein the first time point is a time point prior to administration of the treatment to the subject, and the second time point is a time point after the administration of the treatment to the subject.

89. The method of claim 86 or 87, wherein the first time point is a time point after administration of the treatment to the subject, and the second time point is a time point after the administration of the treatment to the subject and after the first time point.

90. The method of any one of the preceding claims, wherein the RNA comprises one or more of mRNA, IncRNA, or miRNA.

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