Methods and systems for processing of high-input nucleic acid samples and characterizing rare sample targets

Abstract

Provided herein are methods and compositions for analyzing target components and / or rare target components of a sample. In some cases, partitions may be provided that include portions of a nucleic acid sample. In some cases, partitions may be provided that include a rare target component. The partitions may also include processing materials. The portions of the nucleic acid sample or the rare target component may be reacted with the processing materials. In some cases, an imaging system may be used to scan the partitions. Signals generated from scanning the partitions may be used to identify a plurality of nucleic acid molecules or rare target molecules.

Description

METHODS AND SYSTEMS FOR PROCESSING OF HIGH-INPUT NUCLEIC ACID SAMPI. ES AND CHARACTERIZING RARE SAMPLE TARGETSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to and the benefit of U. S. Provisional Application Nos.: 63 / 714,848, filed October 31, 2024, 63 / 714,850, filed October 31, 2024, and 63 / 817,086, filed June 3, 2025, the entire disclosures of which are hereby incorporated by reference in their entireties.SEQUENCE LISTING

[0002] The instant application contains a sequence listing which has been submitted via Patent Center and is hereby incorporated by reference in its entirety. Said XML copy, entitled 43161-64727_001WO, was created on October 30, 2025, is 36,629 bytes in size.BACKGROUND

[0003] Legacy digital polymerase chain reaction (dPCR) platforms currently face challenges in applications involving high-input nucleic acid samples and rare molecule detection, due to manyfactors, including limited DNA input and high dead volume, which result in the loss of precious molecules, and sensitivity issues and Poisson error factors. High-input nucleic acid samples are also subject to inhibitory effects during performance of amplification reactions. Although pre-processing samples can address some of these problems, the limited number of partitions of current dPCR platforms can easily become over-saturated, requiring multiple rounds of sample dilutions as well as splitting of the sample into multiple reactions (i.e., reactions within multiple sample containers), which increases workflow time and costs, and introduces sample contamination risks.

[0004] Sensitive pathogen screening methods are crucial for early detection and treatment of infected individuals. Current assays often lack the sensitivity to identify active infections when target molecules are present in minute quantities (e.g., < 0.1 pathogen equivalents per mL of blood), especially when the rare target molecules are present in a sample having high overall nucleic acid input.

[0005] Increasing assay sensitivities for rare mutations, which often remain undetected for years, can enable earlier identification, monitoring, and treatment, and ultimately lead to improved outcomes. However, detecting rare molecular targets (e.g., in cell-tree DNA (cfDNA)) poses significantchallenges due to their extremely low abundance. The primary obstacles in rare molecule detection include: inconsistent results across tests, undermining diagnostic reliability; limited sample availability, constraining the amount of analyzable DN / X; and potential loss of rare molecules during processing, compromising detection accuracy, along with other factors. While digital PCR (dPCR) is often employed for rare molecule detection, current systems face several limitations. Traditional dPCR systems can be susceptible to the above listed obstacles. A high dead volume in cartridge designs can lead to the loss of up to 50% of rare molecules, significantly hindering accurate detection. Furthermore, microfluidic designs often limit the amount of total DNA that can be analyzed in a single reaction, reducing sensitivity for extremely rare targets.

[0006] The inventions described herein cover systems, methods, compositions, and kits for providing partition counts, workflow innovations, and detection capabilities suitable for processing high-input nucleic acid samples and detection of rare targets of a sample.SUMMARY

[0007] Aspects disclosed herein cover systems, methods, compositions, and kits that are capable of processing high-input nucleic acid samples, with a high degree of sensitivity, without requiring Poisson error correction, and with little-to-no dead volume in relation to partitioning of a sample.

[0008] Aspects also cover systems, methods, compositions, and kits for enhancing assay sensitivity by inclusion of steps for fragmenting nucleic acids of a sample (e.g., a genomic DNA (gDNA) sample), in order to enhance detection of repetitive sequences represented in the fragmented nucleic acids. The inventions can be used to detect target components (e.g., rare targets) of a sample, with extremely high sensitivity, by fragmenting long nucleic acids (e.g., gDNA) of the target components, and focusing detection on shorter sequences (e.g., repetitive sequences) that are characteristic of the target components. Described workfl ows thus increase the number of detectable components of the target components (e.g,, rare targets) in order to increase assay sensitivity (e.g,, in relation to limits of detection), where the detectable components are distributed across a large number of partitions (e.g., greater than 20 million partitions), such that each partition contains at most one fragmented component of the target component.

[0009] In a specific example, methods and systems described herein can be applied to detection of active infection associated with Chagas disease, which is caused by Trypanosoma cruzi (T. Cruzi), a parasitic protozoan. Chagas disease affects an estimated 8-10 million people globally, with 120 million at risk of disease attributed to parasitic exposure. Chagas disease is responsible forapproximately 10,000 deaths annually and a higher economic burden than other endemic diseases, such as Lyme disease. The infected are subject to a life-long, chronic infection, which can progress to cardiomyopathy and digestive tract dysfunction over time. Current molecular detection methods have limited sensitivity and often fail to identify active infection because the amount of parasitic DNA associated with T. cruzi in circulation can be very low (e.g., less than 0.1 parasite equivalents per mL of sample). Enhanced detection methods are crucial for sensitive detection of T. cruzi markers, in order to appropriately diagnose and treat infected individuals. The specific example thus leveraged high performing aspects of the methods and systems described herein to process high DNA input samples of macaque or human whole blood gDNA per reaction. Such high DNA input samples were used to increase the likelihood of detecting rare targets associated with T. cruzi, in a single reaction. This approach was possible only with the methods and systems described herein, which involve distributing a high DNA input sample across a large number of partitions (e.g., at least 30 million partitions), thereby reducing polymerase chain reaction (PCR) inhibitory effects associated with high DNA input (e.g., in comparison to legacy PCR systems). Distribution of the sample across the large number of partitions also achieves single target molecule representation in positive partitions, thereby eliminating the need for Poisson correction during analysis of signal positive partitions.

[0010] Aspects disclosed herein provide methods comprising: processing a sample comprising an amount of input nucleic acids greater than 1 microgram, for detection of a target component potentially present within a set of partitions comprising at least 30 million partitions within a single closed container, wherein processing the sample comprises: (a) generating a fragmented sample upon fragmenting nucleic acids of the sample; (b) distributing the fragmented sample across the set of partitions, wherein each partition of the set of partitions comprises a portion of the fragmented sample and processing materials; (c) reacting the processing materials of each partition of the set of partitions with the portion of the fragmented sample, thereby amplifying the target component of the sample to a level of detection of a detection system configured to scan the single closed container and count a set of positive partitions of the set of partitions, wherein a positive partition of the set of positive partitions emits a signal associated with the target component; (e) detecting the set of positive partitions upon scanning the single closed container; and (f) returning an analysis of the target component.

[0011] Aspects disclosed herein also provide methods for processing a sample for detection of a target component, the methods comprising: processing the sample comprising an amount of inputnucleic acids greater than 1 microgram, wherein the target component of the nucleic acids is within a set of partitions comprising at least 30 million partitions within a single closed container, wherein processing the sample comprises: (a) generating a fragmented sample upon fragmenting the nucleic acids of the sample; (b) distributing the fragmented sample across the set of partitions, wherein each partition of the set of partitions comprises a portion of the fragmented sample and processing materials; (c) reacting the processing materials of each partition of the set of partitions with the portion of the fragmented sample, thereby driving the target component of the sample to a level of detection of a detection system configured to scan the single closed container and count a set of positive partitions of the set of partitions, wherein a positive partition of the set of positive partitions emits a signal associated with the target component; (d) detecting the set of positive partitions upon scanning the single closed container; and (e) returning an analysis of the target component.

[0012] In a specific example, samples processed according to methods described herein can be derived from whole blood. In some embodiments, the amount of input nucleic acids comprises at least 3 micrograms. In some embodiments, the input nucleic acids comprise genomic DNA. In some embodiments, the target component comprises a parasite nucleic acid component. However, other sample types can be processed according to methods and systems described herein, as covered herein.

[0013] In a specific example, a platform executing methods described herein can provide, within a single closed container, over 30 million partitions (i.e., over 1000 times more partitions than legacy dPCR systems) for direct and precise molecular quantification of target molecules of a sample having a high amount of input DNA (e.g., over 1 microgram of input DNA, over 2 micrograms of input DNA, over 3 micrograms of input DNA, over 4 micrograms of input DNA, over 5 micrograms of input DNA, over 6 micrograms of input DNA, over 7 micrograms of input DNA, over 8 micrograms of input DNA, over 9 micrograms of input DNA, over 10 micrograms of input DNA, etc.), without requiring performance of Poisson error correction operations. The ability to partition a single sample with partition numbers that are orders of magnitude greater than that of legacy dPCR platforms can also contribute to achieving detection goals that overlap with those of next generation sequencing.

[0014] In some embodiments, the target component comprises one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component. In some embodiments, the target component comprises at least two shorter nucleotide sequences that are repetitive sequences characteristic of the target component. In some embodiments, the target componentcompnses a rare target component associated with an infectious disease agent. In some embodiments, the rare target component comprises DNA from Trypanosoma cruzi. In some embodiments, the one or more shorter nucleotide sequences of the target component comprise kinetoplast DN / X (kDNA), microsatellite DNA, or a combination thereof.

[0015] In some embodiments, generating the fragmented sample comprises performing one or more methods of fragmenting nucleic acids selected from: a physical method, an enzymatic method, and a chemical method. In some embodiments, generating the fragmented sample comprises performing a mechanical fragmentation operation on the sample. In some embodiments, the mechanical fragmentation operation comprises acoustic shearing (e.g., Covaris treatment), sonication, hydrodynamic shearing, nebulization, or a combination thereof. In some embodiments, generating the fragmented sample comprises performing an enzymatic fragmentation operation on the sample. In some embodiments, the enzymatic fragmentation operation comprises treatment with one or more restriction endonucleases. In some embodiments, the one or more restriction endonucleases are selected from: a SacI restriction endonuclease, a Msel restriction endonuclease, and isoschizomers thereof. Fragmenting can additionally or alternatively be performed using other physical, enzymatic, or chemical methods of fragmenting nucleic acids, where different mechanisms can control resultant fragment characteristics. In some embodiments, chemical fragmentation methods include the use of agents which generate hydroxyl radicals for random DNA cleavage or the use of heat with divalent metal cations, while enzyme-based methods include transposases, restriction enzymes (e.g., mung bean nucleases, nuclease Pl, or micrococcal nuclease), DNase I, non-specific nucleases, and nicking enzymes, or a mixture thereof. In some embodiments, enzyme-based DNA / RN fragmentation methods include using a mixture of at least two different enzymes e.g,, two or more of the enzymes mentioned in the preceding sentence e.g, two or more nucleases. Any standard enzymatic fragmentation buffer and enzymatic fragmentation enzyme can be used for fragmenting the DNA or RNA.

[0016] In specific examples, fragmenting of the sample provides shorter nucleotide sequences for distribution across the large number of partitions, whereby the shorter nucleotide sequences include identifying nucleotide sequences (e.g., repetitive nucleotide sequences, repetitive parasite nucleotide sequences) of the target component. Fragmentation thus significantly increases sensitivity of detection of the target component, by focusing detection on labeled shorter nucleotide sequences (e.g., short identifying nucleotide sequences associated with the target component), instead of longer genomic sequences. In some embodiments, generating the fragmented sample upon fragmenting thenucleic acids of the sample increases the sensitivity of detection of one or more shorter nucleotide sequences of the fragmented sample that is characteristic of the target component. In some embodiments, generating the fragmented sample increases the sensitivity of detection of the one or more shorter nucleotide sequences of the fragmented sample that is characteristic of the target component by at least 3-fold. In some embodiments, generating the fragmented sample increases the sensitivity of detection of the one or more shorter nucleotide sequences of the fragmented sample that is characteristic of the target component by at least 6-fold. In some embodiments, generating the fragmented sample increases the sensitivity of detection of the one or more shorter nucleotide sequences of the fragmented sample that is characteristic of the target component by at least 3 -fold compared to the method steps performed without the fragmentation step (or multiple fragmentation steps). In some embodiments, generating the fragmented sample increases the sensitivity of detection of the one or more shorter nucleotide sequences of the fragmented sample that is characteristic of the target component by at least 6-fold compared to the method steps performed without the fragmentation step (or multiple fragmentation steps).

[0017] In some embodiments, the sample further comprises a background component. In some embodiments, the background component comprises an amplification control. In some embodiments, the amplification control comprises a nucleotide sequence of SEQ ID NO: 13. In some embodiments, returning the analysis comprises: returning a first abundance of the target component and a second abundance of the background component, and returning a relative abundance of the target component from the first abundance and the second abundance.

[0018] In some embodiments, the method is characterized by a limit of detection of less than 20 molecules representing the target component distributed across at least 30 million partitions.

[0019] Aspects of the present disclosure include methods for detecting target sites in a genome as described in the methods disclosed herein. Aspects of the present disclosure include methods for detecting parasite-specific sites within the T. cruzi genome. Aspects of the present disclosure include a multiplex PCR assay based on hydrolysis probe chemistry. In some embodiments, the method is a method for processing a sample for the detection of Chagas disease.

[0020] Aspects disclosed herein also cover methods, systems, compositions, and kits that accurately detect and characterize rare targets of a sample. In a specific example, a platform executing methods described herein can provide, within a single closed container, over 30 million partitions (i.e., over 1000 times more partitions than legacy dPCR systems) for direct and precise molecular quantification of rare target molecules with background molecules (e.g., wild type molecules) of asample, without requiring performance of Poisson error correction operations. The ability to partition a single sample with partition numbers that are orders of magnitude greater than that of legacy dPCR platforms can also contribute to achieving detection goals that overlap with those of next generation sequencing.

[0021] The inventions can be used for detection of rare molecular presence (e.g., 1 in 10,000) over background, with a large amount of input DNA This can be achieved through direct use of high-yielding DNA samples from tissue or whole blood, as well as other sample types.

[0022] In one example, the inventions covered herein can enable accurate detection and characterization of mutations in the J AK2 gene, which is important for diagnosing myeloproliferative neoplasms (MPNs). MPNs are associated with excessive blood cell production and risks of thrombosis and leukemia. Lowering the detection threshold for these rare mutations, which often remain undetected for years, could enable earlier identification, monitoring and treatment, and ultimately lead to better patient outcomes.

[0023] The inventions covered herein also have applications in detection of other rare targets. In some embodiments, the rare target component comprises a target associated with one of: Gaucher disease, Tay-Sachs disease, Krabbe disease, Alpha- 1 antitrypsin deficiency, Niemann-Pick disease type C, Pompe disease, Fabry disease, Metachromatic leukodystrophy disease, GM1 gangliosidosis, Sandhoff disease, Phenylketonuria, Maple syrup urine disease, Galactosemia, Medium-chain acyl-CoA dehydrogenase (MCAD) deficiency, Polycythemia vera, Essential thrombocythemia, Primary myelofibrosis, Factor V Leiden, Achondroplasia, Marfan syndrome, Osteogenesis imperfecta, Ehlers-Danlos syndrome, Sickle cell disease, a-thalassemia, and (3-thalassemia, In some embodiments, wherein the rare target component comprises a target associated with minimal residual disease (MRD). Additional exemplary applications of use are provided herein.

[0024] Aspects disclosed herein provide methods comprising: processing a sample comprising a rare target component, for detection of the rare target component within a set of partitions comprising at least 30 million partitions within a single closed container, wherein processing the sample comprises: (a) generating a pre-amplified sample upon pre- amplifying the rare target component with a set of pre-amplification cycles; (b) generating a purified sample upon performing a purification operation with the pre-amplified sample; (c) distributing the purified sample across the set of partitions, wherein each partition of the set of partitions comprises a portion of the purified sample and processing materials; (d) reacting the processing materials of each partition of the set of partitions with the portion of the purified sample, thereby driving the rare target component of thesample to a level of detection of a detection system configured to scan the single closed container and count a set of positive partitions of the set of partitions, wherein a positive partition of the set of positive partitions emits a signal associated with the rare target component; (e) detecting the set of positive partitions upon scanning the single closed container; and (I) returning an analysis of the rare target component.

[0025] In some embodiments, the method does not comprise (b) generating a purified sample upon performing a purification operation with the pre-amplified sample.

[0026] In some embodiments, the sample comprises a whole blood or tissue sample.

[0027] In some embodiments, the rare target component comprises a mutation in a J AK2 gene. In some embodiments, the mutation m the JAK.2 gene comprises a V617F mutation. In some embodiments, returning the analysis comprises characterizing a myeloproliferative neoplasm.

[0028] In some embodiments, the sample further comprises a background component. In some embodiments, the background component comprises a JAK2 wild type background component. In some embodiments, the background component comprises one or more housekeeping genes. In some embodiments, returning the analysis comprises: returning a first abundance of the rare target component and a second abundance of the background component, and returning a relative abundance of the rare target component from the first abundance and the second abundance.

[0029] In some embodiments, the set of pre-amplification cycles comprises at least a number of cycles such that reacting the processing materials of each partition of the set of partitions with the portion of the purified sample drives the rare target component of the sample to a low count range of the detection system configured to scan the single closed container, wherein the low count range is a range of 1 to 1000 targets. In some embodiments, the set of pre-amplification cycles comprises at least a number of cycl es such that reacting the processing materials of each partition of the set of partitions with the portion of the purified sample drives the rare target component of the sample to a level of detection of the detection system where the rare target component can be accurately detected. In some embodiments, the set of pre-amplification cycles comprises at least 12 cycles. In some embodiments, the set of pre-amplification cycles comprising at least 12 cycles improves the counts of the rare target component by at least 20-fold. In some embodiments, the set of preamplification cycles comprising at least 12 cycles improves the counts of the rare target component by at least 20-fold compared to the method steps performed without the pre-amplification step (or multiple pre-amplification steps).

[0030] In some embodiments, the method lowers the detection threshold for the rare target component. In some embodiments, the lowered detection threshold for the rare target component comprises a limit of detection (LoD) for detection of the rare target component decreased by at least 2-fold. In some embodiments, the analysis provides a sensitivity for detection of the rare target component with a limit of blank (LoB) less than 0.005 and a limit of detection (LoD) less than 0.02 in relation to variant allele frequency (VAF) percentage.

[0031] Aspects disclosed herein provide methods comprising: processing a sample comprising a target component and / or rare target component, for detection of the target component and / or rare target component within a set of partitions comprising a large number of partitions within a single closed container. In some embodiments, the plurality of partitions comprises at least 5,000,000 partitions. In some embodiments, the plurality of partitions comprises at least 10,000,000 partitions. In some embodiments, the plurality of partitions comprises at least 20,000,000 partitions. In some embodiments, the plurality of partitions comprises at least 30,000,000 partitions. In some embodiments, the plurality of partitions comprises at least 40,000,000 partitions.

[0032] In some embodiments, the methods further comprise generating the plurality of partitions by driving a solution comprising the sample (e.g., nucleic acid sample) through a membrane. In some embodiments, the plurality’ of partitions are immobilized (e.g., in a gel-like composition) within a container during distribution of the fragmented and / or purified sample across the set of partitions and reaction of the processing materials of each partition of the set of partitions with the portion of the fragmented and / or purified sample. In some embodiments, the container comprises a tube (e.g., 50 pL PCR tube). In some embodiments, detecting the set of positive partitions upon scanning the single closed container comprises scanning cross-sections of the plurality of partitions immobilized within the container. In some embodiments, reaction of the processing materials of each partition of the set of partitions with the portion of the fragmented and / or purified sample comprises heating the plurality of partitions. In some embodiments, detecting the set of positive partitions upon scanning the single closed container comprises performing imaging of a subset of the plurality of partitions. In some embodiments, the imaging is performed using an imaging system. In some embodiments, the imaging system comprises light sheet imaging.

[0033] In some embodiments, the imaging comprises collecting image data across a set of channels. In some embodiments, the set of channels comprise fluorescence channels. In some embodiments, the set of channels comprise at least 3 channels. In some embodiments, the set of channels compriseat least 4 channels. In some embodiments, the signals comprise fluorescence intensities associated with the plurality of nucleic acid molecules of the nucleic acid sample.

[0034] In some embodiments, reaction of the processing materials of each partition of the set of partitions with the portion of the fragmented and / or purified sample comprises performing an amplification reaction. In some embodiments, the amplification reaction comprises polymerase chain reaction. In some embodiments, the amplification reaction comprises isothermal amplification. In some embodiments, the isothermal amplification comprises loop-mediated isothermal amplification (LAMP). In some embodiments, the method is completed in no more than 3 hours.

[0035] Some platforms, methods, compositions, and kits for performing multiplexed analyses may involve significant infrastructure investment (e.g., m relation to microfluidic platform and detection platform aspects); however, such technologies are limited in relation to: number of targets that can be detected simultaneously; mechanism by which different targets are differentially detected (e.g., as in mechanisms involving primarily signal amplitude- based detection); ability to provide multiplexing capability with a high degree of accuracy for partitioning technologies where the partitions are arranged three-dimensionally (3D) in bulk format (e.g., in a packed configuration in three dimensions); ability to provide multiplexing for partitioning technologies involving an extremely high number of partitions (e.g., greater than 1 million partitions) for digital analyses; and other factors in the context of multidimensional digital analyses.

[0036] Accordingly, this disclosure describes embodiments, variations, and examples of systems, methods, compositions, and kits for digital detection of targets (e.g., rare targets) in a high-performance, efficient, and accurate manner, and with less complex instrumentation, without concern for Poisson error, without concern for dead volume that contributes to sample waste, and without needing to split a sample across multiple containers. In some embodiments, the method is performed within a duration of 3 hours or less. In some embodiments, each partition of the set of partitions comprises at most one target and / or rare target of the target component and / or rare target component of the sample. In some embodiments, the method is executed without performance of a Poisson error correction operation. In examples, methods described herein can be performed within a duration of 3 hours or less, wherein each partition of the set of partitions comprises at most one target and / or rare target of the target component and / or rare target component of the sample, and wherein the method is executed without performance of a Poisson error correction operation.

[0037] Aspects disclosed herein also cover multiplex assay designs for labeling and distinctly detecting various targets (e.g., different repetitive sequences, different targets) of a sample.

[0038] An aspect of the disclosure provides an approach that balances the amplification kinetics between amplicons and distinguishing such amplicons, thereby enabling the broad adoption of high order multiplex PCR panels. The disclosure provides a new paradigm in PCR amplification and multiplexed detection using UltraPCR, where an example of the embodiment(s) utilizes a centrifugation workflow to split a PCR reaction into ~34 million partitions (or greater), forming an optically clear composition of spatially separated reaction compartments in a container (e.g., PCR tube). After in-situ thermocycling, light-sheet scanning is used to produce a 3D reconstruction of the fluorescent positive compartments within the pellet. At some sample DNA concentrations, the magnitude of partitions offered by UltraPCR dictate that the vast majority (or all) of the target molecules occupy a compartment uniquely, in single-molecule format. This single molecule realm allows for isolated amplification events, thereby eliminating competition between different targets and generating unambiguous optical signals for detection. Using a 4-color optical setup, the example of the embodiment(s) incorporates 10+ different fluorescent dyes in the same UltraPCR reaction, and push multiplexing to an unprecedented level by combinatorial labeling with fluorescent dyes. Using the same 4-color optical setup, the example of the embodiment(s) incorporate a 22-target comboplex panel that can detect ail targets simultaneously at high precision. Collectively, UltraPCR pushes PCR applications beyond is currently available, enabling a new class of precision assays.

[0039] The disclosure thus covers systems and / or methods that achieve comparable or better performance of, digital PCR (dPCR) technologies, quantitative PCR (qPCR) technologies, and next generation sequencing (NGS) technologies, within a single platform.

[0040] As such, an aspect of the discl osure provides compositions, kits, methods, and systems for implementation of highly multiplexed molecular diagnostic assays involving color combinatorics, stimulus-responsive probes, tandem probes, conjugated polymer probes, and other mechanisms for increasing the number of targets that can be simultaneously detected in a digital assay. As described in more detail herein, combinations of mechanisms can provide a number of targets that can be differentially detected according to n! / [r! (n-r)! ], where n represents the number of available colors, and r represents the number of selected colors from the number of available colors. Permutations of mechanisms can provide a number of targets that can be differentially detected according to n! / [ (n-r)! ] + n, where n represents the number of available colors, and r represents the number of selected colors from the number of available colors. In examples, the numbers of targets that can be differentially tagged and detected from a single sample and within a single assay run can be greater than 10 targets, greater than 15 targets, greater than 20 targets, greater than 25 targets, greater than30 targets, greater than 35 targets, greater than 40 targets, greater than 45 targets greater than 50 targets, greater than 55 targets, greater than 60 targets, greater than 65 targets, greater than 70 targets, greater than 75 targets, greater than 80 targets, greater than 85 targets, greater than 90 targets, or greater than 100 targets, with optical detection of signals from targets.

[0041] In the context of digital multiplexed analyses, the disclosure also provides systems, methods, compositions, and kits that can achieve a high dynamic range, due to the number of partitions involved and occupancy of the partitions by targets of the sample. In examples, the systems, methods, compositions, and kits can provide a dynamic range of: over 4 orders of magnitude from a lower count capability to a higher count capability (e.g., at least 104), over 5 orders of magnitude from a lower count capability to a higher count capability (e.g., at least 105), over 6 orders of magnitude from a lower count capability to a higher count capability (e.g., at least 106), over 7 orders of magnitude from a lower count capability to a higher count capability (e.g., at least 107), or greater, for sample volumes described herein. In examples, the systems, methods, compositions, and kits can achieve quantification of targets over a 4-log dynamic range, over a 5-log dynamic range, over a 6-log dynamic range, over a 7-log dynamic range, or greater, for sample volumes described herein. In some embodiments, the systems, methods, compositions, and kits provide at least a 6-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component. In some embodiments, the systems, methods, compositions, and kits provide at least a 6-log dynamic range that enables the simultaneous quantification of a rare target component and a background component.

[0042] For partitions arranged in bulk (e.g., in close-packed format, in the form of disperse phases of an emulsion) within a closed container, the systems, methods, compositions, and kits described herein can provide discernable signals from individual partitions, with readout performed using multiple color channels (e.g., 2 color channels, 3 color channels, 4 color channels, 5 color channels, 6 color channels, 7 color channels, etc.) corresponding to light sources and optics involved in detection, with suitable signal-to-noise (SNR) characteristics in relation to background fluorescence.

[0043] For multiplexed analyses, methods described herein involve detection of signals from a large number of partitions, where detected signals correspond to a set of color combinatorics paired with targets of a set of targets potentially represented in the sample and contained within partitions of the set of partitions, and wherein the set of targets has a total number greater than the number of color channels used to detect colors corresponding to the set of color combinatorics. In examples, the set of color combinatorics involves combinations of up to 3 colors, up to 4 colors, up to 5 colors, up to 6colors, up to 7 colors, or greater (from each of the set of partitions), where each combination of colors has a corresponding target associated with the respective combination.

[0044] In one embodiment, the set of partitions involves disperse phases of an emulsion within a closed container, and the set of color combinatorics involves combinations of up to 3 colors, up to 4 colors, up to 5 colors, up to 6 colors, up to 7 colors, etc. detectable from each of the set of partitions. Additionally or alternatively, multiplexing involving stimulus-responsive materials can expand the number of targets that can be differentially tagged and detected by a factor equal to the number of states through which probes used to tag targets can transition. Additionally or alternatively, multiplexing involving materials that exhibit Foerster resonance energy transfer (FRE T) behavior can expand the number of targets that can be differentially tagged and detected by a factor equal to the number of FRET capable probes used.

[0045] The disclosure also provides compositions that produce significantly improved signal-to-noise (SNR) values with reduced background, in relation to detection techniques described herein (e.g., based on light sheet imaging, etc.) for partitions arranged in bulk in 3D. In examples, target signals can be at least 102greater than background noise signals, 103greater than background noise signals, 104greater than background noise signals, 105greater than background noise signals, 106greater than background noise signals, 107greater than background noise signals, or better.Background noise can be attributed to fluorescence from adjacent partitions and adjacent planes of the set of planes of partitions in the context of emulsion digital PCR, or attributed to other sources with closely-positioned partitions.

[0046] In examples associated with reaction materials described herein and used for partition-based digital PCR, determining the target signal value can include: for each plane of a set of planes of partitions under interrogation (e.g., by light sheet detection, by another method of detection, etc.): determining a categorization based upon a profile of positive partitions represented in a respective plane, determining a target signal distribution and a noise signal distribution specific to the profile, and determining a target signal intensity and a noise signal intensity for the respective plane. Here, the target signal value can be an average value (or other representative value) of the target signal intensities determined from the set of planes, and the background noise signal value can be an average value (or other representative value) of the noise signal intensities determined from the set of planes.

[0047] The disclosure also provides oligonucleotide compositions, kits, and designs for multiplexed assays (e.g., locked nucleic acid (LNA) assays, KASP assays, Taqman assays, etc.). Such improvedoligonucleotides improve sample processing, with respect to primer cleanup / reinoval, reduction of background, implementation of compatible forward and reverse primers for direct multiplexed assays (e.g., PCR), implementation of checks for complementarity of amplicons to non-self probes (i.e., in both sense and antisense strands), implementation of checks for complementarity of primers to probes (i.e., in both sense and antisense strands), generation of positive and negative controls for a clinical workflow, establishment of limits of detection (LoDs) and other metrics for NIPT ultraPCR assays, and other improvements.

[0048] Examples of partition generation methods can include generating an extremely high number of droplets (e.g., greater than 5 million droplets, greater than 6 million droplets, greater than 7 million droplets, greater than 8 million droplets, greater than 9 million droplets, greater than 10 million droplets, greater than 15 million droplets, greater than 20 million droplets, greater than 25 million droplets, greater than 30 million droplets, greater than 40 million droplets, greater than 50 million droplets, greater than 100 million droplets, etc.) within a collecting container having a volumetric capacity (e.g., less than 50 microliters, from 50-100 microliters and greater, etc.), where droplets have a characteristic dimension (e.g., from 1-50 micrometers, from 10-50 micrometers, etc.) that is relevant for digital analyses, target detection, individual molecule partitioning, or other applications. In embodiments, droplets that form after leaving the side of the membrane facing the liquid layer(s) in the collecting container then pass through the liquid layer(s), in order to form a gel material comprising partitions (e.g., a partition network, a permeable partition network) where the partitions are stabilized in position in the collecting container. The gel material can thus be rescanned for each of the set of channels of interrogation, while the partitions retain their relative positions within the closed collecting container during each scanning run.

[0049] In relation to occupancy, embodiments, variations, and examples of partitioning may be conducted in a manner such that each partition has one or zero molecules (e.g., one or zero target molecules), such that the partitions may be characterized as having low occupancy (e.g,, less than 15% occupancy of partitions by individual molecules, less than 14% occupancy of partitions by individual molecules, less than 13% occupancy of partitions by individual molecules, less than 12% occupancy of partitions by individual molecules, less than 11% occupancy of partitions by individual molecules, less than 10% occupancy of partitions by individual molecules, less than 9% occupancy of partitions by individual molecules, less than 8% occupancy of partitions by individual molecules, less than 7% occupancy of partitions by individual molecules, less than 6% occupancy of partitionsby individual molecules, less than 5% occupancy of partitions by individual molecules, less than 4% occupancy of partitions by individual molecules, etc. ).

[0050] Compositions, kits, methods, and systems described herein can further involve use of a single primer with tandem adapters or multiple primers used to tag targets with probes. Multiplexed primers configured to flank target-specific probes that encode for different targets can be used. Multiplexed primer compositions can be configured for 20-plex amplification of loci of interest for each a set of targets being analyzed, 30-plex amplification of loci of interest for each a set of targets being analyzed, 40-plex amplification of loci of interest for each a set of targets being analyzed, 50-plex amplification of loci of interest for each a set of targets being analyzed, 60-plex amplification of loci of interest for each a set of targets being analyzed, 70-plex amplification of loci of interest for each a set of targets being analyzed, 80-plex amplification of loci of interest for each a set of targets being analyzed, 90-plex amplification of loci of interest for each a set of targets being analyzed, 100-plex amplification of loci of interest for each a set of targets being analyzed, or greater.

[0051] Relatedly, an aspect of the disclosure provides embodiments, variations, and examples of devices and methods for rapidly generating partitions (e.g., droplets from a sample fluid, droplets of an emulsion) and distributing nucleic acid material (e g., multiplexed target detection) across partitions, where, the device includes: a first substrate defining a reservoir comprising a reservoir inlet and a reservoir outlet; a membrane coupled to the reservoir outlet and comprising a distribution of holes: and a supporting body comprising an opening configured to retain a collecting container in alignment with the reservoir outlet. During operation, the first substrate can be coupled with the supporting body and enclose the collecting container, with the reservoir outlet aligned with, seated within the collecting container, or a combination thereof. During operation, the reservoir can contain a sample fluid (e.g., a mixture of nucleic acids of the sample and materials for an amplification reaction), where application of a force to the device or sample fluid generates a plurality of droplets at an extremely high rate (e.g., of at least 200,000 droplets / mmute, of at least 300,000 droplets / minute, of at least 400,000 droplets / minute, of at least 500,000 droplets / minute, of at least 600,000 droplets / minute, of at least 700,000 droplets / minute, of at least 800,000 droplets / minute, of at least 900,000 droplets / minute, of at least 1 million droplets / minute, of at least 2 million droplets / minute, of at least 3 million droplets / minute, of at least 4 million droplets / minute, of at least 5 million droplets / minute, of at least 6 million droplets per minute, etc.), where the droplets then pass through the fluid layer(s) and form partitions (e.g., a partition network) may be stabilized inposition (e.g., in a close-packed format, in equilibrium stationary positions) within the collecting container.

[0052] An aspect of the disclosure provides embodiments, variations, and examples of a method for rapidly generating partitions (e.g., droplets from a sample fluid, droplets of an emulsion) within a collecting container at an extremely high rate, each of the plurality of droplets including an aqueous mixture for a digital analysis, wherein upon generation, the plurality of droplets pass through the fluid layer(s) and form partitions (e.g., a partition network) that are stabilized in position (e.g., in a close-packed format, at equilibrium stationary positions, etc.) within a continuous phase (e.g., as an emulsion having a bulk morphology defined by the collecting container). In aspects, partition generation can be executed by driving the sample fluid through a distribution of holes of a membrane, where the applied force can be one or more of centrifugal (e.g., under centrifugal force), associated with applied pressure, magnetic, or otherwise physically applied.

[0053] In relation to a single-tube workflow in which the collecting container remains closed (e.g., the collecting container has no outlet, there is no flow out of the collecting container, to avoid sample contamination), method(s) can further include transmitting heat to and from the plurality of droplets within the closed collecting container according to an assay protocol. In relation to generation of stabilized partitions having suitable clarity (e.g., with or without refractive index matching), method(s) can further include transmission of signals from individual stabilized partitions from within the closed collecting container, for readout (e.g., by an optical detection platform, by another suitable detection platform).

[0054] Where method(s) include transmitting heat to and from the plurality of droplets, within the closed container, the droplets may be stable across a wide range of temperatures (e.g., 1 °C through 95 °C, greater than 95 °C, less than 1 °C) relevant to various digital analyses and other bioassays, where the droplets remain consistent in morphology and remain unmerged with adjacent droplets.

[0055] The disclosure generally provides mechanisms for efficient capture, distribution, and labeling of target material (e.g., DNA, RNA, miRNA, proteins, small molecules, single analytes, multianalytes, etc.) in order to enable genomic, proteomic, other multi-omic characterization of materials, or a combination thereof, in parallel and in a multiplexed manner, for various applications.

[0056] In examples, the approach discussed is designed around a simple workflow to enable deployment to local and decentralized laboratories. First, samples may be carried end-to-end in the same PCRtube for user convenience and to minimize sample contamination. Second, ultrapartitioning and PCR amplification can be performed using laboratory equipment such as a swingdebucket centrifuge and thermal cycler, lowering the infrastructure cost for adoption of high-performing analysis techniques. However, compositions and kits of the disclosure can also be utilized m coordination with various technologies for isolating material in single-molecule format (e.g., by use of wells, by use of droplets, by use of other partitioning elements, etc.).

[0057] Another aspect of the present disclosure provides a non-transitory computer readable medium comprising machine executable code that, upon execution by one or more computer processors, implements any of the methods above or elsewhere herein.

[0058] The disclosure provides compositions, kits, methods, and systems for multiplexed detection of targets that can provide value in research or other non-clinical settings, with or without evaluation and processing of live human or mammalian biological material, and without the immediate purpose of obtaining a diagnostic result of a disease or health condition.

[0059] Another aspect of the present disclosure provides a system comprising one or more computer processors and computer memory coupled thereto. The computer memory comprises machine executable code that, upon execution by the one or more computer processors, implements any of the methods above or elsewhere herein.

[0060] In some embodiments, the set of partitions comprises positionally-stabilized disperse phases of an emulsion within a closed container. In some embodiments, the set of label combinatorics involves combinations of a set of labels detectable from each of the set of partitions. In some embodiments, the set of labels comprises a label associated with a class I dye. In some embodiments, the set of labels comprises a label associated with a class II dye. In some embodiments, the set of labels comprises a label associated with a class III dye. In some embodiments, the set of labels comprises a photobl eachable dye. In some embodiments, the set of partitions is stabilized in position within a container, the method further comprising moving the container during performance of 3D scanning of the set of partitions.

[0061] In some embodiments, 3D scanning of the set of partitions comprises scanning the container sequentially, for a number of scanning runs corresponding to the set of optical channels. In some embodiments, the set of optical channels comprises greater than 10 optical channels.

[0062] In some embodiments of the systems, methods, compositions, and kits disclosed herein, the set of processing materials comprises, for a target of the set of targets: a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the target, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising afirst fluorophore configured to transmit a first target signal if the target region is amplified. In some embodiments, the set of processing materials comprises, for a first target and a second target of the set of targets: a primer set comprising: at least one primer configured to tag the first target with a first probe having a first fluorophore and the second target with a second probe having a second fluorophore.

[0063] In some embodiments, the processing materials comprise, for a rare target component, a primer set comprising: a common primer and a set of target- specific primers comprising a targetspecific primer configured to interact with a target region of the rare target component, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified. In some embodiments, the processing materials further comprise, for a background component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the background component, and a second fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the second fluorophore-labeled oligonucleotide comprising a second fluorophore configured to transmit a second target signal if the target region is amplified.

[0064] In some embodiments, the processing materials comprise, for a rare target component, a primer set comprising: a common primer and a set of target- specific primers comprising a targetspecific primer configured to interact with a target region of the rare target component, the targetspecific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. In some embodiments, the processing materials further comprise, for a background component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the background component, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified.

[0065] In some embodiments, the processing materials comprise, for a rare target component and a background component, a primer set comprising at least one primer configured to tag the rare target component with a first probe having a first fluorophore and the background component with a second probe having a second fluorophore.

[0066] In variations wherein a target component comprises one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, the processing materials can comprise, for a first shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the first shorter nucleotide sequence, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified. In some embodiments, the processing materials further comprise, for a second shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the second shorter nucleotide sequence, and a second fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the second fluorophore-labeled oligonucleotide comprising a second fluorophore configured to transmit a second target signal if the target region is amplified.

[0067] In some embodiments, the processing materials comprise, for a first shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the first shorter nucleotide sequence, the target- specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. In some embodiments, the processing materials further comprise, for a second shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the second shorter nucleotide sequence, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified.

[0068] In some embodiments, the processing materials comprise, for a first shorter nucleotide sequence and a second shorter nucleotide sequence of the at least two shorter nucleotide sequences that are repetitive sequences characteristic of the target component, a primer set comprising at least one primer configured to tag the first shorter nucleotide sequence with a first probe having a first fluorophore and the second shorter nucleotide sequence with a second probe having a second fluorophore.

[0069] In some embodiments, the sample further comprises a background component, and the processing materials further comprise a primer set comprising at least one primer configured to tag the background component with a third probe having a third fluorophore. In some embodiments, the background component comprises an amplification control comprising a nucleotide sequence of SEQ ID NO: 13.

[0070] In some embodiments of the systems, methods, compositions, and kits disclosed herein, the first fluorophore is a photo- bleachable fluorophore, and wherein detecting signals from the set of partitions comprises scanning the set of partitions with a first wavelength range of light and a second wavelength range of light configured to bleach the first fluorophore, the method further comprising: detecting signals from the set of partitions in a first phase of analysis upon scanning the set of partitions with the first wavelength range of light, and detecting signals from the set of partitions in a second phase of analysis upon scanning the set of partitions and bleaching the first fluorophore with the second wavelength range of light, thereby enabling differential detection of the first target and the second target.

[0071] In some embodiments, detecting a target (e.g,, rare target) of the set of targets comprises assembling an optical signature from a partition containing the target, from positive and negative signals aggregated from scanning the partition with each of the set of optical channels. In some embodiments, no partitions of the set of partitions contains two or more targets, and wherein the method omits deconvolution of partitions ambiguously containing multiple targets.

[0072] In another aspect, the present disclosure provides a method comprising: performing a digital multiplexed analysis of a sample distributed across a set of partitions stabilized in position within a closed container, wherein each partition of the set of partitions comprises less than two targets of the sample, and wherein the digital multiplexed analysis can simultaneously and differentially detect at least 20 different targets from the sample.

[0073] In some embodiments, performing the digital multiplexed analysis comprises: reacting the sample with a set of processing materials within the set of partitions, wherein each partition of theset of partitions has less than two targets, and detecting signals from the set of partitions upon scanning the set of partitions sequentially with a set of optical channels, wherein said signals correspond to a set of label combinatorics paired with targets of a set of targets potentially-represented in the sample and contained within partitions of the set of partitions. In some embodiments, the set of partitions comprises greater than 30 million droplets stabilized in position in an emulsion, and wherein scanning comprises performing a light sheet imaging operation. In some embodiments, the set of targets has a total number greater than a number of the set of optical channels used to detect signatures corresponding to the set of label combinatorics, and wherein the set of optical channels comprises at least 10 channels. In some embodiments, each of the set of optical channels comprises a respective emission and excitation configuration. In some embodiments, the set of partitions comprises greater than 500,000 partitions and wherein the set of partitions is characterized by less than 15% occupancy (e.g., much less than 15% for rare target detection) of partitions by said targets.

[0074] In some embodiments, wherein the set of processing materials comprises a set of nonhydrolysis probes, the method further comprises tagging the set of targets with a set of permutations of the set of non-hydrolysis probes, wherein detecting signals from the set of partitions comprises detecting signals corresponding to the set of permutations for differential detection of the set of targets.

[0075] As such, the methods and systems described herein can be applied to achieve highly-sensitive pathogen screening improvements, which are crucial for early detection and treatment of infected individuals. Current assays often lack the sensitivity to identify active infections when target molecules are present in minute quantities (e.g., < 0.1 pathogen equivalents per mL of blood), especially when the target molecules are present in a sample having high overall nucleic acid input.

[0076] In one specific example, a challenge in early detection of Chagas disease lies in the extremely low abundance of T. cruzi genomes in blood of a patient. Even with substantial genomic DNA isolated from whole blood, the prevalence is so low that as many as 400 qPCR reactions may be needed to identify just one positive reaction for T. cruzi. This makes it exceedingly difficult to detect using conventional DNA detection methods. Therefore, developing more sensitive screening techniques is essential for timely diagnosis and intervention in Chagas disease cases. The inventions covered herein can enable accurate detection and characterization of repetitive sequences associated with T. cruzi infection, using a multiplexed assay designed to target multiple repetitive T. cruzi sequences. Fragmentation of nucleic acid sequences of the sample enables focus on such repetitivesequences, thus overcoming challenges associated with reduced sensitivity of detection, where detection of signature repetitive sequences is more sensitive than detection of entire T. cruzi genomes of a sample. Exemplary methods described herein cover one or more of a combination of 3 ways to boost assay sensitivity for rare target detection (e.g., detection of T. cruzi), while minimizing the number of reactions (and thus cost) for detecting Chagas disease. The specific example employed a 3-plex PCR assay targeting two T. cruzi repetitive sequence elements and an internal amplification control (IAC), as shown in FIG. 2A and FIG. 2D. This multiplex approach enhances detection sensitivity and reliability. By focusing on two distinct highly abundant elements within the pathogen genomes (kDNA and microsatellite DNA), the likelihood of detecting T. cruzi increases, even at extremely low concentrations.

[0077] However, the methods can be applied to detection of other subsequences (e.g., upon fragmentation of nucleic acids of a sample and distribution across a large number of partitions), in order to increase assay sensitivity. As such, the methods disclosed herein can be applied to detection of active and / or latent infectious diseases attributed to agents that are low in abundance, where detection can be performed with high sensitivity. Additional exemplary applications of use are provided herein.

[0078] Additional aspects and advantages of the present disclosure will become readily apparent to those skilled in this art from the following detailed description, wherein only illustrative embodiments of the present disclosure are shown and described herein. As will be realized, the present disclosure is capable of other and different embodiments, and its several details are capable of modifications in various obvious respects, all without departing from the disclosure. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.INCORPORATION BY REFERENCE

[0079] All publications, patents, and patent applications mentioned in this specification, including U. S. Provisional Application No. 63 / 714,848, 63 / 817,086, and 63 / 714,850, are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. To the extent publications and patents or patent applications incorporated by reference contradict the disclosure contained in the specification, the specification is intended to supersede and / or take precedence over any such contradictory material.BRIEF DESCRIPTION OF THE DRAWINGS

[0080] The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained byreference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings (also “figure” and “FIG.” herein), of which:

[0081] FIG. 1A depicts a flowchart of an embodiment of a method for detection and analysis of a target component of a high-input nucleic acid sample.

[0082] FIG. IB depicts a flowchart of an embodiment of a method for detection and analysis of a rare target component.

[0083] FIG. 1C depicts a flowchart of a variation of a method for detection and analysis of a target component and / or rare target component.

[0084] FIG. 2A depicts a specific example of a w'orkflow for generating a fragmented sample (e.g., from whole blood of a subject). In the specific example, 3 micrograms of input DNA was loaded into each PCR reaction in order to increase target abundance per reaction for improved assay sensitivity.

[0085] FIG. 2B depicts schematics showing how fragmentation improves assay sensitivity' with respect to detection of shorter sequences (e.g., repetitive sequences that can be used to identify a target).

[0086] FIG. 2C depicts a schematic of components implemented in an embodiment of a method for detection and analysis of a rare target component.

[0087] FIG. 2D depicts an exemplary assay design for a 3-plex multiplex assay targeting two repetitive parasite regions associated with T. cruzi, kDNA and microsatellite, and a synthetic internal amplification control (IAC). The 3-plex assay targeted a segment of the parasite kinetoplast (kDNA) that exhibits a highly repetitive minicircle structure, and a segment derived from a highly repetitive microsatellite of the parasite genome.

[0088] FIG. 2E depicts results showing that mechanical fragmentation of sample nucleic acids increased microsatellite molecule detection. Covaris treatment of macaque DNA (typical host model system) spiked with parasite DNA. 125 ng input was used. For kDN / X, counts ranged from 7,808 to 7,790, with 1.1% and 2.1% CV, respectively (n === 2). Bars indicate molecules per 50 pL detected for (A) kDNA, (B) Microsatellite, (C) Internal Amplification Control (IAC) (mean values ± standard error (SE), n === 2). 125 ng of Covans-sheared DNA was input per reaction.

[0089] FIG.2F depicts results showing that enzymatic digestion increased kDNA and microsatellite molecule detection. A custom restriction enzyme (RE) digest panel targeting regions flanking the kDNA and microsatellite PCR amplicons was used. RE digestion was performed in native mastermix with DNA template, followed by single molecule immobilization, amplification, and detection as per the manufacturer’s protocol. This method proved more effective, boosting target counts by approximately 3-fold for kDNA and 6.5-fold for microsatellite. Given the naturally higher copy number of kDNA per parasite and the overall improved performance, the RE approach is a suitable approach for Chagas detection assay. This choice significantly approves the ability to detect T. cruzi at low concentrations, potentially improving early diagnosis of Chagas disease. Bars in FIG.2F indicate molecules per 50 pL detected for (A) kDNA, (B) Microsatellite, (C) Internal Amplification Control (IAC) by UltraPCR (mean values ± standard error (SE), n = 2). 500 ng of restriction-digested DNA input per reaction.

[0090] FIG.2G depicts results of analytical titration of T. cruzi parasite DNA with high background human DNA. Bars indicate molecules per 50 pL detected for (A) kDNA, (B) Microsatellite, (C) IAC (mean values ± standard error (SE), n = 2 or 4). 3000 ng of restriction-digested human DNA (GM12878) was input per reaction. Parasite stock DNA was 2.6xl0e3 parasites / pL.

[0091] FIG.2H depicts results of the input titration for Chagas detection. Lambda DNA spiked with parasite DNA and synthetic IAC used as background. Reactions were prepared, centrifuged, amplified, and imaged. Counts per 50pL were then obtained.

[0092] FIGS.3A and 3B depict comparison schematics of a no pre-amplifi cation workflow (FIG.3A) and a pre-amplification workflow (FIG. 3B). The no pre- mplification workflow includes steps for directly quantifying rare targets (e.g., JAK2 mutations) of a sample. The pre-amplification workflow includes steps for pre-amplifying rare targets with 12-cycles of pre-amplification using JAK2 Forward and Reverse primers using master mix. The pre-amplification workflow shown in FIG. 3B includes a clean up step, followed by a one-step dilution, and then quantification of signalpositive partitions. Due to the exemplary platform’s capacity for single molecule isolation within 30+ million partitions, each amplified sample can be loaded m a single reaction, obviating the need to split the sample into multiple reactions to avoid over-saturation.

[0093] FIG.3C depicts a schematic of exemplary components implemented in an example of a method for detection and analysis of a rare target component (e.g., J / XK2 mutation, with a wild type background component). A multiplex PCR assay for the JAK2 V617F gene mutation is shown in FIG. 3C. JAK2 mutations are crucial in diagnosing myeloproliferative neoplasms (MPNs); disorderscharacterized by excessive blood cell production and associated risks of thrombosis and leukemia. The assay employs a probe-based (e.g., TaqMan-based) approach with two color detection. A F1EX-labeled probe targets the wild-type JAK2 sequence, while a F / XM-labeled probe specifically detects the V617F mutation. These probes flank the V617F mutation site, allowing for simultaneous detection of both wild-type and mutant alleles.

[0094] FIG.3D depicts average rare target component molecule counts for the V617F and wild type (WT) targets as well as their standard errors. The V617F counts are very low for samples D3 and D4 in the no pre-amplification condition leading to higher counting variance, reflected by the larger error bars. Samples that underwent pre-amplification show higher counts in both targets, while maintaining a low false positives rate as seen in the WT sample. In addition, lower counting variance for the V617F target is observed in pre-amplification samples.

[0095] FIG.3E depicts results of an analytical characterization of the JAK2 V617F assay across a titration of VAF values (e.g., percentages). The grey line represents the expected decrease in VAF across the samples. Each data point reflects the average VAF the calculated from single molecule counts and the standard errors. With no pre-amplification, VAF for sample D4 fell below the LoD. However, with pre-amplification, all samples across the dilution series were above the LoD. All samples had replicates of 2, 4, or 8. Thus, the pre-amplification workflow significantly lowers the detection threshold.

[0096] FIG.4 depicts a schematic of an embodiment of a system for partitioning samples.

[0097] FIG. 5 depicts schematics of representative directions along which characterization of partitions as positive partitions and / or negative partitions can be analyzed.

[0098] FIGS.6A-6D depict control and / or training data images of representative positive partitions and negative partitions, where the images depict two-dimensional cross sections from single partitions.

[0099] FIG. 7 depicts an example of partition feature characterization models used to identify signal-positive and / or signal-negative partitions of a sample.

[0100] FIG. 7B depicts an example of classification architecture and training used to generate counts of sample targets.

[0101] FIG. 8 illustrates a computer system that is programmed or otherwise configured to implement methods provided herein.

[0102] FIG.9 illustrates the principle of Universal Multiplexing chemistry. ( / X) During initial cycles of PGR, the UM primer (a forward primer with UM adapter) binds to the template and extends. (B)In subsequent PCJR cycles, the non-UM primer (a reverse primer, unmodified) binds to the sense forward template (now with UM adapter) and extends to create an UM probe complementary sequence. (C) The detection of the target amplicon occurs via hybridization of the UM probe to the target amplicon.

[0103] FIG. 10 depicts results of a comparison between counts per target obtained from a 4-plex UM assay versus a 4-plex I IP assay targeting the same genes. Counts averaged across four replicates per condition are shown. Standard deviations were used for the error bars. The difference between HI’ and UM in each assay was less than 2 % in all targets.

[0104] FIG. 11 depicts results of a comparison of 1-plex, 2-plex, 3-plex, and 4-plex designs for Countable PCR assays targeting four different human genes. The counts for all four targets remained consistent, regardless of whether other targets were present or not. Counts averaged across three replicates per condition are shown. The error bars represent standard deviations. The difference between 1-plex and 4-plex was -0.13%, 0.35%, -0.84% and 1.03% for RPP30, JAK2, RAD5I and MET, respectively.

[0105] FIG. 12 illustrates the dynamic range of UM with 4-plex assay (N = 8). Four different targets were quantified using UM probes across dilution series from 0 to 1,000,000 of template. The error bars represent standard deviations. Even in multiplexed conditions, UM showed a linear increase in counts per target across a 6-log range.

[0106] FIG. 13 depicts results of probe permutation in high / medium / low expression targets (N = 4). Three targets with varying expression levels were quantified using different combinations of UM probes as shown in the table above. The error bars represent standard deviations. The assayperformance remained consistent regardless of the UM adapter choice or expression level. %CV was calculated across samples with the same targets, regardless of probe combinations.

[0107] FIG. 14 depicts results of a combination of a 4-plex assay utilizing HP chemistry for two targets and utilizing UM (N = 4). The error bars represent standard deviations. Each target can be quantified without interference, either by HP or UM chemistry.DETAILED DESCRIPTION

[0108] While various embodiments of the invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions may occur to those skilled in the art withoutdeparting from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed.

[0109] Whenever the term “at least,” “greater than,” or “greater than or equal to” precedes the first numerical value in a series of two or more numerical values, the term “at least,” “greater than” or “greater than or equal to” applies to each of the numerical values in that series of numerical values. For example, greater than or equal to 1, 2, or 3 is equivalent to greater than or equal to 1, greater than or equal to 2, or greater than or equal to 3.

[0110] Whenever the term “no more than,” “less than,” or “less than or equal to” precedes the first numerical value in a series of two or more numerical values, the term “no more than,” “less than,” or “less than or equal to” applies to each of the numerical values in that series of numerical values. For example, less than or equal to 3, 2, or 1 is equivalent to less than or equal to 3, less than or equal to 2, or less than or equal to 1.1. General Overview

[0111] The method(s) described herein can confer several benefits over other systems, methods, compositions, and kits.

[0112] In particular, the method(s) enable accurate detection and characterization of target components and / or rare target components of a sample, including a high-input nucleic acid sample, with workflow innovations that involve fragmentation and / or pre-amplification of target molecules, including long and / or rare target molecules, and distribution of fragmented and / or pre-amplified target molecules across over 30 million partitions, such that each partition contains at most 1 processed and / or pre-amplified target molecule and / or rare target molecule. In embodiments, the method(s) enable accurate detection and characterization of target components of a high-input nucleic acid sample, with workflow innovations that involve fragmentation of target molecules, including long target molecules, and distribution of fragmented target molecules across over 30 million partitions, such that each partition contains at most 1 processed target molecule. In embodiments, the method(s) enable accurate detection and characterization of rare target components of a sample, with workflow innovations that involve pre-amplification of rare target molecules and distribution of pre-amplified target molecules across over 30 million partitions, such that each partition contains at most I pre-amplified rare target molecule. In embodiments, each partition of the set of partitions includes at most one target of the target component of the sample. Inembodiments, each partition of the set of partitions includes at most one rare target of the rare target component of the sample.

[0113] In particular, the method(s) can also enable detection and digital quantitation of a set of targets having a number much greater than the number of channels (e.g., color channels, fluorescence detection channels) available for detection. Multiplexed detection involving a greater number of targets than available color channels for detection is based upon one or more of: color combinatorics, stimulus-responsive probes, tandem probes, conjugated polymer probes, and other mechanisms for increasing the number of targets that can be simultaneously detected in a digital assay. Such functionality is attributed to operation in a regime involving low occupancy of a large number of partitions, such that there is an extremely low probability of overlap between target template molecules within individual partitions. Large partition numbers contribute to significantly low percentages of doublets (e.g., single partitions occupied by two targets), triplets (e.g., single partitions occupied by three targets), or other forms of multi-plets (single partitions occupied by multiple targets). As such, signals from different amplified target templates distributed across individual partitions can be differentially detected and analyzed in relation to performance of digital assays.

[0114] In the context of digital multiplexed analyses, the disclosure also provides systems, methods, compositions, and kits that can achieve a high dynamic range, due to the number of partitions involved and occupancy of the partitions by targets of the sample. In examples, the systems, methods, compositions, and kits can provide a dynamic range of: over 4 orders of magnitude from a lower count capability to a higher count capability (e.g., at least IO4), over 5 orders of magnitude from a lower count capability' to a higher count capability' (e.g., at least 105), over 6 orders of magnitude from a lower count capability to a higher count capability (e.g., at least 106), over 7 orders of magnitude from a lower count capability to a higher count capability (e.g,, at least 107), or greater, for sample volumes described herein. In examples, the systems, methods, compositions, and kits can achieve quantification of targets over a 4-log dynamic range, over a 5-log dynamic range, over a 6-log dynamic range, over a 7-log dynamic range, over a 8-log dynamic range, over a 9-log dynamic range, over a 10-log dynamic range, or greater, for sample volumes described herein. In some embodiments, the systems, methods, compositions, and kits provide at least a 2-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component. In some embodiments, the systems, methods, compositions, and kits provide at least a 2-log dynamic range that enables the simultaneousquantification of a rare target component and a background component. In some embodiments, the systems, methods, compositions, and kits provide at least a 3-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component. In some embodiments, the systems, methods, compositions, and kits provide at least a 3-log dynamic range that enables the simultaneous quantification of a rare target component and a background component. In some embodiments, the systems, methods, compositions, and kits provide at least a 4-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component. In some embodiments, the systems, methods, compositions, and kits provide at least a 4-log dynamic range that enables the simultaneous quantification of a rare target component and a background component. In some embodiments, the systems, methods, compositions, and kits provide at least a 5-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component. In some embodiments, the systems, methods, compositions, and kits provide at least a 5-log dynamic range that enables the simultaneous quantification of a rare target component and a background component.

[0115] In some embodiments, the systems, methods, compositions, and kits provide at least a 6-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component. In some embodiments, the systems, methods, compositions, and kits provide at least a 6-log dynamic range that enables the simultaneous quantification of a rare target component and a background component.

[0116] For partitions arranged in bulk (e.g., in close-packed format, in the form of an emulsion) within a closed container, the systems, methods, compositions, and kits described herein can provide discernable signals from individual partitions, with readout performed using multiple color channels (e.g,, 2 color channels, 3 color channels, 4 color channels, 5 color channels, 6 color channels, 7 color channels, 8 color channels, etc.), with suitable signal-to-noise (SNR) characteristics in relation to background fluorescence.

[0117] For multiplexed analyses, methods described herein involve detection of signals from a large number of partitions, where detected signals correspond to a set of color combinatorics paired with targets of a set of targets potentially represented in the sample and contained within partitions of the set of partitions, and wherein the set of targets has a total number greater than the number of color channels used to detect colors corresponding to the set of color combinatorics. In examples, the setof color combinatorics involves combinations of up to 3 colors, up to 4 colors, up to 5 colors, up to 6 colors, up to 7 colors, or greater, where each combination of colors has a corresponding target associated with the respective combination.

[0118] In one embodiment, the set of partitions involves positionally stabilized disperse phases of an emulsion within a closed container, and the set of color combinatorics involves combinations of up to 3 colors, up to 4 colors, up to 5 colors, up to 6 colors, up to 7 colors, etc. detectable from each of the set of partitions. Additionally or alternatively, multiplexing involving stimulus-responsive materials can expand the number of targets that can be differentially tagged and detected by a factor equal to the number of states through which probes used to tag targets can transition. Additionally or alternatively, multiplexing involving materials that exhibit Foerster resonance energy transfer (FRET) behavior can expand the number of targets that can be differentially tagged and detected by a factor equal to the number of FRET capable probes used.

[0119] In variations, processing materials of the method(s) described herein can include: a primer set comprising a common primer and a target- specific primer (or set of target-specific primers) configured to interact with the target region, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. The processing materials can further include and a probe additive reagent configured to reduce background noise (e.g., from adjacent partitions and planes of partitions within the container, as described herein). The common primer can be a forward primer or a reverse primer. The target-specific primer can be a forward primer or a reverse primer. In specific examples, processing materials can include Taqman® probes (e.g,, dual-labeled hydrolysis probes). In specific examples, processing materials can include molecular beacons or similar probe structures (e.g., probes with hairpin structures), where such probes may be quenched by quenchers at regions opposite respective fluorophores when the probe is not bound to a target or in an extended configuration,

[0120] In more detail, the methods confer the benefit of enabling performance of ultra-high multiplexed target detection using a partitioning system and methods of sample processing configured to provide a high number of partitions (e.g., more than 100,000 partitions, more than 200,000 partitions, more than 500,000 partitions, more than I million partitions, more than 10 million partitions, more than 20 million partitions, more than 30 million partitions, more than 50 million partitions, more than 100 million partitions, etc.) with low-occupancy (e.g., less than 10%occupancy, less than 8% occupancy, less than 5% occupancy, etc.) of partitions by targets. In particular, use of a low-occupancy platform involving high numbers of partitions provides a regime where the probability of encountering a falsely-labeled multi-color partition associated with one of a set of targets is very low. Such a regime allows a high number of targets to be uniquely labeled by at least one color at low error.

[0121] In various applications, the methods provide functionality for assaying samples for a panel of SNPs, CNVs, insertions, deletions, targets associated with other loci of interest, other suitable components, or a combination thereof. Evaluation of samples is performed in a multiplexed manner / in parallel, instead of detecting targets one-by-one in separate reactions.

[0122] In various applications, the method(s) can evaluate samples for a panel of SNPs (e.g., 50 common SNPs, less than 50 common SNPs, greater than 50 common SNPs). In some cases, the methods may not comprise sequencing of an individual first to determine the target panel. Common SNPs may be those that have allele frequency of 1% or more (e.g., from 30-60% allele frequency) in the population.

[0123] In variations, the methods can be used to detect low abundance infectious disease agents from a sample. In one specific use case, the low abundance of T. cnizi genomes in samples (e.g., whole blood samples) can make detection using unfragmented gDNA extremely challenging. To enhance assay sensitivity, the specific use case method and system focused on detection of repetitive sequences that are characteristic of T. cruzi, specifically the kDNA and microsatellite regions within the parasite genome, which occur hundreds of times per genome. The specific use case aimed to isolate individual repeat elements across a large number of single partitions. This strategy enabled detection based on the more abundant repetitive sequence themselves, rather than detection by each parasite genome present. In the specific use case, fragmenting the sample(s) include one of a mechanical fragmentation operation and an enzymatic fragmentation operation.

[0124] In one specific use case, the methods can be used to detect rare target mutations in the JAK2 gene, which are important for characterizing myeloproliferative neoplasms (MPNs), which are associated with excessive blood cell production and risks of thrombosis and leukemia. Such rare targets are present with wild type molecules, and the ability to detect such rare molecule targets, with pre-amplifi cation and distribution across greater than 30 million partitions, provides a highly sensitive means of characterization with a lowered detection threshold.

[0125] In another specific use case, the methods can be used to determine an amount of non-self vs. self genetic material in a sample mixture (e.g., from relative abundance calculations), where selfgenetic material originates from a subject, and non-self genetic material originates from another subject, and both the self genetic material and non-self genetic material may be mixed within the same sample. Determination of non-self vs. self genetic material can have specific uses in one or more of: non-invasive prenatal testing (NIPT) and non-invasive prenatal screening (e.g. for measuring fetal DNA fraction in maternal blood); evaluation or prediction of success of organ transplants (e.g. predicting rejection events by monitoring level of donor DNA in recipient’s blood); evaluation of a sample to characterize DNA associated with cancers and DNA not associated with cancers (e.g., tumor DNA vs. non-tumor DNA); evaluation of a mixture of environmental samples (e.g., for detection of genetically modified organisms); forensic applications (e.g., detection of minute amounts of suspect DNA in a sample, which is difficult to detect by implementation of other PCR platforms); and other use cases. In some embodiments, the rare target component comprises a target associated with a genetically-modified organism. In some embodiments, the genetically-modified organism comprises a crop.

[0126] In another specific use case, the method(s) can be used for evaluation of minimal residual disease (MRD) based upon detection of numbers of cancer cell targets present in a sample from a subject after one or more phases of cancer treatment (e.g., treatment of leukemia, treatment of lymphoma, treatment of multiple myeloma, etc.).

[0127] In another specific use case, the method(s) can be used for single nucleotide polymorphism genotyping (SNPtyping) to measure genetic variations of SNPs between members (e.g., members of a species). Additionally, the method(s) can be used for single nucleotide variant genotyping (SNVtyping) for germline DNA samples.

[0128] The method(s) can also be used for applications involving disease prediction generation and monitoring with multiplexed detection of markers of a gene expression marker panel (e.g., for pregnancy-associated complications, for other applications).

[0129] The method(s) can be applied to samples from human organisms, other multicellular animals, plants, fungi, unicellular organisms, viruses, other material, or a combination thereof, with respect to evaluating presence or absence of sets of targets in parallel. Characterizations of the sets of targets can then be used for diagnostic purposes, for generation of targeted therapies to improve states of organisms from which the samples were sourced, or a combination thereof. The method(s) can also provide value in research or other non-clinical settings, with or without evaluation and processing of live human or mammalian biological material, and without the immediate purpose of obtaining a diagnostic result of a disease or health condition.

[0130] In some embodiments, the methods disclosed herein comprise processing a sample comprising a rare target component, for detection of the rare target component within a set of partitions comprising at least 20 million partitions within a single closed container. In some embodiments, the method is performed within a duration of 3 hours or less. In some embodiments, each partition of the set of partitions comprises at most one rare target of the rare target component of the sample. In some embodiments, the method is executed without performance of a Poisson error correction operation.

[0131] In some embodiments, the methods disclosed herein comprise processing a sample comprising a rare target component, for detection of the rare target component within a set of partitions within a single closed container, wherein processing the sample comprises driving the rare target component of the sample to a low count range of a detection system configured to scan the single closed container, wherein the low count range is a range of 1 to 1000 targets. In some embodiments, driving the rare target component to the low count range comprises: (a) generating a pre-amplified sample upon pre-amplifying the rare target component with a set of pre-amplification cycles; (b) generating a purified sample upon performing a purification operation with the preamplified sample; and (c) distributing the purified sample across the set of partitions, wherein each partition of said set of partitions comprises a portion of the purified sample and processing materials. In some embodiments, processing the sample provides a sensitivity for detection of the rare target component, with a limit of blank (LoB) less than 0.005 and a limit of detection (LoD) less than 0.02 in relation to variant allele frequency (VAF) percentage.

[0132] The method(s) confer(s) the benefit of providing non-naturally occurring compositions for facilitating interactions with and amplification of a large set of target analytes from a sample in parallel, with improved efficiency, without utilizing complex microfluidic setups, and in a manner that reduces overall costs. As such, the method(s) provide a cost-competitive alternative to other methods for detection and digital quantitation of a large number of target analytes in a multiplexed manner.

[0133] The method(s) can provide mechanisms for target-specific / allele-specific amplification and can be applied to digital polymerase chain reaction (dPCR), other PCR-associated assays, or a combination thereof.

[0134] Additionally or alternatively, the method(s) can confer any other suitable benefit.2. Methods and Materials

[0135] As shown in FIG. 1A, embodiments of a method 100 include processing a sample comprising an amount of input nucleic acids (e.g., greater than 1 microgram), for detection of a target component, wherein the target component present in the nucleic acids is within a set of partitions within a single closed container S110, wherein processing the sample includes: generating a fragmented sample upon fragmenting the nucleic acids of the sample S120; distributing the fragmented sample across the set of partitions, wherein each partition of the set of partitions comprises a portion of the fragmented sample and processing materials S140; reacting the processing materials of each partition of the set of partitions with the portion of the fragmented sample, thereby driving the target component of the sample to a level of detection of a detection system configured to scan the single closed container and count a set of positive partitions of the set of partitions, wherein a positive partition of the set of positive partitions emits a signal associated with the target component S150; detecting the set of positive partitions upon scanning the single closed container S160; and returning an analysis of the target component S170.

[0136] As shown in FIG. 1B, embodiments of a method 200 include processing a sample comprising a rare target component, for detection of the rare target component within a set of partitions within a single closed container S210, wherein processing the sample includes: generating a pre-amplified sample upon pre-amplifying the rare target component with a set of pre-amplification cycles S220; generating a purified sample upon performing a purification operation with the pre-amplified sample S230; distributing the purified sample across the set of partitions, wherein each partition of the set of partitions comprises a portion of the purified sample and processing materials S240; reacting the processing materials of each partition of the set of partitions with the portion of the purified sampl e, thereby driving the rare target component of the sample to a level of detection of a detection system configured to scan the single closed container and count a set of positive partitions of the set of partitions, wherein a positive partition of the set of positive partitions emits a signal associated with the rare target component S250; detecting the set of positive partitions upon scanning the single closed container S260; and returning an analysis of the rare target component S270.

[0137] As shown in FIG. 1C embodiments of a method 300 for detection and quantitation (e.g., multiplexed detection and quantification) of targets includes: detecting signals indicative of a profile of a set of targets, from a sample distributed across a set of partitions (e.g., a high number of partitions at low occupancy ) S310, and returning a characterization of the sample based upon the profile S320. In embodiments, said signals correspond to a set of color combinatorics, other differentiable signals resulting from probes used to tag targets, or a combination thereof, whereincolor combinatorics of the set of color combinatorics may be paired with targets of the set of targets, and where the set of targets has a total number greater than the number of color channels used to detect colors corresponding to the set of color combinatorics. As such, the method can provide unique labeling for multiplexed characterization of a panel of targets based upon color combinatorics. In some cases, the method may not comprise multiplexing based solely upon signal amplitudes. Alternatively, in relation to molecule targets (e.g., rare molecule targets) and detection thereof, a first label can be used for a first sequence associated with the target (e.g., rare target), a second label can be used for a second sequence associated with the target (e.g., rare target), and a third label can be used for a control sequence. In embodiments in relation to rare molecule targets and detection thereof, a first label can be used for the rare target, and a second label can be used for a background non-target molecule (e.g., wild type molecule). As such, the sample can include a wild type background component that is distributed across partitions as part of the workflow for detection of the rare target component. Forward and reverse primers can be designed for amplification of a specific locus or specific loci of interest.

[0138] In some embodiments, the primers are 121 / 122 primer sets. In some embodiments, the primers are S35 / S36 primer sets. In some embodiments, the primers are S34 / S67 primer sets. In some embodiments, the primers are TCZ1 / TCZ2 primer sets. In some embodiments, the primers are Cruzi 1 / Cruzi 2 primer sets. In some embodiments, Cruzi 1 / Cruzi 2 / Cruzi 3 primer sets.

[0139] In some embodiments, the 121 forward primer comprises a nucleotide sequence of 5'-AAATAATGTACGGGKGAGATGCATGA-3' (SEQ ID NO: 28). In some embodiments, the 122 reverse primer comprises a nucleotide sequence of 5 -GGTTCGATTGGGGTTGGTGTAAT ATA-3' (SEQ ID NO: 29).

[0140] In some embodiments, the S35 forward primer comprises a nucleotide sequence of 5'-AAATAATGTACGGG(T / G)GAGATGCATGA-3' (SEQ ID NO: 30). In some embodiments, the S36 reverse primer comprises a nucleotide sequence of 5'-GGGTTCGATTGGGGTTGGTGT-3' (SEQ ID NO: 31).

[0141] In some embodiments, the S34 forward primer comprises a nucleotide sequence of 5'-A / XCGCTATTATTGTTGTTGC-3' (SEQ ID NO: 32). In some embodiments, the S67 reverse primer comprises a nucleotide sequence of 5'-GGTTCGATTGGGGTTGGTG-3' (SEQ ID NO: 33).

[0142] In some embodiments, the Cruzi 1 forward primer comprises a nucleotide sequence of 5'-ASTCGGCTGATCGTTTTCGA-3' (SEQ ID NO: 5). In some embodiments, the Cruzi 2 reverse primer comprises a nucleotide sequence of 5'-AATTCCTCCAAGCAGCGGATA-3' (SEQ ID NO:6). In some embodiments, the Cruzi 3 primer comprises a nucleotide of 5'-CACACACTGGACACCAA-3' (SEQ ID NO: 34).

[0143] In some embodiments, the forward primer comprises a nucleotide sequence of: 5'-CCCCCCTCCCAGGCCAC / XCTG-3' (SEQ ID NO: 35). In some embodiments, the reverse primer comprises a nucleotide sequence of: 5'-GTGTCCGCC / XCCTCCTTCGGGCC-3' (SEQ ID NO: 36).

[0144] In some embodiments, the forward primer comprises a nucleotide sequence of: 5'-TGGGATAACAAAGGAGCA-3' (SEQ ID NO: 37). In some embodiments, the reverse primer comprises a nucleotide sequence of: 5'-TCAGCCTGTTGAGTCAAATT-3' (SEQ ID NO: 38).

[0145] In some embodiments, the forward primer comprises a nucleotide sequence of: 5'-ATACCCCAATATCATTCATG-3' (SEQ ID NO: 39). In some embodiments, the reverse primer comprises a nucleotide sequence of: 5'-CCACATAGTACGAGGGTG-3' (SEQ ID NO: 40).

[0146] The methods function to enable detection of genetic variations in biological sample material, in a multiplexed manner. In more detail, the methods enable performance of ultra-high multiplexed target detection by implementing a high number of partitions (e.g., more than 100,000 partitions, more than 200,000 partitions, more than 500,000 partitions, more than 1 million partitions, more than 10 million partitions, more than 20 million partitions, more than 30 million partitions, more than 50 million partitions, more than 100 million partitions, etc.) with low-occupancy (e.g., less than 10% occupancy, less than 8% occupancy, less than 5% occupancy, etc.) of partitions by targets. In particular, use of a low-occupancy platform involving high numbers of partitions provides a regime where the probability of encountering more than one target in a partition is very low, such that a unique color combination can be inferred from the particular target color-coded by the unique color combination.

[0147] In some embodiments, the sample comprises at least 0.01 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.02 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.03 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.04 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.05 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.06 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.07 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.08 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.09 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.1 microgram of nucleic acidmaterial. In some embodiments, the sample comprises at least 0.125 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.15 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.175 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.2 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.3 microgram of nucleic acid material. In some embodiments, the sample comprises at least 0.4 microgram of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 0.5 microgram of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 1.0 microgram of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 2.0 micrograms of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 3.0 micrograms of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 4.0 micrograms of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 5.0 micrograms of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 6.0 micrograms of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 7.0 micrograms of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 8.0 micrograms of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 9.0 micrograms of nucleic acid material. In some embodiments, the nucleic acid sample comprises at least 10.0 micrograms of nucleic acid material. In some embodiments, the nucleic acid sample comprises other amounts of nucleic acid material.

[0148] In some embodiments, the nucleic acid material may comprise one or more nucleic acid molecules. In some embodiments, the one or more nucleic molecules of the nucleic acid sample may have a variety of sizes and lengths. In some embodiments, each of the one or more nucleic acid molecules of the nucleic acid sample in a sampl e may have the same size. In some embodiments, the one or more nucleic acid molecules of the nucleic acid sample may have different sizes. In some embodiments, each of the one or more nucleic acid molecules of the nucleic acid sample may have the same length. In some embodiments, the one or more nucleic acid molecules may have different lengths. In some embodiments, the one or more nucleic acid molecules of the nucleic acid sample may have lengths of up to 10 base pairs (bp), up to 15 bp, up to 20 bp, up to 25 bp, up to 30 bp, up to 35 bp, up to 40 bp, up to 45 bp, up to 50 bp, up to 60 bp, up to 70 bp, up to 80 bp, up to 90 bp, up to 100 bp, up to 110 bp, up to 120 bp, up to 130 bp, up to 140 bp, up to 150 bp, up to 160 bp, up to 170 bp, up to 180 bp, up to 190 bp, up to 200 bp, up to 210 bp, up to 220 bp, up to 230 bp, up to 240 bp,up to 250 bp, up to 260 bp, up to 270 bp, up to 280 bp, up to 290 bp, up to 300 bp, up to 310 bp, up to 320 bp, up to 330 bp, up to 340 bp, up to 350 bp, up to 360 bp, up to 370 bp, up to 380 bp, up to 390 bp, up to 400 bp, up to 410 bp, up to 420 bp, up to 430 bp, up to 440 bp, up to 450 bp, up to 460 bp, up to 470 bp, up to 480 bp, up to 490 bp, up to 500 bp, up to 520 bp, up to 540 bp, up to 560 bp, up to 580 bp, up to 600 bp, up to 620 bp, up to 640 bp, up to 660 bp, up to 680 bp, up to 700 bp, up to 720 bp, up to 740 bp, up to 780 bp, up to 780 bp, up to 800 bp, up to 820 bp, up to 840 bp, up to 860 bp, up to 880 bp, up to 900 bp, up to 920 bp, up to 940 bp, up to 960 bp, up to 980 bp, up to 1 (kilo base pairs) kb, up to 1.2 kb, up to 1.4 kb, up to 1.6 kb, up to 1.8 kb, up to 2 kb, up to 2.2 kb, up to 2.4 kb, up to 2.6 kb, up to 2.8 kb, up to 3 kb, up to 3.2 kb, up to 3.4 kb, up to 3.6 kb, up to 3.8 kb, up to 4 kb, up to 4.2 kb, up to 4.4 kb, up to 4.6 kb, up to 4.8 kb, up to 5 kb, up to 10 kb, up to 20 kb, up to 50 kb, up to 100 kb, or longer.

[0149] In relation to detection and effective use of sample processing materials, the method(s) involve detection of signals from targets of interest of a processed sample, where the signals correspond to different color combinatorics of a set of color combinatorics, alone or in combination with other types of differentiable signals, where color combinatorics of the set of color combinatorics may be paired with targets of the set of targets, and where the set of targets has a total number greater than the number of color channels used to detect colors corresponding to the set of color combinatorics. In particular, due to the high-degree of partitioning described herein, any positive partition (e.g., droplet and / or disperse phase of an emulsion generated from the sample and containing a target) may contain one color combination corresponding to fluorescent materials used during processing of the sample, thereby providing an accurate mechanism for multiplexed detection.

[0150] In specific examples, the method(s) can provide a multi-color combinatoric scheme with 5-color assay. As described in more detail herein, the methods can provide mechanisms for multi-color combinatorics using competitive target-specific or allele-specific assays (e.g., Kompetitiv allelespecific PCR (KASP), PCR allele competitive extension (PACE), etc.), other assay chemistries, or a combination thereof because they involve no additional probe sequence within generated amplicons, provide a low degree of assay complexity, and thus result in significantly reduced assay cost for a panel of targets. In variations, such assays can be based upon target-specific (e.g., allele-specific) oligonucleotide extension and fluorescence resonance energy transfer for signal generation. In alternative variations, such assays can be based upon generation and detection of other types of signals.

[0151] The methods can further provide functionality for multiplexed detection of genetic variants in a sample by optimizing the amount of information obtained using lower-cost and / or a reduced set of sample processing materials compared to assays based upon fluorescent detection, involving a higher number of primer types, probe types, quencher types, and probe additives. In combination with a higher number of colors / dyes used for detection, the methods can further improve the number of targets that can be detected from a sample within a single container.

[0152] The method(s) can be implemented by embodiments, variations, and examples of system components described in U. S. Application number 17 / 230,907 filed on 14-APR-2021 and / or U. S. Application number 17 / 687,080 filed 04-MAR-2022, which may be each hereby incorporated in its entirety by this reference. Additionally or alternatively, the method(s) can be implemented by other system elements.

[0153] Sample Types and Targets: In variations, the methods 100 and 200 can be used to process sample types including biological fluids including or derived from one or more of: blood (e.g., whole blood, peripheral blood, non-peripheral blood, blood lysate, etc.), plasma, serum, saliva, reproductive fluids, mucus, pleural fluid, pericardial fluid, peritoneal fluid, amniotic fluids, optic fluid, sweat, interstitial fluid, synovial fluid, cerebral-spinal fluid, urine, gastric fluids, biological waste, other biological fluids; tissues (e.g., homogenized tissue samples); food samples; liquid consumable samples; and / or other sample materials. In some embodiments, the sample comprises a whole blood sample. In some embodiments, the sample comprises a tissue sample. Samples can be derived from human organisms, other multicellular animals, plants, fungi, unicellular organisms, viruses, and / or other material. In specific examples, samples processed can include maternal samples (e.g., blood, plasma, serum, urine, chorionic villus, etc.) including maternal and fetal material (e.g., cellular material, cell-tree nucleic acid material, other nucleic acid material, etc.) from which prenatal detection or diagnosis of genetic disorders (e.g., aneuploidies, genetically inherited diseases, other chromosomal issues, etc.) can be performed.

[0154] In embodiments, targets detected according to embodiments, variati ons, and examples of the methods 100 and 200 can include: nucleic acids (e.g., DNA, RNA, miRNA, etc.), proteins, amino acids, peptides, small molecules, single analytes, multianalytes, chemicals, and / or other target material, in order to enable genomic, proteomic, and / or other multi-omic characterizations and diagnoses for various applications. Genetic targets can include one or more of: single nucleotide polymorphisms (SNPs), copy number variations (CNVs), insertions, deletions, genes, methylatedloci. and / or other loci of interest. In some embodiments, the input nucleic acids comprise genomic DNA. In some embodiments, the target component comprises a parasite nucleic acid component.

[0155] In some embodiments, the target component comprises one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component. In some embodiments, the target component comprises at least two shorter nucleotide sequences that are repetitive sequences characteristic of the target component. In some embodiments, the target component comprises at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, or a greater number of shorter nucleotide sequences that are repetitive sequences characteristic of the target component.

[0156] In some embodiments, the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component has a length up to 20 base pairs (bp), up to 30 bp, up to 40 bp, up to 50 bp, up to 60 bp, up to 70 bp, up to 80 bp, up to 90 bp, up to 100 bp, up to 110 bp, up to 120 bp, up to 130 bp, up to 140 bp, up to 150 bp, up to 160 bp, up to 170 bp, up to 180 bp, up to 190 bp, up to 195 bp, up to 200 bp, up to 210 bp, up to 220 bp, up to 230 bp, up to 240 bp, up to 250 bp, up to 260 bp, up to 270 bp, up to 280 bp, up to 290 bp, up to 300 bp, up to 310 bp, up to 320 bp, up to 330 bp, up to 340 bp, up to 350 bp, up to 360 bp, up to 370 bp, up to 380 bp, up to 390 bp, up to 400 bp, up to 410 bp, up to 420 bp, up to 430 bp, up to 440 bp, up to 450 bp, up to 460 bp, up to 470 bp, up to 480 bp, up to 490 bp, up to 500 bp, up to 520 bp, up to 540 bp, up to 560 bp, up to 580 bp, up to 600 bp, up to 620 bp, up to 640 bp, up to 660 bp, up to 680 bp, up to 700 bp, up to 720 bp, up to 740 bp, up to 780 bp, up to 780 bp, up to 800 bp, up to 820 bp, up to 840 bp, up to 860 bp, up to 880 bp, up to 900 bp, up to 920 bp, up to 940 bp, up to 960 bp, up to 980 bp, up to 1 (kilo base pairs) kb, up to 1.2 kb, up to 1.4 kb, up to 1.6 kb, up to 1.8 kb, up to 2 kb, up to 2.2 kb, up to 2.4 kb, up to 2.6 kb, up to 2.8 kb, up to 3 kb, up to 3,2 kb, up to 3.4 kb, up to 3.6 kb, up to 3.8 kb, up to 4 kb, up to 4.2 kb, up to 4.4 kb, up to 4,6 kb, up to 4.8 kb, up to 5 kb, or greater.

[0157] In some embodiments, the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component has a length of about 25-50 bp, about 50-100 bp, about 100-150 bp, about 150-200 bp, about 200-250 bp, about 250-300 bp, about 300-350 bp, about 350-400 bp, about 400-450 bp, about 450-500 bp, about 500-550 bp, about 550-600 bp, about 600-650 bp, about 650-700 bp, about 700-750 bp, about 750-800 bp, about 800-850 bp, about 850-900 bp, about 900-950 bp, about 950-1 kb, about 1-1.5kb, about 1.5-2 kb, about 2-2.5 kb, about 2.5-3 kb, about 3-3.5 kb, about 3.5-4 kb, about 4-4.5 kb, about 4.5-5 kb, or any intermediate length.

[0158] In some embodiments, the target component comprises a genome wherein up to 5%, up to 10%, up to 15%, up to 20%, up to 25%, up to 30%, up to 35%, up to 40%, up to 45%, up to 50%, or a greater percentage of the genome is comprised of one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component.

[0159] In some embodiments, the target component comprises a rare target component associated with an infectious disease agent. In embodiments, the rare target component comprises DNA selected from: Trypanosoma cruzi, Mycobacterium leprae, Trichomonas vaginalis, Schistosoma mansoni, Schistosoma japonicum, Orientia tsutsugamushi, Trypanosoma brucei, Trypanosoma congolense, Leishmania donovani, Leishmania major, Leishmania braziliensis, Leishmania infantum, Eimeria tenella, Theileria annulata, Theileria parva, Entamoeba histolytica, Toxoplasma gondii, Plasmodium vivax, Plasmodium knowlesi, Plasmodium ovale, Plasmodium malariae, Acanthamoeba castellanii, Mycobacterium tuberculosis, Plasmodium falciparum, Babesia bovis, Leishmania tropica, and a combination thereof. In some embodiments, the rare target component comprises DNA from Trypanosoma cruzi. In some embodiments, the rare target component comprises DNA from Mycobacterium leprae. In some embodiments, the rare target component comprises DNA from Trichomonas vaginalis. In some embodiments, the rare target component comprises DNA from Schistosoma mansoni. In some embodiments, the rare target component comprises DNA from Schistosoma japonicum. In some embodiments, the rare target component comprises DNA from Orientia tsutsugamushi. In some embodiments, the rare target component comprises DNA from Trypanosoma brucei. In some embodiments, the rare target component comprises DNA from Trypanosoma congolense, In some embodiments, the rare target component comprises DNA from Leishmania donovani. In some embodiments, the rare target component comprises DNA from Leishmania major. In some embodiments, the rare target component comprises DNA from Leishmania braziliensis. In some embodiments, the rare target component comprises DNA from Leishmania infantum. In some embodiments, the rare target component comprises DNA from Eimeria tenella. In some embodiments, the rare target component comprises DNA from Theileria annulata. In some embodiments, the rare target component comprises DNA from Theileria parva. In some embodiments, the rare target component comprises DNA from Entamoeba histolytica. In some embodiments, the rare target component comprises DNA from Toxoplasma gondii. In some embodiments, the rare target component comprises DNA from Plasmodium vivax. In some embodiments, the rare target component comprises DNA from Plasmodium knowlesi. In some embodiments, the rare target component comprises DNA fromPlasmodium ovale. In some embodiments, the rare target component comprises DNA from Plasmodium malarias. In some embodiments, the rare target component comprises DNA from Acanthamoeba castellanii. In some embodiments, the rare target component comprises DNA from Mycobacterium tuberculosis. In some embodiments, the rare target component comprises DNA from Plasmodium falciparum. In some embodiments, the rare target component comprises DNA from Babesia bovis. In some embodiments, the rare target component comprises DNA from Leishmania tropica. In some embodiments, the one or more shorter nucleotide sequences comprise kinetoplast DNA (kDNA), microsatellite DNA, nuclear satellite DNA (satDNA), DNA encoding single-copy nuclear genes, DNA encoding mitochondrial maxicircle genes, or a combination thereof. In some embodiments, the kDNA comprises a nucleotide sequence of SEQ ID NO: 1. In some embodiments, the microsatellite DNA comprises a nucleotide sequence of SEQ ID NO: 5.

[0160] In some embodiments, the rare target component comprises a target associated with one of: Gaucher disease, Tay-Sachs disease, Krabbe disease, Alpha- 1 antitrypsin deficiency, Niemann-Pick disease type C, Pompe disease, Fabry disease, Metachromatic leukodystrophy disease, GM1 gangliosidosis, Sandhoff disease, Phenylketonuria, Maple syrup urine disease, Galactosemia, Medium-chain acyl-CoA dehydrogenase (MCAD) deficiency, Polycythemia vera, Essential thrombocythemia, Primary myelofibrosis, Factor V Leiden, Achondroplasia, Marfan syndrome, Osteogenesis imperfecta, Ehlers-Danlos syndrome, Sickle cell disease, a-thalassemia, andP" thalassemia.

[0161] In some embodiments wherein the target component comprises a parasite nucleic acid component and / or rare target component associated with an infectious disease agent (e.g., T. cruzi), the amount of parasitic DNA present in the sample comprises less than 1, less than 0.9, less than 0.8, less than 0.7, less than 0.6, less than 0.5, less than 0.4, less than 0.3, less than 0.2, less than 0.1, less than 0,09, less than 0.08, less than 0.07, less than 0.06, less than 0.05, less than 0.04, less than 0,03, less than 0.02, less than 0.01, or lower parasite equivalents per mL of sample.

[0162] In some embodiments, the rare target component comprises a target associated with minimal residual disease (MRD).

[0163] In some embodiments, the rare target component comprises a mutation in a JAK2 gene. In some embodiments, the mutation in the JAK2 gene comprises a V617F mutation.

[0164] In some embodiments, the sample further comprises a background component. In some embodiments, the background component comprises an amplification control comprising a nucleotide sequence of SEQ ID NO: 13. In some embodiments, the background componentcomprises a JAK2 wild type background component. In some embodiments, the background component comprises one or more housekeeping genes.

[0165] In some embodiments, the rare target component comprises a target associated with a genetically-modified organism. In some embodiments, the genetically-modified organism comprises a crop.

[0166] Additionally or alternatively, in other specific applications, target material tagged in a multiplexed manner and evaluated according to methods described herein can provide diagnostics and / or characterizations in relation to one or more of: monitoring or detection of products (e.g., proteins, chemicals) released from single cells (e.g., interleukins or other compounds released from immune cells); monitoring cell survival and / or division for single cells; monitoring or detection of enzymatic reactions involving single cells; antibiotic resistance screening for bacteria; characterization of pathogens in a sample (e.g., in relation to infections, sepsis, m relation to environmental and food samples, etc.); microbiome characterizations (e.g., based upon detection of hypervariable regions of rRNA); characterization of heterogeneous cell populations in a sample; characterization of individual cells or viral particles; monitoring of viral infections of a single host cell; liquid biopsies and companion diagnostics; detection of cancer forms from various biological samples (e.g., from cell-free nucleic acids, tissue biopsies, biological fluids, feces, etc.) based upon characterization of target panels; detection and / or monitoring of minimal residual diseases; monitoring responses to therapies; detection or prediction of rejection events of transplanted organs; other diagnostics associated with other health conditions; other characterizations of statuses of other organisms; and other suitable applications.

[0167] A specific example of the method 100, as shown in FIG, 2A, involved extraction of DNA from 5 mL of a whole blood sample potentially including nucleic acid material associated with an infectious agent (e.g., T. cruzi), followed by fragmentation of extracted DNA, and distribution of a large amount (e.g., 3 micrograms) of input DNA across partitions within closed containers. As such, the specific example demonstrated that high input capacity and efficient processing could be used to process 24 times more DNA than a typical qPCR reaction with a single reaction, handling 3 pg of extracted DNA compared to 125 ng for a standard qPCR This substantially increases the likelihood of detecting rare molecules, such as those associated with T. cruzi. Partitioning was performed using 20 minutes of centrifugation (e.g., using an example of the system shown in FIG. 4), followed by amplification of partitioned material and subsequent detection by 3D imaging with a lightsheet scanner. In the specific example of step SI 20, fragmented sample was processed, with master mix,according to embodiments, variations, and examples of subsequent steps S140, SI 50, and SI 60, described in more detail herein. A titration study was performed to show that examples of the methods described herein can reliably detect parasite targets with up to 3 pg of input DNA -24 times more than qPCR. Consistent Internal Amplification Control (IAC) counts were observed up to 5 pg input of Lambda background DNA. Based on these findings, a 3 pg input was selected for subsequent tests, balancing optimal performance and reliability. This approach significantly improves the efficiency of Chagas screening assays by reducing the number of required reactions while maintaining assay integrity. Other amounts of input can, however, be envisioned, for other applications of use and / or other targets being detected. FIG. 2H depicts results of the input titration for Chagas detection. Lambda DNA spiked with parasite DNA and synthetic IAC used as background. Reactions were prepared, centrifuged, amplified, and imaged. Counts per 50 pL were then obtained.2.1. Method - Pre-processing: Fragmentation

[0168] Step S120 recites: Generating a fragmented sample upon fragmenting the nucleic acids of the sample S120. Fragmenting in Step SI 20 functions to generate shorter sequences that still include characteristic sequences for detection of the target component, whereby the shorter sequences are distributed across a large number of partitions such that each partition contains at most one target sequence (e.g., shorter target sequence) that is labeled and detected with processing materials. FIG.2B depicts schematics showing how fragmentation improves assay sensitivity with respect to detection of shorter sequences (e.g., repetitive sequences that can be used to identify a target).Multiple optimization steps were performed to improve parasite detection upon fragmentation of parasite DNA, in order to achieve high -sensitivity detection of repetitive template sequences associated with the parasite DNA. After Step SI 20 is performed, the resultant fragmented sample can then be combined with process materials as described in relation to step S140 herein.

[0169] In some embodiments, generating the fragmented sample comprises performing one or more methods of fragmenting nucleic acids selected from: a physical method, an enzymatic method, and a chemical method. Physical fragmentation methods employ physical forces to break long nucleic acids into shorter fragments with minimal sequence bias. Representative embodiments of physical fragmentation methods include focused ultrasonication (e.g., acoustic systems that concentrate energy into the sample, such as Govans / Adaptive Focused Acoustics shearing technology), generic probe / bath sonication, hydrodynamic shearing through narrow orifices, nebulization withcompressed gas, microfluidic shear in defined channels, bead beating, and needle or pipette shearing. Physical fragmentation methods are valued for low sequence bias and tunable fragment size distributions. Parameters that can be tuned to yield target size distributions include acoustic intensit / peak power, number of cycles, exposure time, and temperature. Enzymatic fragmentation methods use nucleases and engineered enzyme systems to cleave nucleic acids at random or defined sites. In some embodiments, enzyme-based methods include transposases, restriction enzymes (e.g., mung bean nucleases, nuclease Pl, or micrococcal nuclease), Dnase I, non-specific nucleases, and nicking enzymes, or a mixture thereof. In some embodiments, enzyme-based DNA / RNA fragmentation methods include using a mixture of at least two different enzymes e.g., two or more of the enzymes mentioned in the preceding sentence e.g. two or more nucleases. Any standard enzymatic fragmentation buffer and enzymatic fragmentation enzyme can be used for fragmenting the DNA or RNA. In a representative embodiment, sequence-specific restriction endonucleases can be used to cleave nucleic acids at selected and defined states. Chemical fragmentation methods induce nucleic acid fragmentation through chemical or radiative treatment rather than physical / mechanical or enzymatic cleavage. Common chemical fragmentation approaches include acid-catalyzed depurination, alkaline hydrolysis, oxidative cleavage (e.g., via reactive oxygen species), irradiation (e.g., UV irradiation), and thermal or freeze-thaw stress. Thermal stress and repeated freeze-thaw cycles can fragment high molecular weight nucleic acids via physical stress and hydrolytic acceleration. Chemical fragmentation methods can be simple, low-cost, and performed without specialized instrumentation, but typically offer more limited control over fragment size. In some embodiments, chemical fragmentation methods include the use of agents which generate hydroxyl radicals for random DNA cleavage or the use of heat with divalent metal cations.

[0170] In variations, fragmentation can involve one or more of mechanical fragmentation (e.g., sonication, bead beating, etc.), enzymatic fragmentation (e.g., using digestion enzymes, using restriction-digestion agents), fragmentation using heating of a sample, fragmentation using cooling of a sample, and / or other methods of fragmentation. In some embodiments, generating the fragmented sample comprises performing one or more operations on the sample selected from: a mechanical fragmentation operation, an enzymatic fragmentation operation, a heating fragmentation operation, and a cooling fragmentation operation.

[0171] In some embodiments, generating the fragmented sample comprises performing a mechanical fragmentation operation on the sample. In some embodiments, the mechanical fragmentationoperation comprises acoustic shearing, hydrodynamic shearing, needle shearing, microfluidic shearing, sonication, nebulization, bead beating, cryogenic grinding, or a combination thereof. In some embodiments, the mechanical fragmentation operation comprises acoustic shearing, sonication, or a combination thereof. In some embodiments, the mechanical fragmentation operation comprises acoustic shearing. In some embodiments, the mechanical fragmentation operation comprises sonication. In some embodiments, the mechanical fragmentation comprises Covaris treatment (e.g., Covaris shearing).

[0172] In some embodiments, generating the fragmented sample comprises performing an enzymatic fragmentation operation on the sample. In some embodiments, the enzymatic fragmentation operation comprises treatment (e.g., digestion) with one or more restriction endonucleases. In some embodiments, the one or more restriction endonucleases are selected from: a SacI restriction endonuclease, a Msel restriction endonuclease, and isoschizomers thereof. In some embodiments, the restriction endonuclease is a SacI restriction endonuclease. In some embodiments, the restriction endonuclease is a Msel restriction endonuclease.

[0173] In some embodiments, generating the fragmented sample upon fragmenting the nucleic acids of the sample increases the sensitivity of detection (e.g., number of molecules detected) relative to the unfragmented sample. In some embodiments, generating the fragmented sample upon fragmenting the nucleic acids of the sample increases the sensitivity of detection of one or more shorter nucleotide sequences of the fragmented sample that is characteristic of the target component. In some embodiments, generating the fragmented sample increases the sensitivity of detection of the one or more shorter nucleotide sequences of the fragmented sample that is characteristic of the target component by at least 1.5-fold, by at least 2-fold, by at least 2.5-fold, by at least 3-fold, by at least 3.5-fold, by at least 4-fold, by at least 4.5-fold, by at least 5-fold, by at least 5.5-fold, by at least 6-fold, by at least 6.5-fold, by at least 7-fold, by at least 7.5-fold, by at least 8-fold, by at least 8.5-fold, by at least 9-fold, by at least 9.5-fold, by at least 10-fold, by at least 11-fold, by at least 12-fold, by at least 13-fold, by at least 14-fold, by at least 15-fold, by at least 16-fold, by at least 17-fold, by at least 18-fold, by at least 19-fold, by at least 20-fold, or by a greater amount. In some embodiments, generating the fragmented sample increases the sensitivity of detection of the one or more shorter nucleotide sequences of the fragmented sample that is characteristic of the target component by at least 1.5-fold, by at least 2-fold, by at least 2.5-fold, by at least 3-fold, by at least 3.5-fold, by at least 4-fold, by at least 4.5-fold, by at least 5-fold, by at least 5.5-fold, by at least 6-fold, by at least 6.5-fold, by at least 7-fold, by at least 7.5-fold, by at least 8-fold, by at least 8.5-fold, by at least 9-fold,by at least 9.5-fold, by at least 10-fold, by at least 11-fold, by at least 12-fold, by at least 13-fold, by at least 14-fold, by at least 15-fold, by at least 16-fold, by at least 17-fold, by at least 18-fold, by at least 19-fold, by at least 20-fold, or by a greater amount, compared to the method steps performed without the fragmentation step (or multiple fragmentation steps).

[0174] Fragmentation can be used to generate sequences having lengths of up to 20 base pairs (bp), up to 30 bp, up to 40 bp, up to 50 bp, up to 60 bp, up to 70 bp, up to 80 bp, up to 90 bp, up to 100 bp, up to 110 bp, up to 120 bp, up to 130 bp, up to 140 bp, up to 150 bp, up to 160 bp, up to 170 bp, up to 180 bp, up to 190 bp, up to 195 bp, up to 200 bp, up to 210 bp, up to 220 bp, up to 230 bp, up to 240 bp, up to 250 bp, up to 260 bp, up to 270 bp, up to 280 bp, up to 290 bp, up to 300 bp, up to 310 bp, up to 320 bp, up to 330 bp, up to 340 bp, up to 350 bp, up to 360 bp, up to 370 bp, up to 380 bp, up to 390 bp, up to 400 bp, up to 410 bp, up to 420 bp, up to 430 bp, up to 440 bp, up to 450 bp, up to 460 bp, up to 470 bp, up to 480 bp, up to 490 bp, up to 500 bp, up to 520 bp, up to 540 bp, up to 560 bp, up to 580 bp, up to 600 bp, up to 620 bp, up to 640 bp, up to 660 bp, up to 680 bp, up to 700 bp, up to 720 bp, up to 740 bp, up to 780 bp, up to 780 bp, up to 800 bp, up to 820 bp, up to 840 bp, up to 860 bp, up to 880 bp, up to 900 bp, up to 920 bp, up to 940 bp, up to 960 bp, up to 980 bp, up to 1 (kilo base pairs) kb, up to 1.2 kb, up to 1.4 kb, up to 1.6 kb, up to 1.8 kb, up to 2 kb, up to 2.2 kb, up to 2.4 kb, up to 2.6 kb, up to 2.8 kb, up to 3 kb, up to 3.2 kb, up to 3.4 kb, up to 3.6 kb, up to 3.8 kb, up to 4 kb, up to 4.2 kb, up to 4.4 kb, up to 4.6 kb, up to 4.8 kb, up to 5 kb, or greater.

[0175] Fragmentation can be used to generate sequences having lengths of about 25-50 bp, about 50-100 bp, about 100-150 bp, about 150-200 bp, about 200-250 bp, about 250-300 bp, about 300-350 bp, about 350-400 bp, about 400-450 bp, about 450-500 bp, about 500-550 bp, about 550-600 bp, about 600-650 bp, about 650-700 bp, about 700-750 bp, about 750-800 bp, about 800-850 bp, about 850-900 bp, about 900-950 bp, about 950-1 kb, about 1-1,5kb, about 1,5-2 kb, about 2-2.5 kb, about 2,5-3 kb, about 3-3.5 kb, about 3.5-4 kb, about 4-4,5 kb, about 4.5-5 kb, or any intermediate length.

[0176] In some embodiments, fragmenting the nucleic acids of the sample generates 5 or more fragments, 10 or more fragments, 15 or more fragments, 20 or more fragments, 25 or more fragments, 30 or more fragments, 35 or more fragments, 40 or more fragments, 45 or more fragments, 50 or more fragments, 60 or more fragments, 70 or more fragments, 80 or more fragments, 90 or more fragments, 100 or more fragments, 120 or more fragments, 140 or more fragments, 160 or more fragments, 180 or more fragments, 200 or more fragments, 220 or more fragments, 240 or more fragments, 260 or more fragments, 280 or more fragments, 300 or morefragments, 320 or more fragments, 340 or more fragments, 360 or more fragments, 380 or more fragments, 400 or more fragments, 420 or more fragments, 440 or more fragments, 460 or more fragments, 480 or more fragments, 500 or more fragments, 520 or more fragments, 540 or more fragments, 560 or more fragments, 580 or more fragments, 600 or more fragments, 620 or more fragments, 640 or more fragments, 660 or more fragments, 680 or more fragments, 700 or more fragments, 720 or more fragments, 740 or more fragments, 760 or more fragments, 780 or more fragments, 800 or more fragments, 820 or more fragments, 840 or more fragments, 860 or more fragments, 880 or more fragments, 900 or more fragments, 920 or more fragments, 940 or more fragments, 960 or more fragments, 980 or more fragments, 1,000 or more fragments, or greater.

[0177] FIG. 2E depicts results showing that mechanical fragmentation of sample nucleic acids increased microsatellite molecule detection. Bars indicate molecules per 50 pL detected for (A) kDNA, (B) Microsatellite, (C) Internal Amplification Control (1AC) (mean values ± standard error (SE), n = 2). 125 ng of Covaris-sheared DNA was input per reaction. In validating results from mechanical fragmentation performed in relation to FIG. 2E, fragmentation using sonication was used to sequester tandem parasite sequence repeats into distinct partitions for individual detection.Covaris shearing was used to achieve 300 base pair (bp) DNA fragments. In relation to results shown in FIG. 2E, fragmentation did not significantly impact the number of kDNA molecules detected, with 7808 and 7790 (1.1 and 2.1 %CV, n = 2) counts identified for fragmented and unfragmented DNA, respectively. Fragmenting gDNA increased detected microsatellite molecules from 956 to 7829 (1.4 and 0.9 %CV, n = 2) counts identified. IAC values were consistent across conditions suggesting that fragmentation does not affect amplification efficiency. Mechanical fragmentation (e.g., Covaris treatment) was thus used to successfully generate DNA fragments of approximately 300 base pairs. This approach resulted in an 8-fold increase in microsatellite counts but showed no significant change in kDNA detection, possibly due to the unique network structure of kDNA in / '. cruzi.

[0178] FIG, 2F depicts results showing that enzymatic digestion increased kDNA and microsatellite molecule detection. Restriction enzyme digestion of macaque DNA (e.g., typical host model system) spiked with parasite DNA was involved, with a 500 ng input. The two restriction enzyme approaches resulted in 2.5-fold higher detection of kDNA (0.2 and 1.0 %CV, n = 2) and 6.5-fold higher detection of micro-satellite elements (3.7 and 8.7 %CV, n = 2) relative to unfragmented samples. IAC values were consistent across all conditions suggesting that restriction enzyme treatment does not affect amplification efficiency. Bars indicate molecules per 50 pL detected for (A) kDNA, (B)Microsatellite, (C) Internal Amplification Control (IAC) (mean values ± standard error (SE), n = 2).500 ng of restriction-digested DNA input per reaction. In validating results from enzymatic fragmentation performed in relation to FIG. 2F, restriction endonuclease (RE) digestion was assessed as a method to provide additional workflow flexibility without sacrificing assay quality.

[0179] As such, implementing fragmentation boosted sensitivity while reducing reaction numbers. This strategy improved detection of low-abundance T. cruzi genomes in blood, potentially enabling earlier Chagas disease diagnosis.2.2. Method - Pre-processing: Pre-amplification, Purification, and / or Dilution

[0180] Step S220 recites: Generating a pre-amplified sample upon pre-amplifying the rare target component with a set of pre-amplification cycles S220. Pre-amplification in Step S220 functions to drive the sample, having the rare target component, to a state where the rare target component can be accurately detected and characterized by a detection platform. As such, step S220 functions to enable detection of the rare target component of the sample, with a lowered detection threshold (e.g., in terms of limit of blank (LoB) and limit of detection (LoD)).

[0181] Step S230 recites: generating a purified sample upon performing a purification operation with the pre-amplified sample, which functions to generate a processed sample with purified products, for detection in subsequent steps. Sample purification can be performed with a clean up kit (e.g., New England Biolabs™ clean up kit, SPRI clean up kit, etc.). However, variations of the method 200 can omit purification operations performed according to Step S230. That is, in embodiments, the method does not comprise Step S230 generating a purified sample upon performing a purification operation with the pre-amplified sample,

[0182] Pre-amplification can involve pre-amplification of the sample, using a suitable master mix, for a number of cycles, in order to drive the rare target component above a detection threshold, after distributing the rare target components across the set of partitions. In variations, the number of preamplification cycles can be 1 cycle, 2 cycles, 3 cycles, 4 cycles, 5 cycles, 6 cycles, 7 cycles, 8 cycles, 9 cycles, 10 cycles, 11 cycles, 12 cycles, 13 cycles, 14 cycles, 15 cycles, 20 cycles, or more. In some embodiments, the set of pre-amplification cycles comprises at least a number of cycles such that reacting the processing materials of each partition of the set of partitions with the portion of the purified sample drives the rare target component of the sample to a low count range of the detection system configured to scan the single closed container, wherein the low count range is a range of I to1000 targets. In some embodiments, the set of pre-amplification cycles comprises at least a number of cycles such that reacting the processing materials of each partition of the set of partitions with the portion of the purified sample drives the rare target component of the sample to a level of detection of the detection system where the rare target component can be accurately detected. In some embodiments, the set of pre- amplification cycles improves the counts of the rare target component by at least 1.5-fold, by at least 2-fold, by at least 2.5-fold, by at least 3-fold, by at least 3.5-fold, by at least 4-fold, by at least 4.5-fold, by at least 5-fold, by at least 5.5-fold, by at least 6-fold, by at least 6.5-fold, by at least 7-fold, by at least 7.5-fold, by at least 8-fold, by at least 8.5-fold, by at least 9-fold, by at least 9.5-fold, by at least 10-fold, by at least 11-fold, by at least 12-fold, by at least 13-fold, by at least 14-fold, by at least 15-fold, by at least 16-fold, by at least 17-fold, by at least 18-fold, by at least 19-fold, by at least 20-fold, or by a greater amount. In some embodiments, the set of pre-amplification cycles improves the counts of the rare target component by at least 1.5-fold, by at least 2-fold, by at least 2.5-fold, by at least 3 -fold, by at least 3.5-fold, by at least 4-fold, by at least 4.5-fold, by at least 5-fold, by at least 5.5-fold, by at least 6-fold, by at least 6.5-fold, by at least 7-fold, by at least 7.5-fold, by at least 8-fold, by at least 8.5-fold, by at least 9-fold, by at least 9.5-fold, by at least 10-fold, by at least 11-fold, by at least 12-fold, by at least 13-fold, by at least 14-fold, by at least 15-fold, by at least 16-fold, by at least 17-fold, by at least 18-fold, by at least 19-fold, by at least 20-fold, or by a greater amount, compared to the method steps performed without the preamplification step (or multiple pre-amplification steps). In some embodiments, the set of preamplification cycles comprises at least 10 cycles. In some embodiments, the set of pre-amplification cycles comprises at least 12 cycles. In some embodiments, the set of pre-amplification cycles comprising at least 12 cycles improves the counts of the rare target component by at least 20-fold.

[0183] A cycle can include denaturation phases, annealing phases, extension phases, and storage phases. Temperatures associated with thermocycling can range from 8 °C to 98 °C, or other temperature ranges. Pre-amplification can be performed with isothermal amplification or other amplification techniques. In some embodiments, the isothermal amplification comprises loop-mediated isothermal amplification (LAMP).

[0184] Post-purification in Step S230, the sample can be diluted, prior to subsequent amplification and detection steps described below. Dilution can be performed on a pre-amplified and / or purified sample, with a dilution factor of 1: 2, 1:3, 1:4, 1:5, 1:6, 1:7, 1:8, 1:9, 1:10, 1:15, 1:20, 1:25, 1:30, 1:35, 1:40, 1:45, 1:50, 1:55, 1:60, 1:65, 1:70, 1:75, 1:80, 1:85, 1:90, 1:95, 1:100, 1:200, 1:300, 1:400, 1:500, 1:600, 1:700, 1:800, 1:900, 1:1,000, 1:1,500, 1:2,000, 1:2,500, 1:3,000, 1:3,500, 1:4,000,1:4,500, 1:5,000, 1:5,500, 1:6,000, 1:6,500, 1:7,000, 1:7,500, 1:8,000, 1:8,500, 1:9,000, 1:9,500, 1: 10,000, or dilution factors intermediate to those described, or another dilution factor. However, variations of the method 200 can omit dilution of the pre-amplified sample.

[0185] After Step(s) S220 / S230, the result sample can then be combined with process materials as described in relation to step S240 below.

[0186] In a specific example of Steps S220 and S230, individual samples were processed with a workflow that did not involve pre-amplification (as shown in FIG. 3A), and with the preamplification workflow (as shown in FIG. 3B) for direct comparison of performance. To enhance the sensitivity of the assay, the pre-amplification method was performed prior to analysis according to methods described. Samples were processed using both pre-amplified and non-pre-amplified workflows to directly compare their performance on the platform. For evaluation, approximately 80 ng (12,100 Genome Equivalents (GE)) of genomic DNA (gDNA) from GM12878 cells was used. This gDNA was spiked with synthetic JAK2 V617F target to create samples with 10-fold decreases in Variant Allele Frequency (VAF), represented as sample dilutions DI, D2, D3, and D4. GM12878 gDNA alone was used to represent 0% VAF (WT only), serving as the negative control.Quantification was performed on data generated from light sheet scanning of samples in individual containers. Evaluation of the two workflows was conducted using ~80 ng (i.e., 12,100 Genome Equivalents (GE)) of genomic DNA from the GM12878 cell line spiked with synthetic JAK2 V617F target to generate samples with 10-fold decreases in Variant Allele Frequency (VAF) represented by samples DI, D2, D3, D4 in FIG. 3D. GM12878 genomic DNA alone was used to represent the 0% VAF sample (WT, in FIG. 3D).

[0187] In the specific example of generating a pre-amplified and purified sample according to Steps S220 and S230, 12 cycles of pre-amplification were used. For pre-amplification and purification in bulk, a 2X master mix (Q5® High-Fidelity 2X Master Mix, New England Biolabs) was combined with nuclease free water and a forward and reverse primer mix, along with a nucleic acid cleanup kit (New England Biolabs). For pre-amplification and purification of samples in emulsion format according to a variation of Steps S220 and S230, an a la carte master mix (e.g., nuclease free water, histodenz, 20x PCR buffer, dNTPs, and a forward and reverse primer mix) with 0.5 pL added 2X master mix (Q5® High-Fidelity 2X Master Mix, New England Biolabs) was used for each sample, followed by SPRI clean up to preserve %minor allele frequency (% MAF). A range of % MAF conditions were tested, with replicate samples, such that samples DI through D4 had expected mutated target counts per microliter of 2000, 200, 20, and 2 counts, respectively, and wild typecounts were expected to be 20,000 counts per microliter. 40 microliters of each prepared sample were used. Thermocycling cycles in the specific example were performed according to Table 1 below.

[0188] In the specific examples, pre-amplified and purified samples were then subjected to a 1-step dilution (1:20 dilution factor) to ensure that the counting range was within the specifications of the exemplary platform, and I microliter of the diluted, pre-amplified, and purified samples was processed, with mastermix, according to embodiments, variations, and examples of subsequent steps S240, S250, and S260, described in more detail herein.2.3. Method - Sample Partitioning with Assay Materials and Compositions2.3.1. Method - Assay Materials and Compositions for Competitive Target-Specific Assays

[0189] Step S140 recites: distributing the fragmented sample across the set of partitions, wherein each partition of the set of partitions comprises a portion of the fragmented sample and processing materials S140, which functions to tag and amplify the target component of the sample, after performance of fragmenting steps described herein. In some embodiments, each partition of the set of partitions comprises at most one target of the target component of the sample. Step S240 recites: distributing the purified sample across the set of partitions, wherein each partition of the set of partitions comprises a portion of the purified sample and processing materials S240, which functions to tag and amplify the rare target component of the sample, after performance of pre-amplificationsteps described herein. In some embodiments, each partition of the set of partitions comprises at most one rare target of the rare target component of the sample. The set of processing materials described here in Section 2.3.1 can include fewer components (e.g., forward and reverse primers, single primers with tandem adapters, using shared probes / quencher oligonucleotides for primers targeting different targets, etc.) to provide detection of multiple targets in parallel. For instance, for a set of colors / wavelengths used for detection and digital quantitation of multiple targets based on color combinatorics, the set of processing materials may include one probe for each of the set of colors / wavelengths, rather than one probe per target of interest. As such, probes can be designed against a common PCR adapter tagged to forward and / or reverse primers of the set of processing materials, where the number of probes used has a number corresponding to the number of channels for detection, rather than the number of targets, thereby significantly reducing assay cost. As such, the set of processing materials implements chemistry for differential discrimination of partition contents based on color combinatorics, where color combinatorics of a set of color combinatorics may be paired with targets of a set of targets of interest, and where the set of targets has a total number greater than the number of color channels used to detect colors corresponding to the set of color combinatorics.

[0190] In embodiments, as shown in FIG. 2C, the set of processing materials can include: a) for each of the set of targets, a set of target-specific (e.g., allele-specific) forward primers corresponding to different variations of a respective target of the set of targets, and a common reverse primer for the set of target-specific (e.g., allele-specific) forward primers, and b) a master mixture including amplification reagent as well as: for each of the set of targets, a set of target-specific (e.g., allelespecific) flanking sequences corresponding to different targets of the set of targets.

[0191] A specific example of processing materials, including primers and probes, is shown in FIG.2D, for detection of repetitive sequences characteristic of T. cruzi. In more detail, a multiplexed assay was developed for targeting the repetitive microsatellite and kinetoplast (kDNA) regions of T. cruzi, as well as a synthetic DNA spike-in internal amplification control (IAC) to confirm assay amplification efficiency. A separate label was used for each of the microsatellite region, the kinetoplast (kDNA) region, and the IAC. Variations of the assay design can use other labels, and / or target other regions, with other control sequences.

[0192] Another specific example of processing materials, including primers and probes, is shown in FIG. 3C, for the JAK2 mutation example described herein.

[0193] Concentrations of forward primers can range from 50 nM to 300 nM in solution, or alternatively, less than 50 nM or greater than 300 nM in solution. Concentrations of reverse primers can range from 100 nM to 600 nM in solution, or alternatively, less than 100 nM or greater than 600 nM in solution. Concentrations of reporter oligonucleotides (e.g., fluorescent reporter oligonucleotides) can range from 30 nM to 200 nM in solution, or alternatively, less than 30 nM or greater than 200 nM in solution. Concentrations of quencher oligonucleotides can range from 100 nM to 600 nM in solution, or alternatively, less than 100 nM or greater than 600 nM in solution.

[0194] Primers (e.g., forward primers, reverse primers) can have lengths of 10 base pairs, 11 base pairs, 12 base pairs, 13 base pairs, 14 base pairs, 15 base pairs, 16 base pairs, 17 base pairs, 18 base pairs, 19 base pairs 20 base pairs, 21 base pairs, 22 base pairs, 23 base pairs, 24 base pairs, 25 base pairs, 26 base pairs, 27 base pairs, 28 base pairs, 29 base pairs, 30 base pairs, 35 base pairs, 40 base pairs, 45 base pairs, 50 base pairs, an intermediate number of base pairs, or a greater number of base pairs. In variations, primers can incorporate sequence regions corresponding to probes and target sequences (e.g., a 20 base pair target sequence, a target sequence having another suitable length, etc.), and be designed for various levels of plexy (e.g., 1-plex conditions, 2-plex conditions, 3-plex conditions, 4-plex conditions, 5-plex conditions, 6-plex conditions, 7-plex conditions, etc.) as described herein. In variations, forward primers can be longer than reverse primers, and in specific examples, use of forward primers having lengths 5-10 base pairs longer (e.g., than reverse primers, than another reference length) produced higher counts (e.g., 8-10% higher counts) and higher SNR values (e.g., 12-17% higher SNR values) in relation to shorter primer lengths, when detecting of targets from partitions, thereby providing higher detection performance.

[0195] Primers (e.g., forward primers, reverse primers) can have annealing temperatures from 48 °C-65 °C or another suitable annealing temperature range based upon reactions performed according to various assays. Primers (e.g., forward primers, reverse primers) can have melting temperatures from 65 °C to 70 °C (e.g., from 67 °C to 68.8 °C) or another suitable melting temperature range based upon reactions performed according to various assays.

[0196] Characteristics of forward and reverse primers described herein can be reversed (e.g., the set of processing materials can include a forward primer and a set of target-specific reverse primers). Still alternatively, both forward and reverse primers can be target-specific.

[0197] In some embodiments of the systems, methods, compositions, and kits disclosed herein, the set of processing materials comprises, for a target of the set of targets: a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured tointeract with a target region of the target, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified. In some embodiments, the set of processing materials comprises, for a first target and a second target of the set of targets: a primer set comprising: at least one primer configured to tag the first target with a first probe having a first fluorophore and the second target with a second probe having a second fluorophore.

[0198] In some embodiments, the processing materials comprise, for a rare target component, a primer set comprising: a common primer and a set of target- specific primers comprising a targetspecific primer configured to interact with a target region of the rare target component, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified. In some embodiments, the processing materials further comprise, for a background component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the background component, and a second fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the second fluorophore-labeled oligonucleotide comprising a second fluorophore configured to transmit a second target signal if the target region is amplified.

[0199] In some embodiments, the processing materials comprise, for a rare target component, a primer set comprising: a common primer and a set of target- specific primers comprising a targetspecific primer configured to interact with a target region of the rare target component, the targetspecific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. In some embodiments, the processing materials further comprise, for a background component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the background component, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 16. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 17. Insome embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 18. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 19.

[0200] In some embodiments, the processing materials comprise, for a rare target component and a background component, a primer set comprising at least one primer configured to tag the rare target component with a first probe having a first fluorophore and the background component with a second probe having a second fluorophore.

[0201] In some embodiments (e.g., wherein the rare target component comprises a mutation in a JAK.2 gene), the processing materials comprise a primer comprising a nucleotide sequence of SEQ ID NO: 14. In some embodiments, the processing materials comprise a primer comprising a nucleotide sequence of SEQ ID NO: 15.

[0202] In variations wherein a target component comprises one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, the processing materials can comprise, for a first shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target- specific primers comprising a target-specific primer configured to interact with a target region of the first shorter nucleotide sequence, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified. In some embodiments, the processing materials further comprise, for a second shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the second shorter nucleotide sequence, and a second fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the second fluorophore-labeled oligonucleotide comprising a second fluorophore configured to transmit a second target signal if the target region is amplified.

[0203] In some embodiments, the processing materials comprise, for a first shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the first shorter nucleotide sequence, the target-specific primer having a common adapter sequence, and afluorophore- labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. In some embodiments, the processing materials further comprise, for a second shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the second shorter nucleotide sequence, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 16. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 17. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 18. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 19.

[0204] In some embodiments, the processing materials comprise, for a first shorter nucleotide sequence and a second shorter nucleotide sequence of the at least two shorter nucleotide sequences that are repetitive sequences characteristic of the target component, a primer set comprising at least one primer configured to tag the first shorter nucleotide sequence with a first probe having a first fluorophore and the second shorter nucleotide sequence with a second probe having a second fluorophore.

[0205] In some embodiments (e.g., wherein the target component comprises one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component), the processing materials comprise a primer comprising a nucleotide sequence of SEQ ID NO: 1. In some embodiments, the processing materials comprise a primer comprising a nucleotide sequence of SEQ ID NO: 2. In some embodiments, the processing materials comprise a primer comprising a nucleotide sequence of SEQ ID NO: 5. In some embodiments, the processing materials comprise a primer comprising a nucleotide sequence of SEQ ID NO: 6. In some embodiments, the processing materials comprise a probe comprising a nucleotide sequence of SEQ ID NO: 3. In some embodiments, the processing materials comprise a probe comprising a nucleotide sequence of SEQ ID NO: 7. In some embodiments, the processing materials comprise a probe additive comprising a nucleotide sequence of SEQ ID NO: 4. In some embodiments, the processing materials comprise a probe additive comprising a nucleotide sequence of SEQ ID NO: 8.

[0206] In some embodiments, the sample further comprises a background component, and the processing materials further comprise a primer set comprising at least one primer configured to tag the background component with a third probe having a third fluorophore. In some embodiments, the background component comprises an amplification control comprising a nucleotide sequence of SEQ ID NO: 13. In some embodiments, the processing materials comprise a primer comprising a nucleotide sequence of SEQ ID NO: 9. In some embodiments, the processing materials comprise a primer comprising a nucleotide sequence of SEQ ID NO: 10. In some embodiments, the processing materials comprise a probe comprising a nucleotide sequence of SEQ ID NO: 11. In some embodiments, the processing materials comprise a probe additive comprising a nucleotide sequence of SEQ ID NO: 12.

[0207] In some embodiments of the systems, methods, compositions, and kits disclosed herein, the first fluorophore is a photo-bleachable fluorophore, and wherein detecting signals from the set of partitions comprises scanning the set of partitions with a first wavelength range of light and a second wavelength range of light configured to bleach the first fluorophore, the method further comprising: detecting signals from the set of partitions in a first phase of analysis upon scanning the set of partitions with the first wavelength range of light, and detecting signals from the set of partitions in a second phase of analysis upon scanning the set of partitions and bleaching the first fluorophore with the second wavelength range of light, thereby enabling differential detection of the first target and the second target.

[0208] As noted briefly herein and shown in FIG. 2C, in embodiments, the master mixture can include amplification reagents and, for each of the set of targets, a set of target-specific flanking sequences corresponding to different targets of the set of targets, in order to support multiplexed processing, detection, and digital quantitation. As such, in one variation, the set of processing materials can include, for a target of the set of targets: a primer set comprising: a common primer and a set of target-specific primers configured to interact with a target region of the target, the set of target-specific primers comprising a first target-specific primer comprising a first flanking sequence, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore- labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified.

[0209] For tagging a target with probes configured to emit multiple colors (where tandem probes are described in more detail herein), the set of target-specific primers can further include a second target-specific primer comprising a second flanking sequence, and the set of processing materialsfurther comprises a second fluorophore-labeled oligonucleotide corresponding to the second flanking sequence, the second fluorophore-labeled oligonucleotide comprising a second fluorophore configured to transmit a second target signal if the target region is amplified, such that the target can be positively detected based upon the first target signal and the second target signal. Alternatively, a single primer can be used to tag the target, along with tandem adapters corresponding to the probes used to tag the targets. As such, the set of processing materials can include at least one primer configured to tag the target with a first probe having a first fluorophore and a second probe having a second fluorophore (and / or additional probes with additional fluorophores), wherein the first fluorophore and the second fluorophore (and optional additional fluorophores) correspond to two (or more) color channels of the number of color channels.10210] The master mixture can include a probe including a dye / fluorophore with complementary quencher for each target, a polymerase (e.g., Taq polymerase), dNTPs, and buffer components.

[0211] With respect to tagging implemented using the forward primers, and corresponding dyes / fluorophore families of probes, dyes / fluorophores can be associated with chemical families including: acridine derivatives, arylmethine derivatives, fluorescein derivatives, anthracene derivatives, tetrapyrrole derivatives, xanthene derivatives, oxazine derivatives, dipyrromethene derivatives, cyanine derivatives, squarame derivates, squaraine rotaxane derivatives, naphthalene derivatives, coumarin derivatives, oxadiazole derivatives, pyrene derivatives, and / or other chemicals. Such fluorophores can further be attached to other functional groups for tagging of targets in a detectable manner.

[0212] In examples, dyes (e.g., for tagging of RNAs, DNAs, oligonucleotides, etc.) can include one or more of: FAM, (e.g., 6-FAM), Cy3TM, Cy5TM, Cy5.5TM, TAMRATM (e.g., 5-TAMRA, 6-TAMRA, etc.), MAX, JOE, TETTM, ROX, TYETM (e.g., TYE 563, TYE 665, TYE 705, etc.), Yakima Yellow ®, HEX, TEX (e.g., TEX 615), SUN, ATTOTM (e.g., ATTO 488, ATTO 490LS, ATTO 532, ATTO 550, ATTO 565, ATTO RholOl, ATTO 590, ATTO 633, ATTO 647, ATTO 647N, etc.), Alexa Fluor ® (e.g., Alexa Fluor 488, Alexa Fluor 532, Alexa Fluor 546, Alexa Fluor 594, Alexa Fluor 647, Alexa Fluor 660, Alexa Fluor 750, etc.), IRDyes® (e.g., 5’IRDye 700, 5’lRDye 800, 5’IRDye 800CW, etc.), Rhodamine (e.g., Rhodamine Green, Rhodamine Red, Texas Red ®, Lightcycler ®, Dy 482XL, Dy 508XL, Dy 526XL, Dy 750, Hoechst dyes, DAP! dyes, SYTOX dyes, chromomycin dyes, mithramycm dyes, YOYO dyes, ethidium bromide dyes, acridine orange dyes, TOTO dyes, thiazole dyes, CyTR / XK dyes, propidium iodide dyes, LDS dyes, BODIPY dyes, and / or other dyes. In some embodiments of the systems, methods, compositions, and kitsdisclosed herein, the dyes used are selected from: Alexa Fluor 488, Alexa Fluor 594, ATTO 490LS, ATTO 532, ATTO 647N, Cy5TM, FAM, Dy 482XL, Dy 508XL, Dy 526XL, and combinations thereof.

[0213] In examples, cell function dyes for tagging of target material and detection can include one or more of: DCFH, DUR, SNARF, indo-1, Fluo-3, Fluo-4, and / or other dyes. In some embodiments, the method for tagging of target material and detection includes at least 1 dye, at least 2 dyes, at least 3 dyes, at least 4 dyes, at least 5 dyes, at least 6 dyes, at least 7 dyes, at least 8 dyes, at least 9 dyes, or at least 10 dyes.

[0214] In examples, fluorescent proteins for tagging of target material and detection can include one or more of: cerulean, mCFP, mTurquoise, T-Sapphire, CyPet, ECFP, CFP, EBFP, Azurite, and / or other fluorescent proteins.

[0215] Dyes / fluorophores implemented can correspond to wavelength ranges in the visible spectrum and / or non-visible spectrum of electromagnetic radiation. Furthermore, dyes / fluorophores implemented can be configured to prevent overlapping wavelengths (e.g., of emission) and / or signal bleed through with respect to multiplexed detection and achieving high SNR values involving detection of signals from packed partitions. In variations, the set of processing materials can include components for 7 wavelength ranges for multiplexed detection of targets; however, the set of processing materials can include components for less than 7 wavelength ranges (e.g., one wavelength, two wavelengths, three wavelengths, four wavelengths, five wavelengths) or more than 7 wavelength ranges.

[0216] Quencher oligonucleotides implemented can include a quencher molecule configured such that, when the quencher oligonucleotide anneals with a primer having a fluorophore, the quencher molecule is in proximity to (e.g., directly opposite) the fluorophore in order to quench the fluorophore. Additionally or alternatively, quenchers can include one or more of: black hole quenchers, static quenchers, self-quenchers (e.g., fluorophores that self-quench under certain conditions by producing secondary structures or other structures), and / or other suitable quenchers. Variations of positions of quenchers (e.g., when tandem probes may be involved) are described in more detail herein.

[0217] The set of processing materials of Steps S140 and S240 can additionally or alternatively include implementation of components configured to improve signal -to-noise ratio (SNR) characteristics in the context of multiplexed detection, by increasing signal characteristics and / or reducing background (e.g., noise other artifacts). The components can include one additive for eachwavelength range / color for detection (as opposed to one additive for each target / SNP being evaluated). Additionally or alternatively, the additives can have from 5-20 bases or another suitable number of bases. Additionally or alternatively, modified nucleic acids (e.g., such as locked nucleic acids (LNA) or other modified nucleic acids) can be incorporated into forward and / or reverse primers of the set of processing materials to improve SNR. In variations, LNA content can occupy a percentage (e.g., 10-60% LNA content) of the respective primer to improve SNR, where LNA content can be biased toward the 3’ end, the 5’ end, or intermediate the 3’ and 5’ ends.

[0218] However, the set of processing materials can additionally or alternatively include other suitable components and / or be configured in another suitable manner.

[0219] Furthermore, with respect to different wavelength ranges, different targets can be tagged with dye / fluorophore colors in a manner that promotes discrimination of results (e.g., without overlap) upon detection of signals from processed sample material. Furthermore, different targets can be matched with different combinations of colors / associated wavelengths m order to provide distinction upon detection of signals from processed sample materials. Variations and examples of multiplexing based upon color combinatorics and other features are provided in U. S. Application 18 / 583,701, which is herein incorporated in its entirety by this reference.2.4. Method - Partitioning of Sample with Processing Materials

[0220] Distributing the sample combined with the set of processing materials, across a set of partitions in steps S140 and S240 can include receiving a sample (variations and examples of which may be described herein) at a vessel passively or actively (e.g., with applied force, such as with gravitational force, with centrifugal force, with pressurization, etc,). The sample and processing materials can be delivered manually (e.g,, with a fluid aspiration and delivery device, such as a pipettor). The sample and processing materials can additionally or alternatively be delivered with automation (e.g., using liquid handling apparatus or other sample handling apparatus).

[0221] In variations, vessel formats can include tubes (e.g., PCR tubes) containing partitions of the sample (e.g., in partition network format, in permeable partition network format, in gel-format, in emulsion format, in another format), wells (e.g., microwells, nanowells, etc.), channels, chambers, and / or other suitable containers. Additionally or alternatively, alternative variations of steps S140 and S240 can include receiving the sample at other suitable substrates (e.g., slides, plates, etc.) functionalized with material components configured to interact with target material of the sample.For instance, sample material can be spotted onto substrates with material components configured to interact with target material of the sample and in a detectable manner.

[0222] Embodiments, variations, and examples of the methods described herein can be implemented by or by way of embodiments, variations, and examples of components of system 400 shown in FIG.4, with a first substrate 410 defining a set of reservoirs 414 (for carrying sample / mixtures for droplet generation), each having a reservoir inlet 415 and a reservoir outlet 416; one or more membranes (or alternatively, droplet-generating substrates) 420 positioned adjacent to reservoir outlets of the set of reservoirs 414, each of the one or more membranes 420 including a distribution of holes 425; and optionally, a sealing body 430 positioned adjacent to the one or more membranes 420 and including a set of openings 435 aligned with the set of reservoirs 414; and optionally, one or more fasteners (including fastener 440) configured to retain the first substrate 410, the one or more membranes 420, and optional sealing body 430 in position relative to a set of collecting containers 450. In variations, the system 400 can additionally include a second substrate 460, wherein the one or more membranes 420 and optionally, the sealing body 430, may be retained in position between the first substrate 410 and the second substrate 460 by the one or more fasteners. In using embodiments, variations, and examples of the system 400, material derived from each sample is retained in its own tube and may not comprise batching and pooling, allowing for scalable batch size.

[0223] In variations, the distribution of holes 425 can be generated in bulk material with specified hole diameter(s), hole depth(s) (e.g., in relation to membrane thickness), aspect ratio(s), hole density', and hole orientation, where, in combination with fluid parameters, the structure of the membrane can achieve desired flow' rate characteristics, with reduced or eliminated polydispersity and merging, suitable stresses (e.g., shear stresses) that do not compromise the single cells but allow for partitioning of the single cells, and steady formation of droplets (e.g., without jetting of fluid from holes of the membrane),

[0224] In variations, the hole diameter can range from 0,02 micrometers to 30 micrometers, and in examples, the holes can have an average hole diameter of 0.02 micrometers, 0.04 micrometers, 0.06 micrometers, 0.08 micrometers, 0.1 micrometers, 0.5 micrometers, 1 micrometers, 2 micrometers, 3 micrometers, 4 micrometers, 5 micrometers, 6 micrometers, 7 micrometers, 8 micrometers, 9 micrometers, 10 micrometers, 20 micrometers, 30 micrometers, any intermediate value, or greater than 30 micrometers (e.g., with use of membrane having a thickness greater than or otherwise contributing to a hole depth greater than 100 micrometers).

[0225] In variations, the hole depth can range from 1 micrometer to 200 micrometers (e.g., in relation to thickness of the membrane layer) or greater, and in examples the hole depth (e.g., as governed by membrane thickness) can be 1 micrometers, 5 micrometers, 10 micrometers, 20 micrometers, 30 micrometers, 40 micrometers, 50 micrometers, 60 micrometers, 70 micrometers, 80 micrometers, 90 micrometers, 100 micrometers, 125 micrometers, 150 micrometers, 175 micrometers, 200 micrometers, or any intermediate value.

[0226] In variations, the hole aspect ratio can range from 5: 1 to 200: 1, and in examples, the hole aspect ratio can be 5:1, 10:1, 20:1, 30:1, 40:1, 50:1, 60:1, 70:1, 80:1, 90:1, 100:1, 125:1, 150:1, 175:1, 200:1, or any intermediate value.

[0227] In variations, the hole-to-hole spacing can range from 5 micrometers to 200 micrometers or greater, and in examples, the hole-to-hole spacing is 5 micrometers, 10 micrometers, 20 micrometers, 30 micrometers, 40 micrometers, 50 micrometers, 60 micrometers, 70 micrometers, 80 micrometers, 90 micrometers, 100 micrometers, 125 micrometers, 150 micrometers, 175 micrometers, 200 micrometers, or greater. In a specific example, the hole-to-hole spacing is greater than 10 micrometers.

[0228] In examples, the hole orientation can be substantially vertical (e.g., during use in relation to a predominant gravitational force), otherwise aligned with a direction of applied force through the distribution of holes, or at another suitable angle relative to a reference plane of the membrane or other droplet generating substrate 420.

[0229] Additionally or alternatively, embodiments, variations, and examples of the methods described herein can be implemented by or by way of embodiments, variations, and examples of components described m U. S. Application No. 17 / 687,080 filed 04-MAR-2022, U. S, Patent No. 11,242,558 granted 08-FEB-2022, U. S. Application No. 16 / 309,093 filed 25-MA Y-2017, and PCT Application PCT / CN2019 / 093241 filed 27-JUN-2019, each of which is herein incorporated in its entirety by reference. However, methods described herein can additionally or alternatively implement other system elements for sample reception and processing.2.5. Method - Target-Specific Tagging and Amplification

[0230] Step SI 50 recites: reacting the processing materials of each partition of the set of partitions with the portion of the fragmented sample, thereby driving the target component of the sample to a level of detection of a detection system configured to scan the single closed container and count a set of positive partitions of the set of partitions, wherein a positive partition of the set of positivepartitions emits a signal associated with the target component. In Step SI 50, reacting the processing materials of each partition of the set of partitions with the portion of the fragmented sample can include performing a single reaction within the set of partitions within the single closed container, without dividing the fragmented sample across more than one container.

[0231] Step S250 recites: reacting the processing materials of each partition of the set of partitions with the portion of the purified sample, thereby driving the rare target component of the sample to a level of detection of a detection system configured to scan the single closed container and count a set of positive partitions of the set of partitions, wherein a positive partition of the set of positive partitions emits a signal associated with the rare target component. In Step S250, reacting the processing materials of each partition of the set of partitions with the portion of the purified sample can include performing a single reaction within the set of partitions within the single closed container, without dividing the purified sample across more than one container.

[0232] A first reaction stage can include denaturing of sample material (e.g., loci of interest associated with the rare molecule component) and processing the denatured sample material with primers (i.e., target-specific forward primers grouped with corresponding reverse primers for each target). In the first stage, one of the target-specific forward primers of the set of sample processing materials matches the target (e.g., target molecule component, fragmented target molecule component, repetitive segment component, microsatellite component, rare molecule component, etc.) and, with the common reverse primer, amplifies the target region. As such, targets present in the sample may be amplified upon interacting with respective target-specific forward primers. Then, a second reaction stage can include generation of target-specific sequences (e.g,, tail sequences), where the common reverse primer binds to, elongates, and produces a complimentary copy of a labeled target sequence. Then, a third reaction stage and subsequent stages can include one or more rounds of amplification / PCR to produce a detectable signal, whereby l evels of tagged target-specific sequences increase until a detection threshold is reached and / or surpassed. In the third reaction stage and subsequent stages, labeled oligonucleotides bind to new complementary sequences (e.g., tail sequences), releasing fluorophores from corresponding quenchers to produce detectable signals for each target present, across the distribution of partitions. However, fluorophores corresponding to targets that may not be present may not be released and thus continue to be quenched during rounds of amplification. In particular, with regard to parameters associated with threshold cycles at which or beyond which amplified targets become detectable (e.g., Ct, Cp, Cq, etc.), the third reaction stages can include detecting and / or returning results indicative of target presence prior to the end-point ofthe process and / or at the end-point of the process (e.g., as in end-point PCR). Additionally or alternatively, real-time measurement of signals can be performed contemporaneously with each cycle of amplification.

[0233] In relation to the one or more stages of sample processing, activation-associated steps can be performed at a temperature or temperature profile (e.g., 90 °C, 92 °C, 94 °C, 96 °C, 98 °C, another suitable temperature), for a duration of time (e.g., 10 minutes, 12 minutes, 15 minutes, another suitable duration of time), and / or for a number of cycles (e.g., 1 cycle, 2 cycles, another suitable number of cycles). In relation to the one or more stages of sample processing, denaturation-associated steps can be performed at a temperature (e.g., 90 °C, 92 °C, 94 °C, 96 °C, 98 °C, another suitable temperature) or temperature profile, for a duration of time (e.g., 10 seconds, 15 seconds, 20 seconds, 25 seconds, another suitable duration of time), and / or for a number of cycles (e.g., 1 cycle, 5 cycles, 10 cycles, 20 cycles, 30 cycles, 40 cycles, 45 cycles, another suitable number of cycles). In relation to the one or more stages of sample processing, annealmg / elongation-associated steps can be performed at a temperature or temperature profile (e.g., 52-70 °C with a ramp down rate, another suitable temperature profile), for a duration of time (e.g., 20 seconds, 30 seconds, 60 seconds, 90 seconds, another suitable duration of time), and / or for a number of cycles (e.g., 1 cycle, 5 cycles, 10 cycles, 20 cycles, 25 cycles, 30 cycles, 40 cycles, 45 cycles, another suitable number of cycles).

[0234] In a specific example, activation-associated steps m a first stage of sample processing can be performed at a temperature of 94 °C, for 15 minutes, with 1 cycle. In the specific example, denaturation-associated steps in a second stage of processing can be performed at 94 °C for 20 seconds, with annealing / elongation performed from 61-55 °C (with a drop of 0.6 °C / cycle), for 60 seconds and for 10 cycles. In the specific example, denaturation-associated steps in a third stage of processing can be performed at 94 °C for 20 seconds, with annealing / elongation performed at 55 °C for 60 seconds and for 26 cycles. Additional denaturation-associated steps can be performed at 94 °C for 20 seconds, with annealing / elongation performed at 57 °C for a suitable number of cycles (e.g,, 3 cycles).

[0235] In another specific example, activation-associated steps in a first stage of sample processing can be performed at a temperature of 94 °C, for 15 minutes, with 1 cycle. In the specific example, denaturation-associated steps in a second stage of processing can be performed at 94 °C for 20 seconds, with annealing / elongation performed from 65-57 °C (with a drop of 0.8 °C / cycle), for 60 seconds and for 10 cycles. In the specific example, denaturation-associated steps in a third stage of processing can be performed at 94 °C for 20 seconds, with annealing / elongation performed at 57 °Cfor 60 seconds and for 30 cycles. Additional denaturation-associated steps can be performed at 94 °C for 20 seconds, with annealing / elongation performed at 57 °C for a suitable number of cycles (e.g., 3 cycles).

[0236] Stages of reaction m Steps SI 50 and S250 can further include implementation of additives (described in Section 2 herein) to improve signal-to-noise ratio (SNR) characteristics in the context of multiplexed detection, by increasing signal characteristics and / or reducing background (e.g., noise other artifacts). Additionally or alternatively, stages of sample processing in Steps SI 50 and S250 can implement other components (e.g., density gradient mediums) to improve SNR.

[0237] In particular, in the context of emulsion digital PCR with the numbers of partitions described herein, such multiplexed assay design aspects described can produce significantly improved signal-to-noise (SNR) values with reduced background, in relation to detection techniques described herein (e.g., based on light sheet imaging, etc.). In examples, target signals can be at least 102greater than background noise signals, 103greater than background noise signals, 104greater than background noise signals, 105greater than background noise signals, 106greater than background noise signals, 107greater than background noise signals, or better. Background noise can be attributed to fluorescence from adjacent partitions and adjacent planes of the set of planes of partitions in the context of emulsion digital PCR, or attributed to other sources with closely-positioned partitions. Determining the SNR can include scanning a set of planes of the set of partitions, determining a target signal value and a noise signal value for the set of planes, and determining the SNR from the target signal value and the noise signal value, where a variation of determining the target signal value and the noise signal value is described herein,

[0238] In examples associated with reaction materials described herein, determining the target signal value and a noise signal value can include: for each plane of a set of planes of partitions under interrogation (e.g., by light sheet detection, fluorescent microscopy, confocal microscopy, detection by photodiodes, by another method of detection, etc,): determining a categorization (of a set of categorizations for the respective plane) based upon a profile of signal-positive partitions represented in a respective plane, determining a target signal distribution and a noise signal distribution specific to the profile. Here, a target signal value can be determined from the target signal distribution, and can be an average value (or other representative value) of the target signal intensities determined from the set of planes. Similarly, a noise signal value can be determined from the noise signal distribution, and the background noise signal value can be an average value (or other representative value) of the noise signal intensities determined from the set of planes.

[0239] However, materials used for the amplification and / or detection reactions can be otherwise configured to improve SNR.

[0240] In relation to driving the target component and / or rare target component of the sample to a level of detection of a detection system configured to scan the single closed container and count a set of positive partitions of the set of partitions, the detection system can include a light sheet scanner configured to interrogate (e.g., illuminate and receive signals from) cross sectional planes of contents of the single closed container. As such, detecting the set of positive partitions can include scanning the single closed container with a light sheet scanner and generating a set of images of cross sections of contents of the single closed container. Aspects of detection and counting of molecule and / or rare molecule components of a sample (e.g., in relation to detection thresholds at the lower range of a detection system) are described in Section 2.6 herein.2.6. Method - Signal Detection

[0241] Steps SI 60 and S260 recite: detecting the set of positive partitions upon scanning the single closed container. In relation to detecting the set of positive partitions, a computing system comprising instructions stored in non-transitory media can be used to generate characterizations of the sample, based upon detection and analysis of positive partitions. The computing system, with the detection system, can be configured to perform fast, and precise counting across a wide dynamic range (e.g., a dynamic range of 7 logarithms, a dynamic range of 6 logarithms, a dynamic range of 5 logarithms, a dynamic range of 4 logarithms, etc.). In relation to accurate, fast, and precise counting across the entire dynamic range, if the number of targets of the sample is within a first range, generating the count can include performing a first set of steps, if the number of targets of the sample is within a second range, generating the count comprises performing a second set of steps different than the first set of steps, and if the number of targets of the sample is within a third range, generating the count comprises generating a third set of steps different than the first set of steps and the second set of steps. The first range can be a range from a lower order of magnitude of 1 molecule to a higher order of magnitude of IO2or 103molecules. An exemplary low count range can be a range of 1 to 1000 targets. The second range can be a range from a lower order of magnitude of IO2molecules to a higher order of magnitude of 105molecules. The third range can be a range from a lower order of magnitude of 105molecules to a higher order of magnitude of 10° molecules or greater. The ranges can thus overlap or may alternatively not overlap. For instance, counts that fall within overlapping ranges of subportions of the dynamic range can be assessed using different setsof operations, and the higher quality count (e.g., in relation to confidence, in relation to accuracy, in relation to another quality metric) can be returned for characterization of the sample.

[0242] Methods described herein cover pre- amplification of a sample including a rare molecule component, such that it is detectable using a first range (e.g., lower order of magnitude range) of a detection system. Variations of methods described herein also cover pre-amplification of a sample including a rare molecule component such that it is detectable using a second range (e.g., medium order of magnitude range) and / or a third range (e.g., high order of magnitude range, with involvement of subsampling) of a detection system, where counting in the second range may be more accurate than counting in other ranges. Alternatively, sample processing according to methods described herein can include combinations of pre-amplification, dilution steps, and / or purification steps, to drive a sample to be analyzed within a first range, second range, third range, and / or other suitable range of a detection system (e.g., depending upon sensitivity, accuracy, speed, and / or other performance metrics being optimized for in relation to generated analyses). In some embodiments, the methods provide at least a 6-log dynamic range that enables the simultaneous quantification of a rare target component and a background component. In some embodiments, the methods provide at least a 5-log dynamic range that enables the simultaneous quantification of a rare target component and a background component. In some embodiments, the methods provide at least a 4-log dynamic range that enables the simultaneous quantification of a rare target component and a background component. In some embodiments, the methods provide at least a 3 -log dynamic range that enables the simultaneous quantification of a rare target component and a background component. In some embodiments, the methods provide at least a 2-1 og dynamic range that enables the simultaneous quantification of a rare target component and a background component.

[0243] Methods described herein cover fragmentation of a sample including a target component comprising one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, such that the one or more shorter nucleotide sequences is detectable using a first range (e.g., lower order of magnitude range) of a detection system. Variations of methods described herein also cover fragmentation of a sample including a target component comprising one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component such that the one or more shorter nucleotide sequences is detectable using a second range (e.g., medium order of magnitude range) and / or a third range (e.g., high order of magnitude range, with involvement of subsampling) of a detection system, where counting in the second range may be more accurate than counting in other ranges. In some embodiments, the methods provide at least a 6-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component. In some embodiments, the methods provide at least a 5-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component. In some embodiments, the methods provide at least a 4-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component. In some embodiments, the methods provide at least a 3 -log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component. In some embodiments, the methods provide at least a 2-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of a target component.

[0244] Furthermore, variations of the methods can involve utilizing different counting approaches within other ranges of target numbers.

[0245] In relation to the level of detection of the detection system (e g., in relation to detection of the target component and / or rare target component at the lower limit of detection of the detection system), detection can include enumerating positive partitions of the set of partitions upon scanning a set of sheets of partitions within the single closed container using light sheet scanning, and enumerating positive partitions identified from the set of sheets. Relatedly, generating the count can include enumerating positive partitions of the set of partitions, wherein a partition of the set of partitions is identified as a positive partition based upon satisfaction of a set of criteria including: a signal intensity criterion, an optical property criterion, a shape criterion, a morphology criterion, a spatial criterion, a chromaticity criterion, and a combination thereof, from readout data acquired upon performing optical interrogation of the set of partitions, as described herein. In some embodiments, detecting the set of positive partitions and returning the analysis comprises enumerating the set of positive partitions, wherein a positive partition of the set of positive partitions is identified as positive based upon satisfaction of: a signal intensity criterion, an optical property criterion, a shape criterion, and a morphology criterion. Different criteria can thus reduce or eliminate false positives that could adversely affect counts, where false positives can be attributed to air bubbles, dust, edge fluorescence from damaged collecting containers, merged droplets, merged partitions, emulsion interface effects (e.g., due to presence of micelles, etc.), and / or other artifacts that could produce false positive counts. Different criteria can additionally or alternatively reduce oreliminate noise that could adversely affect counts, where noise can be atributed to reagents used (e.g., nuclease free water, Tris-EDTA buffer, oil phases, additives, imaging fluids, PCR master mix, etc.) according to methods described herein.

[0246] Signal Intensity Criterion: In variations, and with respect to a partition, the signal intensity criterion is evaluated for a set of pixels depicting the droplet, and the signal intensity criterion is based upon one or more of: a maximum signal intensity of the set of pixels, a maximum convoluted intensity of the set of pixels, a difference between the maximum intensity and the minimum intensity of the set of pixels, a total intensity of the set of pixels, a sum of signal intensities, a mean of signal intensities, a median of signal intensities, and another suitable representation of signal intensities.

[0247] Optical Property Criterion: In variations, and with respect to a partition, the optical property criterion is evaluated for a set of pixels depicting the partition, and the optical property criterion is based upon one or more of: a lateral intensity gradient across the set of pixels (across a direction of pixels in which a portion of the droplet / partition is depicted), an axial intensity gradient across the set of pixels (across a direction of pixels in which a portion of the partition is depicted), second order intensity gradients across the set of pixels along a set of directions (e.g., an axial direction and a lateral direction), and intensity uniformity across the set of pixels. Axial and lateral directions for a droplet / partition are shown in FIG. 5, with respect to a partition. In relation to the lateral intensity gradient criterion, pixels along a set of lateral directions, as shown in FIG. 5 (where lateral directions are shown as LI, L2,..., Ln), are processed to determine an average lateral intensity' gradient (e.g., in relation to partition radius).

[0248] Shape Criterion: In variations, and with respect to a partition, the shape criterion is evaluated for a set of pixels depicting the partition, and the shape criterion is based upon one or more of: a partition radius determined from the set of pixels prior to removing background pixels, a partition radius determined from the set of pixels after removing background pixels, a partition eccentricity determined from the set of pixels prior to removing background pixels, a partition eccentricity' determined from the set of pixels after removing background pixels, and a partition radius of gyration.

[0249] Morphology Criterion: In variations, and with respect to a partition, the morphology criterion is evaluated for a set of pixels depicting a three-dimensional profile of a representative positive partition determined from a set of control samples.

[0250] Chromaticity Criterion: In variations, and with respect to a partition, the chromaticity criterion covers combinations of color / label signals, evaluated for a set of pixels of a representativepositive partition determined from a set of control samples. In one example, if partitions with target molecules are in observed in a first channel, and a second reference channel, such partitions are filtered out as false positives.

[0251] Spatial Criterion: In variations, and with respect to a partition, the spatial criterion relates to location of droplets within space (e.g., within the container).

[0252] In relation to the set of pixels used to evaluate a droplet / partition with respect to different criteria described herein, the set of pixels can be acquired from image data corresponding to more than a single cross-section (e.g., multiple lightsheet image frames corresponding to multiple crosssections). Alternatively, the set of pixels can be acquired from image data corresponding to a single cross-section (e.g., lightsheet image frame for a single cross-section).

[0253] An example of a positive partition is shown in FIG. 6A, and examples of negative partition are shown in FIGS. 6B, 6C, and 6D. A stack of cross sectional images for each partition and / or a projection of multiple cross sectional images for each droplet onto a two-dimensional space can also be used for control and / or training data.

[0254] With respect to increasing specificity of positive droplet identification from readout data generated from lightsheet images, detection in Steps S 160 and S260 can include generating the count upon processing input data produced from the readout data, with a machine learning model. The machine learning model can be trained with a training dataset where the training dataset is generated from processing of a set of control samples that include positive partitions (e.g., partitions individually containing a single target) and negative partitions (e.g., partitions that do not contain a single target). Increasing specificity of positive partition identification produces high-confidence positive partition calling in rare-molecule samples (e.g., samples at lower order of magnitude ranges of the entire dynamic range).

[0255] The machine learning model can include classification model architecture, where the classification model architecture is trained with a supervised learning approach using labelled training data from control samples in order to allow the trained model to accurately identify positive partition based upon a set of features. Features of pixels and / or partitions (e.g., droplets) of training data can be used to train the classification model, and features of pixels and / or partitions of new-input test data (e.g., generated from subsequent scans of processed samples) can be used to generate counts of targets from such processed samples. As another approach, features can be learned from raw data instead of extracting known features, and / or features can be classified directly by feeding raw images (partition candidates + surrounding pixels) into training models.

[0256] Exemplary partition features applied by and / or used to train the classification model architecture can include one or more of: a partition intensity feature, a signal to noise ratio, an intensity uniformity feature (e.g., determined from an integrated total of partition pixel intensity divided by [partition area multiplied by partition intensity]), a first order intensity gradient in a polar / lateral direction (e.g., dl / dr), a second order intensity gradient in a polar / lateral direction (e.g., d2I / dr2), a first order intensity gradient in an axial direction (e.g., dl / dz), a second order intensity gradient in a polar direction (e.g., d2I / dz2), an integrated intensity (e.g., integrated intensity of all pixels representing a droplet), an eccentricity feature (e.g., eccentricity determined from a ratio of:[difference between a major partition diameter and a minor partition diameter]: [sum of a major partition diameter and a minor partition diameter]), a radius of gyration (e.g., determined from an square-root of integrated total of droplet radius squared multiplied by droplet pixel intensity, divided by integrated total droplet pixel intensity), and a partition correlation with a three-dimensional (3D) profile of a positive partition generated from a control sample. As such, a partition can be labeled as a positive partition (e.g., a partition originally containing a single target) based upon a set of features, and the classification model can be trained to accurately label a test droplet at partition based upon the set of features (shown in FIG. 7 A). An exemplary structure for training the classification model is shown in FIG. 7B.

[0257] In embodiments where there is spatial variation of droplet features associated with positive partitions and / or negative partitions at different positions within the closed collecting container, the classification model architecture can include subarchitecture for accurately labeling positive partitions based upon location (e.g., coordinates x, y, z) within the closed collecting container.Alternatively, in embodiments where there is spatial variation of droplet features associated with positive partitions and / or negative partitions at different positions within the closed collecting container, the classification model architecture can include subarchitecture for scaling features for determination of positive partitions, such that returning outputs of the classification model is based upon scaled feature values (e.g,, effectively normalizing features across different partition positions).

[0258] While embodiments, variations, and examples of machine learning models (e.g., in relation to inputs, outputs, and training) are described herein, models implemented for positive partition identification can additionally or alternatively include other architecture components. For instance, statistical analyses and / or machine learning model architecture can be characterized by a learning style including any one or more of: supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning (e.g., using a Q-learning algorithm, using temporaldifference learning, etc.), and any other suitable learning style. Furthermore, any machine learning algorithms can implement any one or more of: a classification algorithm (e.g., a decision tree learning method such as classification and regression tree, chi-squared approach, random forest approach, multivariate adaptive approach, gradient boosting machine approach, etc.), a regression algorithm, an instance-based method, a regularization method, a Bayesian method, a kernel-based approach (e.g., a support vector machine, a linear discriminate analysis, etc.), a clustering method (e.g., k-means clustering), an associated rule learning algorithm (e.g., an / Xpriori algorithm), an artificial neural network model, a deep learning algorithm, a self-attention model, a dimensionality reduction method (e.g., principal component analysis, partial least squares regression, etc.), an ensemble method, and any suitable form of algorithm. As such, detecting the set of positive partitions can include processing a set of images generated (e.g., from light sheet scanning, from confocal images, from other forms of scanning) with a machine learning model comprising architecture for identifying positive partitions of the set of positive partitions based upon evaluating each candidate partition against a signal intensity criterion, an optical property criterion, a shape criterion, a morphology criterion, a spatial criterion, a chromaticity criterion, or a combination thereof. In some embodiments, detecting the set of positive partitions includes processing a set of images generated with a machine learning model comprising architecture for identifying positive partitions of the set of positive partitions based upon evaluating each candidate partition against a signal intensity criterion, an optical property criterion, a shape criterion, and a morphology criterion.

[0259] Additional aspects and variations of detection methods are described in U. S. Application No, 18 / 583,701 filed on 21 -FEB-2024, which is herein incorporated in its entirety by this reference.2.7. Method - Returned Outputs

[0260] Step S I 70 recites: returning an analysis of the target component, which functions to provide metrics associated with presence, abundance, and / or other features of the target component in the sample. In variations, returning the analysis can include returning a count of the target component, accounting for pre-amplification, purification, and / or dilution factors associated with processing of the sample in order to drive it to the detection threshold of the detection system. In one example, returning the analysis can include returning a first abundance of the target component and a second abundance of the background component, and returning a relative abundance of the target component from the first abundance and the second abundance. In some embodiments, the methodprovides at least a 6-log dynamic range that enables the simultaneous quantification of at least two shorter nucleotide sequences that are repetitive sequences characteristic of the target component.

[0261] Step S270 recites: returning an analysis of the rare target component, which functions to provide metrics associated with presence, abundance, and / or other features of the rare target component in the sample. In variations, returning the analysis can include returning a count of the rare target component, accounting for pre-amplification, purification, and / or dilution factors associated with processing of the sample in order to drive it to the detection threshold of the detection system. In one example, returning the analysis can include returning a first abundance of the rare target component and a second abundance of the background component (e.g., wild type background component), and returning a relative abundance of the rare target component from the first abundance and the second abundance. In some embodiments, the method provides at least a 6-log dynamic range that enables the simultaneous quantification of the rare target component and the background component.

[0262] Returning the analysis can provide characterizations of the sample with respect to infectious disease-relevant characterizations and / or diagnoses. Exemplary infectious diseases can include diseases associated with parasitic infection, diseases associated with human immunodeficiency virus (HIV), diseases associated with coronaviruses, diseases associated with latent infections, sexually transmitted diseases (e.g., human papillomavirus (HPV)), diseases associated with parasites, diseases associated with bacteria, diseases associated with fungi, and / or other infectious diseases and / or infectious states (e.g., sepsis).

[0263] Returning the analysis can provide characterizations of the sample with respect to oncologyrelevant characterizations and / or diagnoses. In a specific example, the rare target component comprises a mutation in a JAK2 gene, and returning the analysis comprises characterizing a myeloproliferative neoplasm. In another specific example, the rare target component comprises a component associated with a circulating tumor cell type and / or circulating stem cell type. In another specific example, the rare target component comprises a rare molecule associated with detection of a cancer type associated with tissues described herein. In another specific example, the rare target component comprises a rare molecule associated with tumor-derived nucleic acids.

[0264] Returning the analysis can provide characterizations of the sample with respect to cell and gene therapy characterizations. In an example, returning the analysis can provide characterizations of the sample with respect to CAR T-cell therapy characterizations, in relation to cancer treatments that use a patient’s own T cells to fight cancer. / Analyses can indicate effectiveness of therapies, bydetection of rare targets associated with the CAR T-cell therapies applied to a patient from whom a sample is retrieved.

[0265] Returning the analysis can provide characterizations of the sample with respect to residual testing characterizations (e.g., minimal residual disease (MRD)).

[0266] Returning the analysis can provide characterizations of the sample with respect to forensic testing characterizations (e.g., by detection of rare / foreign nucleic acids in the field of forensics).

[0267] Returning the analysis can provide characterizations of the sample with respect to genetically-modified organism testing characterizations. Exemplary genetically-modified organisms can be used to generate samples for testing according to methods described herein, where samples can be obtained from crops, seeds, soils, leaves, roots, water, and / or other material.

[0268] Returning the analysis can provide characterizations of the sample with respect to detection of other targets and / or rare targets of a sample.

[0269] In relation to generating the analysis, processing, and analysis steps described herein can improve a limit of detection and / or lower a detection threshold for detection of the target component and / or rare target component by at least 1.5-fold, by at least 2-fold, by at least 2.5-fold, by at least 3-foid, by at least 3.5-fold, by at least 4-fold, by at least 4.5-fold, by at least 5-fold, by at least 5.5-fold, by at least 6-fold, by at least 6.5-fold, by at least 7-fold, by at least 7.5-fold, by at least 8-fold, by at least 8.5-fold, by at least 9-fold, by at least 9.5-fold, by at least 10-fold, by at least 11-fold, by at least 12-fold, by at least 13 -fold, by at least 14-fold, by at least 15 -fold, by at least 16-fold, by at least 17-fold, by at least 18-fold, by at least 19-fold, by at least 20-fold, or by a greater amount.

[0270] In some embodiments, the method lowers the detection threshold for the rare target component. In some embodiments, the method lowers the detection threshold for the rare target component. In some embodiments, the lowered detection threshold for the rare target component comprises a limit of detection (LoD) for detection of the rare target component decreased by at least 1.5-fold, by at least 2-fold, by at least 2.5-fold, by at least 3-fold, by at least 3.5-fold, by at least 4-fold, by at least 4,5-fold, by at least 5-fold, by at least 5.5-fold, by at least 6-fold, by at least 6.5-fold, by at least 7-fold, by at least 7.5-fold, by at least 8-fold, by at least 8.5-fold, by at least 9-fold, by at least 9.5 -fold, by at least 10-fold, by at least 11 -fold, by at least 12-fold, by at least 13 -fold, by at least 14-fold, by at least 15-fold, by at least 16-fold, by at least 17-fold, by at least 18-fold, by at least 19-fold, by at least 20-fold, or by a greater amount. In some embodiments, the lowered detection threshold for the rare target component comprises a limit of detection (LoD) for detection of the rare target component decreased by at least 1.5-fold. In some embodiments, the lowereddetection threshold for the rare target component comprises a limit of detection (LoD) for detection of the rare target component decreased by at least 2-fold. In some embodiments, the lowered detection threshold for the rare target component comprises a limit of detection (LoD) for detection of the rare target component decreased by at least 3-fold. In some embodiments, the lowered detection threshold for the rare target component comprises a limit of detection (LoD) for detection of the rare target component decreased by at least 4-fold.

[0271] In variations, the analysis provides a sensitivity for detection of the target component and / or rare target component, with a limit of blank (LoB) and / or a limit of detection (LoD) less than respective limiting amounts. The LoB is a sensitivity metric that represents the highest concentration of an analyte that is likely to be found in a blank sample, which contains no analyte. The LoD is a sensitivity metric that represents the lowest amount and / or concentration of a substance that can be reliably detected in a sample, with a certain level of certainty. In examples, the LoB achievable using the methods described herein is less than 0.006, 0.005, 0.004, 0.003, 0.002, 0.001, or lower (in relation to frequency percentages). In examples, the LoD achievable using the methods described herein is less than 50, less than 45, less than 40, less than 35, less than 30, less than 25, less than 20, less than 15, less than 10, less than 5, or lower (e.g., in relation to numbers of sequences detected, the number of target molecules, etc.). In examples, the LoD achievable using the methods described herein is less than 0.06, 0.05, 0.04, 0.03, 0.02, 0.01, 0.009, 0.008, 0.007, 0.006, 0.005, 0.004, 0.003, 0.002, 0.001, or lower. LoB and LoD values can be provided in relation to numbers of sequences detected, frequencies of sequences, or other features. LoB and LoD values can be provided in relation to variant allele frequency (VAF) percentage or other features,

[0272] In some embodiments, the method is characterized by a limit of detection of less than 20, less than 30, less than 40, less than 50, less than 60, less than 70, less than 80, less than 90, less than 100, or a lower number of molecules representing the target component and / or rare target component distributed across at least 30 million partitions. In some embodiments, the method is characterized by a limit of detection of less than 20 molecules representing the target component and / or rare target component distributed across at least 30 million partitions.

[0273] In some embodiments, the analysis provides a sensitivity for detection of the rare target component with a limit of blank (LoB) less than 0.005 and a limit of detection (LoD) less than 0.02 in relation to variant allele frequency (VAF) percentage.

[0274] In a specific example associated with the experiment design of FIG. 3C, the LoB in relation to variant allele frequency (VAF) percentage was 0.0035, and the LoD in relation to %V / XF was0.0151. In the example, the LoD decreases 2.4-fold when the pre-amplification protocol was used. The WT sample was used as the “blank“ and sample D4 was used as the “low concentration sampled The calculations used are LoB::::meanbiank+ 1.645(SDbiank); and LoD:::LOB +1.645(SDioWconoentrationSampie). Exemplary LoB and LoD results are provided in Table 2 below.

[0275] FIG, 3D depicts average rare target component molecule counts for the V617F and WT targets as well as their standard errors. The V617F counts are very' low for samples D3 and D4 in the no pre-amplification condition, leading to higher counting variance, reflected by the larger error bars. Samples that underwent pre-amplification show higher counts in both targets, while maintaining a low false positives rate as seen in the WT sample. In addition, lower counting variance for the V617F target is observed in pre-amplification samples. Using target-specific PCR increases the total number of molecules an assay can screen for the presence of a rare mutation. Copies of WT and V617F mutations increase at the same rate, nearly doubling with each PCR cycle. However, the level of background signal does not increase as rapidly because it is from non-specific, weak primer interactions. As a result, the occurrence of rare molecules (as copies of the originals) are boosted well above the noise level, leading to more accurate detection and thus smaller error bars because the total number of molecules to be checked is orders of magnitude greater. Table 3 below depicts exemplary results.n-

[0276] FIG. 3E depicts results of an analytical characterization of the JAK2 V617F assay across a titration of VAF%. The grey line represents the expected decrease in VAF across the samples. Each data point reflects the average VAF that was calculated from the UltraPCR molecule counts and the standard errors. With no pre-amplification, sample D4’s VAF falls below the calculated LoD. With pre-amplifi cation, all samples across the dilution series were above the calculated LoD. / Xll samples had replicates of 2, 4, or 8. Thus, the pre-amplification workflow significantly lowers the detection threshold.

[0277] As such, exemplary analyses show that increasing the abundance of the rare target component with pre-amplification leads to lower standard error, enhanced precision, and an improved Limit of Detection, making it possible to more confidently identify and detect samples with lower VAF'. In a single reaction, the exemplary system and method provided a 6-log dynamic range that enables the simultaneous quantification of rare molecules (e.g., rare mutant molecules) and highly abundant WT molecules present after pre-amplification, ensuring accurate quantification of the rare target’s relative abundance. Preamplifi cation thus facilitates the detection of low VAFs by increasing the abundance of both wild-type (WT) and mutant (MT) target molecules, thereby reducing standard error and lowering the limit of detection. The methods and systems described herein leverage these improvements, enabling confident identification of amplified rare molecules through deeper sampling. The demonstrated pre-amplification workflow in this high dynamic range platform allows for deeper sampling of rare molecules and unparalleled detection sensitivity at a fraction of the workflow time and cost of legacy dPCR platforms. By eliminating the need for multiple rounds of dilutions or splitting samples into multiple reactions, the methods and systems described herein offer unparalleled detection sensitivity while significantly reducing workflow time and cost compared to legacy digital PCR platforms,

[0278] FIG. 2G depicts results of analytical titration of T. cruzi parasite DNA with high background human DNA. In relation to FIG. 2G, 3000 ng of restriction endonuclease (RE)-digested human DNA (GM12878) was spiked with -2600 parasite genomes and serially diluted 10-fold, maintaining a total DNA input of 3 micrograms per reaction throughout. At the 6thdilution, 100% of samples (n:::16) were detected above the assay LoD - as such, even at a 6-log dilution, the method achieved 100% sample detection, while the IAC remained consistent. 75% of samples exceeded the microsatellite LoD of 18, with an average of 36 molecules detected (39.4% CV, n:::4). At the 7thdilution,50% of samples surpassed the kDNA LoD, with 7-20 kDNA molecules detected (40.4% CV, n::::4). LAG values averaged 29,490 (2.4% CV, n == 16) across all dilutions.

[0279] In FIG. 2G, bars indicate molecules per 50 pL detected for (A) kDNA, (B) Microsatellite, (C) LAG (mean values ± standard error (SE), n::::2 or 4). 3000 ng of restriction-digested human DNA (GM 12878) was input per reaction. Parasite stock DNA was 2.6 x 103parasites / uL. In more detail, results depicted in FIG. 2G are attributed to a workflow involving fragmentation of sample nucleic acids by using a restriction endonuclease, where the fragmented sample was then serially diluted and interrogated as described herein. The analytical range of the assay was assessed across the serial dilution of parasite DNA with 3 pg human background DNA, in order to provide a high DNA input workflow scenario (e.g., as in a clinical sample). At the 6thdilution, 100% of samples had a LoD greater than the kDNA LoD (dashed line, n = 16), with a corresponding value of 15 with an average number of 259 kDNA molecules detected (19.6% CV, n = 4). At the same dilution (i.e., 6thdilution), 75% of samples had a LoD greater than the microsatellite LoD (dashed line, n = 16), with a corresponding value of 18, with an average of 36 molecules detected (39.4 %CV, n = 4). At the 7thdilution, 50% of samples had a LoD greater than the kDNA LoD, with kDNA molecules detected ranging between 7 and 20 (40.4% CV, n = 4). As expected, IAC values were consistent across the dilution series with an average value of 29,490 (2.4% CV, n = 16).

[0280] As such, exemplary analyses showed that the systems and methods described herein are capable of processing and analyzing high-mass samples within a single reaction within a single closed container, with high-sensitivity’ detection of latent T. cruzi parasitic infections when upstream fragmentation is performed, A single high-mass reaction performed according to methods described herein, combined with target sequence fragmentation, enables robust detection of rare molecules such as T. cruzi parasites across a wide range of diminishing concentrations. Using this approach, the presence of target molecules like T. cruzi kDNA and microsatellite DNA can be identified to extremely low concentrations with high sensitivity and specificity in the same reaction. Exemplary workflows disclosed herein utilize fragmentation to partition individual repeat elements for increased parasite molecule detection that allows 20-fold higher DNA input than legacy PCR systems, providing deeper sampling, easier clinical workflow, and potentially a lower cost assay. Assay sensitivity can thus be achieved, even for rare targets, with a combination of fragmentation, multiplexed tagging, and detection of different regions (e.g., repetitive regions, other characteristic regions, other characteristic structures), and / or pre-amplifi cation of sample nucleic acids. Because the systems and methods described herein support significantly more input DNA than legacy PCRsystems within a single reaction, the platform disclosed herein shows promise for improving various applications requiring rare molecule detection, such as sparse pathogen DNA or low abundance tumor-derived DNA.2.8. Method - Additional Aspects

[0281] The methods described herein may be completed in a period of time. In some cases, imaging the plurality of partitions may be completed in no more than about 5 minutes, no more than about 10 minutes, no more than about 15 minutes, no more than about 20 minutes, no more than about 25 minutes, no more than about 30 minutes, no more than about 45 minutes, no more than about 1 hour, no more than about 2 hours, no more than about 3 hours, no more than about 4 hours, no more than about 5 hours, no more than about 6 hours, no more than about 7 hours, no more than about 8 hours, no more than about 9 hours, no more than about 10 hours, or longer. In some cases, reacting the plurality of partitions may be completed in no more than about 5 minutes, no more than about 10 minutes, no more than about 15 minutes, no more than about 20 minutes, no more than about 25 minutes, no more than about 30 minutes, no more than about 45 minutes, no more than about 1 hour, no more than about 2 hours, no more than about 3 hours, no more than about 4 hours, no more than about 5 hours, no more than about 6 hours, no more than about 7 hours, no more than about 8 hours, no more than about 9 hours, no more than about 10 hours, or longer. In some cases, generating the plurality of partitions may be completed in no more than about 5 minutes, no more than about 10 minutes, no more than about 15 minutes, no more than about 20 minutes, no more than about 25 minutes, no more than about 30 minutes, no more than about 45 minutes, no more than about 1 hour, no more than about 2 hours, no more than about 3 hours, no more than about 4 hours, no more than about 5 hours, no more than about 6 hours, no more than about 7 hours, no more than about 8 hours, no more than about 9 hours, no more than about 10 hours, or longer. In some cases, generating and reacting the plurality of partitions may be completed in no more than about 5 minutes, no more than about 10 minutes, no more than about 15 minutes, no more than about 20 minutes, no more than about 25 minutes, no more than about 30 minutes, no more than about 45 minutes, no more than about 1 hour, no more than about 2 hours, no more than about 3 hours, no more than about 4 hours, no more than about 5 hours, no more than about 6 hours, no more than about 7 hours, no more than about 8 hours, no more than about 9 hours, no more than about 10 hours, or longer. In some cases, reacting and imaging the plurality of partitions may be completed in no more than about 5 minutes, no more than about 10 minutes, no more than about 15 minutes, no more than about 20 minutes, nomore than about 25 minutes, no more than about 30 minutes, no more than about 45 minutes, no more than about 1 hour, no more than about 2 hours, no more than about 3 hours, no more than about 4 hours, no more than about 5 hours, no more than about 6 hours, no more than about 7 hours, no more than about 8 hours, no more than about 9 hours, no more than about 10 hours, or longer. In some cases, generating, reacting, and imaging the plurality of partitions may be completed in no more than about 5 minutes, no more than about 10 minutes, no more than about 15 minutes, no more than about 20 minutes, no more than about 25 minutes, no more than about 30 minutes, no more than about 45 minutes, no more than about 1 hour, no more than about 2 hours, no more than about 3 hours, no more than about 4 hours, no more than about 5 hours, no more than about 6 hours, no more than about 7 hours, no more than about 8 hours, no more than about 9 hours, no more than about 10 hours, or longer. In some cases, reacting, and imaging the plurality of partitions may be completed in no more than about 3 hours.

[0282] In relation to generation of stabilized partitions having suitable clarity (e.g., with or without refractive index matching), method(s) can further include transmission of signals from individual stabilized partitions from within the closed collecting container, for readout (e.g., by an optical detection platform, by another suitable detection platform). In embodiments, clarity can be defined in units associated with clarity or turbidity (e.g., NTU, FNU), such that the threshold level of clarity can be measured for the emulsion(s) generated according to the methods described herein. In one variation, clarity can be characterized in relation to transmissivity as detectable by a transmission detector and / or in relation to a suitable distance or depth (e.g., depth or distance into a collecting container for the emulsion; through a depth of a container of the emulsion, along an axis in which measurement of clarity is performed, etc.), where, in variations, the threshold level of clarity of the stabilized partitions is associated with a transmissivity greater than 70% transmissivity, greater than 80% transmissivity, greater than 90% transmissivity, greater than 95% transmissivity, greater than 99% transmissivity, etc. As such, in accordance with methods described herein, upon measuring clarity of the stabilized partitions within the closed collecting container using a transmission detector the stabilized partitions is characterized by a clarity associated with greater than 70% transmissivity, greater than 80% transmissivity, greater than 90% transmissivity, greater than 95% transmissivity, greater than 99% transmissivity, etc., which is above the threshold level of clarity.

[0283] During storage, as discussed herein, clarity of stabilized partitions within the closed collecting container may regress to a less clear state (e.g., from over 80% transmissivity to less than 80% transmissivity). In order to improve and / or restore clarity of the stabilized partitions, the closedcollecting container can be centrifuged (e.g., re-centrifuged) to improve and / or restore clarity of the stabilized partitions (e.g., to an over 80% transmissivity format, to an over 80% transmissivity format, etc.).2.9. Method - Universal Multiplexing

[0284] In some embodiments, the systems, methods, compositions, and kits disclosed herein employ a Universal Multiplexing approach.

[0285] Universal Multiplexing (UM) is a versatile, cost-effective solution for assaying multiple targets (e.g., with Countable PCR). Universal Multiplexing offers a solution to develop multiplex assays for up to four targets at approximately 1 / 10 the cost of conventional hydrolysis probe (HI’) multiplexed assays. Using standard unmodified primers, UM delivers the same performance and specificity as multiplexed hydrolysis probe assays. Combining UM with Countable PCR delivers a versatile, straightforward solution for developing multiplex PCR assays with single-molecule precision.

[0286] Multiplex PCR is a powerful technique that enables the simultaneous detection of multiple targets in a single reaction. Rather than detecting individual targets separately and comparing results, multiplexing reduces reaction size and sample consumption and improves quantification accuracy by minimizing pipetting errors. However, developing multiplex PCR assays presents challenges that have limited their widespread adoption.

[0287] Countable PCR overcomes multiplexing challenges through true single-molecule amplification, as described herein. In conventional qPCR or dPCR, balancing amplification kinetics between amplicons is difficult because target molecules compete for resources in the same reaction vessel or partition. This varying amplification efficiency can lead to amplification bias between targets, resulting in inaccurate quantification and potential target dropouts. In contrast, Countable PCR isolates each molecule (e.g,, DNA molecule) in its compartment within a gel-like matrix for independent amplification. Multiplexing becomes achievable with minimal optimization, without competition between targets within compartments.

[0288] To address challenges associated with traditional multiplexed assays, UM was developed. A UM assay and its comparative performance with HP-based assays on the Countable PCR platform are disclosed herein.

[0289] In one aspect, the present disclosure provides a UM assay. In some embodiments, the UM assay comprises a 1-plex UM assay. In some embodiments, the UM assay comprises a 2-plex UMassay. In some embodiments, the UM assay comprises a 3-plex UM assay. In some embodiments, the UM assay comprises a 4-plex UM assay. In some embodiments, the UM assay comprises a level of plexy of 4 or more.

[0290] FIG. 9 illustrates the assay principle of UM chemistry. UM uses generic prefixed probe sequences with target-specific primers. In UM, one primer is appended with a UM adapter sequence. During initial PCR cycles, the primer with the UM adapter binds to the template and extends. In subsequent cycles, the non-UM primer (typically R primer) binds to the forward template (now with UM adapter) and extends to create a UM probe complementary sequence. Detection occurs when the UM probe hybridizes to the probe binding site within the amplicon. The reaction can involve a 1:5 ratio (or another suitable ratio) of primer with UM adapter to the non-UM primer to drive the generation of antisense templates with the probe binding site. In some embodiments, the reaction can involve a 1:1, 1:2, 1:3, 1:4, 1:5, 1:6, 1:7, 1:8, 1:9, 1:10, 1:11, 1:12, 1:13, 1:14, 1:15, 1:16, 1:17, 1:18, 1:19, 1:20, 1:21, 1:22, 1:23, 1:24, 1:25, 1:26, 1:27, 1:28, 1:29, 1:30, or another suitable ratio of primer with UM adapter to the non-UM primer.

[0291] To convert an existing probe-based or DNA intercalating dye-based assay, a UM adapter sequence can be added to the 5’ end of either the forward or reverse primers to create a UM primer. The other primer can remain unchanged. In some embodiments, the UM adapter sequence is added to the 5’ end of the forward primer to create the UM primer. In some embodiments, the UM adapter sequence is added to the 5’ end of the reverse primer to create the UM primer.

[0292] A Universal Multiplexing kit can be used to develop multiplex assays for multiple targets per reactions. In some embodiments, the Universal Multiplexing kit comprises a UM probe. In some embodiments, the Universal Multiplexing kit comprises one UM probe. In some embodiments, the Universal Multiplexing kit comprises two UM probes. In some embodiments, the Universal Multiplexing kit comprises three UM probes. In some embodiments, the Universal Multiplexing kit comprises four UM probes. In some embodiments, the Universal Multiplexing kit comprises four or more UM probes. In some embodiments, the Universal Multiplexing kit comprises a UM probe comprising an adapter sequence selected from SEQ ID NOs: 16-19. In some embodiments, the Universal Multiplexing kit comprises a UM probe comprising an adapter sequence of SEQ ID NO: 16. In some embodiments, the Universal Multiplexing kit comprises a UM probe comprising an adapter sequence of SEQ ID NO: 17. In some embodiments, the Universal Multiplexing kit comprises a UM probe comprising an adapter sequence of SEQ ID NO: 18. In some embodiments,the Universal Multiplexing kit comprises a UM probe comprising an adapter sequence of SEQ ID NO: 19.

[0293] In some embodiments, the Universal Multiplex kit can be used to develop multiplex assays for one target per reaction. In some embodiments, the Universal Multiplex kit can be used to develop multiplex assays for up to two targets per reaction. In some embodiments, the Universal Multiplex kit can be used to develop multiplex assays for up to three targets per reaction. In some embodiments, the Universal Multiplex kit can be used to develop multiplex assays for up to four targets per reaction. In some embodiments, the Universal Multiplex kit can be used to develop multiplex assays for four or more targets per reaction.

[0294] In some embodiments, the target comprises a target as disclosed herein (e.g., target component, rare target component, etc. ).

[0295] In a specific example, a Universal Multiplex kit comprising UM probes was used to develop multiplex assays for up to four targets per reaction. Table 4 lists the UM adapter sequences for the UM-1, UM-2, UM-3, and UM-4 probes within the exemplary Universal Multiplex kit.Table 4. Four UM adapter sequences in the exemplary Universal Multiplex kit.

[0296] Table 5 shows the sequences of both UM primers and non-UM primers designed for each of the four targets in the UNI assays of the specific example. Table 5 also shows how these primers were derived from forward and reverse primers from a previously designed HP-based assay.Table 5. Primer sequences used for the exemplary UM assays. A UM adapter (underlined) was appended to the 5’ end of a gene-specific primer to generate a UM primer. No modification was used for non-UM primers.

[0297] Following best practices for multiplex PCR assay design, oligo analysis tools can be used to conduct in silico analysis to check for self-interactions (such as hairpin formation) within oligos -including those with appended UM adapters - and cross-interactions between all primers, probes, and amplicons to reduce and / or prevent non-specific signal generation.

[0298] In variations where applications may demand higher specificity', HPLC-purified UM primers can be prepared to eliminate truncated oligos that may be generated during the synthesis process.

[0299] Countable PCR reactions were set up and analyzed. Table 6 summarizes an exemplary Countable PCR reaction set up. An excess of non-UM primer over UM primer was used for optimal signal generation in UM.

[0300] UM chemistry delivered the same counting performance as hydrolysis probe assays. In a specific example, the Countable PCR performance of a UM 4-plex assay was compared to that of a 4-plex HP-based assay targeting the same genes. Counts from UM assay matched those from HPbased assay closely, with less variation, as shown in FIG. 10.

[0301] Because the fluorescent signals in the UM chemistry come from a pre-optimized UM probe mix, the signal and noise characteristics of the assay are independent of primer sequences.

[0302] UM also achieved robust counting performance from 1-plex to 4-plex across 6-logs. In a specific example, 1-plex, 2-plex, 3-plex, and 4-plex configurations were compared in Countable PCR using four UM assays targeting different gene sequences. As shown in FIG. 11, using human gDNA as a template, the counts remained consistent regardless of plex number. There was no amplification bias in the presence of other targets for Countable PCR - a phenomenon commonly observed in qPCR or even in digital PCR when one partition contains multiple templates. The assay noise was also low (0 for NTC samples), as evidenced by the non-detection of counts for NTC samples within the 4-plex configuration.

[0303] In another specific example, the same 4-plex UM assay was further tested with DNA templates diluted across a 6-log range of serial dilutions, with roughly equal amounts of templates per target. As shown in FIG. 12, the assay demonstrated robust, reproducible quantification of four different targets from across 6-log dynamic range. This capability allows for the detection of both abundant and rare targets, such as in gene expression analysis, that are often times conducted in separate qPCR assays with DNA intercalating dyes.

[0304] UM also offers flexibility in multiplex assay design. In a specific example, the UM adapter sequences were carefully designed not to interact with genome sequences of any common species, while preserving the same counting performance across adapter designs. Any UM adapter sequence can be chosen to convert a primer into a UM primer, as long as attention is paid to avoiding hairpin formation resulting from the adapter addition. To demonstrate the flexibility of UM adapter choices, in the specific example three targets with different expression levels were evaluated using three UM probes: GAPDH (high expression), CD3E (medium expression), and CD1A (low expression) using human cDNA as a template. UM-1, UM-2, and UM-4 probes were attached to each target and permuted as shown in FIG. 13. Counts remained constant for all targets regardless of the UM probe chosen, and despite varying expression levels, the coefficient of variation remained low across all samples.

[0305] UM can also be used in combination with HP. In silico analysis of oligos can be performed first to check compatibility. As shown in the specific example of FIG. 14, HP and UM can function effectively together in a single tube.

[0306] UM delivered the same multiplexing and counting performance as HP-based assays in Countable PCR. When integrated with Countable PCR, UM provided consistent counting precision across a 6-log range and up to 4-plexes, irrespective of probe sequence or expression level. Existing assays using DNA intercalating dyes can be converted to UM assays, gaining multiplexing capabilities. Applications such as gene expression analysis or copy number variation - which typically require comparing target and reference genes - can be performed in a single UM reaction rather than multiple separate reactions.2.10. Method - Summary2.10.1. Method - T. cruzi Detection Assays

[0307] Introduction: Chagas disease, caused by Trypanosoma cruzi, affects an estimated 8-10 million people globally, with 120 million at risk and 9,500-12,000 deaths annually. Its economic burden surpasses that of other endemic diseases such as rotavirus and Lyme disease. Early detection is crucial for mitigating health and economic impacts and advancing new treatments. Infected subjects generally control the acute infection but retain a life-long, low parasitemic chronic infection, which can progress to cardiomyopathy and digestive tract dysfunction over decades. Current serological and molecular detection methods have limited sensitivity and often fail toidentify active infection. Enhanced detection methods are crucial for the sensitive detection of parasite markers, including circulating T. cruzi DNA, for identifying individuals who may require treatment and for assessing the treatment efficacy.

[0308] Methods: Two multiplexed T. cruzi detection assays are disclosed in order to address the limitations of qPCR and legacy digital PCR. By utilizing > 30 million partitions, the exemplary methods achieved single molecule representation in positive partitions and eliminated the need for Poisson error correction. The simple, single-tube workflow also featured up to 36.5 pL input volume and no dead volume. The methods utilized these unique capabilities to enhance workflow efficiency and improve sensitivity for rare molecule detection (RMD) in blood, compared to existing methods.

[0309] Results: The methods involved two multiplexed assays targeting the parasite’s repetitive satellite sequence, the kinetoplast, and an internal amplification control. Utilizing the high partition count available, the method involved loading up to 1 pg of DNA per reaction, compared to the conventional 125 ng, enabling the survey of over 10 times more DNA per sample, significantly reducing the number of replicates from 200 to 4. Further, mechanical shearing to achieve 300, 500, and 1000 bp DNA fragments improved partitioning efficiency resulting in a threefold improvement in sensitivity' compared to gDNA input. Fragmentation particularly benefited the satellite sequence, allowing for individual partitioning and quantification of repeated sequences, thereby enhancing measurement precision.

[0310] Conclusion: By leveraging the unique capabilities of the system, entire blood samples can be screened for T, cruzi cfDNA in fewer reactions, while increasing the number of rare molecules per reaction. Overall, this approach greatly increases the sensitivity of T. cruzi detection, reduces cost per sample, and improves workflow efficiency.2.10.2. Method - JAK2 Gene Mutation Detection Assay

[0311] Introduction: Mutations in the JAK2 gene are crucial for diagnosing myeloproliferative neoplasms (MPNs), associated with excessive blood cell production and risks of thrombosis and leukemia. Lowering the detection threshold for these mutations, which often remain undetected for years, could enable earlier identification, monitoring, and treatment, leading to better outcomes.

[0312] Legacy digital PCR (dPCR) platforms excel in rare molecule detection but face challenges like limited DNA input and high dead volume, resulting in loss of precious signal, which is critical when measuring rare targets. Amplifying these samples prior to partitioning (pre-amplification) is a workaround, yet limited partition numbers can lead to oversaturation and inaccurate quantificationwithout additional titration steps and increasing workflow time and costs. The exemplary platform generates over 30 million partitions, 1,500 times more partitions than legacy dPCR, facilitating precise molecule quantification of both housekeeping genes and rare molecules in the same assay.

[0313] Methods: A 2-color JAK2 V617F multiplex assay with a high signal-to-noise ratio for the rare target was designed for the exemplary platform, which utilizes centrifugation to create >30 million partitions per sample. Analytical characterization of the pre-amplification workflow involved using approximately 80 ng (12,100 GE) of contrived genomic DNA from the GM12878 cell line spiked with JAK2 V617F mutant constructs at 30%, 3%, 0.3%, 0.03%, and 0% variant allele frequency (VAF).

[0314] Samples underwent pre-amplification with a high-fidelity enzyme for 12 cycles, followed by DNA purification and a single dilution. Each sample set, comprising 2 samples, was analyzed on the exemplary platform system with 2-4 technical replicates. The high partition count enabled direct quantification on positive partitions only, obviating the need for Poisson correction.

[0315] Results: Without pre-amplification, the assay quantified an average of 23,480 (11.8% CV, n = 16) total JAK2 molecules, suggesting low dead volume throughout the workflow. In pre-amplified samples, an average of 421,588 (19.7% CV, n = 16) JAK2 molecules were measured, with a PCR efficiency of 75% and counting variance between 2.2-13.5%. This workflow provided highly consistent amplification while still within the dynamic range of the platform, as well as high %VAF concordance compared to control.

[0316] At the low %VAF sample (0.03% target), JAK2 V617F mutant target counts improved from 4.3 (90.9% CV) to 158.4 (1.0% CV) molecules, increasing precision and reducing sampling error after pre-amplification. The assay’s limit of detection (LoD) improved from 0.0362% to 0,0151% with pre-amplification,

[0317] Conclusion: Here, the methods demonstrate that adding pre-amplification reduces the LoD and rare molecule counting variance, leveraging high dynamic range precision. Further optimization could enhance sensitivity by counting rare molecules within the platform’s limits, offering an alternative method for detecting rare molecules in oncology.3. Kits and Compositions

[0318] In another aspect, the present disclosure provides a kit containing materials (e.g., processing materials) useful for using the systems and methods disclosed herein. The kit may include one ormore compositions, components of the compositions, or set(s) of processing materials (i.e., various mixes), as disclosed herein.

[0319] In some embodiments, the kit comprises a set of processing materials that comprises: a) for each set of targets, a set of target-specific (e.g., allele-specific) forward primers corresponding to different variations of a respective target of the set of targets, and a common reverse primer for the set of target-specific (e.g., allele-specific) forward primers, and b) a master mixture including amplification reagent as well as: for each of the set of targets, a set of target-specific (e.g., allelespecific) flanking sequences corresponding to different targets of the set of targets. In some embodiments, the kit comprises a set of processing materials that comprises, for a target of the set of targets: a primer set comprising: a common primer and a set of target-specific primers comprising a target- specific primer configured to interact with a target region of the target, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified. In some embodiments, the kit comprises a set of processing materials that comprises, for a first target and a second target of the set of targets: a primer set comprising: at least one primer configured to tag the first target with a first probe having a first fluorophore and the second target with a second probe having a second fluorophore.

[0320] In some embodiments, the kit comprises a set of processing materials that comprises, for a rare target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the rare target component, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified. In some embodiments, the set of processing materials of the kit further comprises, for a background component, a primer set comprising: a common primer and a set of target-specific primers comprising a target- specific primer configured to interact with a target region of the background component, and a second fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the second fluorophore-labeled oligonucleotide comprising a second fluorophore configured to transmit a second target signal if the target region is amplified. In some embodiments, the kit comprises a set of processing materials that comprises, for a rare target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the rare target component, the target-specific primer having a common adapter sequence, and afluorophore- labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. In some embodiments, the set of processing materials of the kit further comprises, for a background component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the background component, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 16. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 17. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 18. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 19.

[0321] In some embodiments, the kit comprises a set of processing materials that comprises, for a rare target component and a background component, a primer set comprising at least one primer configured to tag the rare target component with a first probe having a first fluorophore and the background component with a second probe having a second fluorophore.

[0322] In some embodiments, the kit comprises a set of processing materials for detection of a JAK2 mutation (e.g., the rare target component comprises a mutation in a JAK2 gene). In some embodiments, the set of processing materials of the kit for detection of the JAK2 mutation comprises a primer comprising a nucleotide sequence of SEQ ID NO: 14. In some embodiments, the set of processing materials of the kit for detection of the JAK2 mutation comprises a primer comprising a nucleotide sequence of SEQ ID NO: 15.

[0323] In variations wherein a target component comprises one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, the kit can comprise a set of processing materials that comprises, for a first shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target- specific primers comprising a targetspecific primer configured to interact with a target region of the first shorter nucleotide sequence, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified. In some embodiments, the set of processing materialsof the kit further comprises, for a second shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the second shorter nucleotide sequence, and a second fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the second fluorophore-labeled oligonucleotide comprising a second fluorophore configured to transmit a second target signal if the target region is amplified.

[0324] In some embodiments, the kit comprises a set of processing materials that comprises, for a first shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the first shorter nucleotide sequence, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. In some embodiments, the set of processing materials of the kit further comprises, for a second shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the second shorter nucleotide sequence, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 16. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 17. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 18. In some embodiments, the common adapter sequence comprises a nucleotide sequence of SEQ ID NO: 19.

[0325] In some embodiments, the kit comprises a set of processing materials that comprises, for a first shorter nucleotide sequence and a second shorter nucleotide sequence of the at least two shorter nucleotide sequences that are repetitive sequences characteristic of the target component, a primer set comprising at least one primer configured to tag the first shorter nucleotide sequence with a firstprobe having a first fluorophore and the second shorter nucleotide sequence with a second probe having a second fluorophore.

[0326] In some embodiments, the kit comprises a set of processing materials that comprises a background component comprising an amplification control comprising a nucleotide sequence of SEQ ID NO: 13. In some embodiments, the kit comprises a set of processing materials that comprises a primer set comprising at least one primer configured to tag a background component of the sample with a third probe having a third fluorophore. In some embodiments, the background component comprises the amplification control comprising a nucleotide sequence of SEQ ID NO: 13. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 9. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 10. In some embodiments, the set of processing materials of the kit comprises a probe comprising a nucleotide sequence of SEQ ID NO: 11. In some embodiments, the set of processing materials of the kit comprises a probe additive comprising a nucleotide sequence of SEQ ID NO: 12.

[0327] In some embodiments, the kit comprises a set of processing materials for detection of repetitive sequences characteristic of T. cruzi. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 1. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 2. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 5. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 6. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 34. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 35. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 36. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 37. In some embodiments, the set of processingmaterials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 38. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 39. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a primer comprising a nucleotide sequence of SEQ ID NO: 40. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a probe comprising a nucleotide sequence of SEQ ID NO: 3. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a probe comprising a nucleotide sequence of SEQ ID NO: 7. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a probe additive comprising a nucleotide sequence of SEQ ID NO: 4. In some embodiments, the set of processing materials of the kit for detection of repetitive sequences characteristic of T. cruzi comprises a probe additive comprising a nucleotide sequence of SEQ ID NO: 8.

[0328] In some embodiments, the kit comprises a set of processing materials that comprises a primer comprising a nucleotide sequence selected from SEQ ID NOs: 1-40. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 20. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 21. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 22. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 23. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 24, In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 25. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 26. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 27. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 28. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 29. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 30. In some embodiments, the set of processing materials of the kit comprises a primercomprising a nucleotide sequence of SEQ ID NO: 31. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 32. In some embodiments, the set of processing materials of the kit comprises a primer comprising a nucleotide sequence of SEQ ID NO: 33.

[0329] In some embodiments, the kit comprises a set of processing materials that comprises, for a target of the set of targets: a primer set comprising: a common primer and a set of target-specific primers configured to interact with a target region of the target, the set of target-specific primers comprising a first target-specific primer comprising a first flanking sequence, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified. For tagging a target with probes configured to emit multiple colors (where tandem probes are described in more detail herein), the set of target-specific primers of the set of processing materials of the kit can further comprise a second target-specific primer comprising a second flanking sequence, and the set of processing materials of the kit further comprises a second fluorophore-labeled oligonucleotide corresponding to the second flanking sequence, the second fluorophore-labeled oligonucleotide comprising a second fluorophore configured to transmit a second target signal if the target region is amplified, such that the target can be positively detected based upon the first target signal and the second target signal. Alternatively, a single primer can be used to tag the target, along with tandem adapters corresponding to the probes used to tag the targets, and the set of processing materials of the kit can include at least one primer configured to tag the target with a first probe having a first fluorophore and a second probe having a second fluorophore (and / or additional probes with additional fluorophores), wherein the first fluorophore and the second fluorophore (and optional additional fluorophores) correspond to two (or more) color channels of the number of color channels.

[0330] In some embodiments, the kit comprises a set of processing materials that comprises a master mixture. In some embodiments, the master mixture of the set of processing materials of the kit comprises amplification reagents and, for each set of targets, a set of target-specific flanking sequences corresponding to different targets of the set of targets, in order to support multiplexed processing, detection, and digital quantitation. In some embodiments, the master mixture of the set of processing materials of the kit comprises a probe including a dye / fluorophore with complementary quencher for each target. In some embodiments, the master mixture of the set of processing materials of the kit comprises a polymerase (e.g., Taq polymerase). In someembodiments, the master mixture of the set of processing materials of the kit comprises dNTPs. In some embodiments, the master mixture of the set of processing materials of the kit comprises buffer components. In some embodiments, the dye of the master mixture of the set of processing materials of the kit comprises one or more of: FAM, (e.g., 6-FAM), Cy3TM, Cy5TM, Cy5.5TM, TAMRATM (e.g., 5-TAMRA, 6-TAMRA, etc.), MAX, JOE, TETTM, ROX, TYETM (e.g., TYE 563, TYE 665, TYE 705, etc.), Yakima Yellow ®, HEX, TEX (e.g., TEX 615), SUN, ATTOTM (e.g., ATTO 488, ATTO 490LS, ATTO 532, ATTO 550, ATTO 565, ATTO RholOl, ATTO 590, ATTO 633, ATTO 647, ATTO 647N, etc.), Alexa Fluor ® (e.g., Alexa Fluor 488, Alexa Fluor 532, Alexa Fluor 546, Alexa Fluor 594, Alexa Fluor 647, Alexa Fluor 660, Alexa Fluor 750, etc.), IRDyes® (e.g., 5TRDye 700, 5’IRDye 800, 5’IRDye 800CW, etc.), Rhodamine (e.g., Rhodamine Green, Rhodamine Red, Texas Red ®, Lightcycler ®, Dy 482XL, Dy 508XL, Dy 526XL, Dy 750, Hoechst dyes, DAPI dyes, SYTOX dyes, chromomycin dyes, mithramycin dyes, YOYO dyes, ethidium bromide dyes, acridine orange dyes, TOTO dyes, thiazole dyes, CyTRAK dyes, propidium iodide dyes, LDS dyes, BODIPY dyes, and / or other dyes. In some embodiments, the dye of the master mixture of the set of processing materials of the kit is selected from: Alexa Fluor 488, Alexa Fluor 594, ATTO 490LS, ATTO 532, ATTO 647N, Cy5TM, FAM, Dy 482XL, Dy 508XL, Dy 526XL, and combinations thereof. In some embodiments, the master mixture of the set of processing materials of the kit comprises a cell function dye for tagging of target material and detection that can include one or more of: DCFH, DHR, SNARF, indo-1, Fluo-3, Fluo-4, and / or other dyes. In some embodiments, the master mixture of the set of processing materials of the kit comprises a fluorescent protein for tagging of target material and detection can include one or more of: cerulean, mCFP, mTurquoise, T-Sapphire, CyPet, ECFP, CFP, EBFP, Azurite, and / or other fluorescent proteins. In some embodiments, the master mixture of the set of processing materials of the kit comprises a quencher oligonucleotide configured such that, when the quencher oligonucleotide anneals with a primer having a fluorophore, the quencher molecule is in proximity to (e.g., directly opposite) the fluorophore in order to quench the fluorophore. In some embodiments, the quencher of the master mixture of the set of processing materials of the kit comprises one or more of: a black hole quencher, a static quencher, a self-quencher (e.g., a fluorophore that self-quenches under certain conditions by producing secondary structures or other structures), and / or another suitable quencher.

[0331] In some embodiments, the kit comprises a set of processing materials that comprises components configured to improve the signal-to-noise ratio (SNR) characteristics in the context ofmultiplexed detection, by increasing signal characteristics and / or reducing background (e.g., noise other artifacts).

[0332] In some embodiments, the kit comprises a Universal Multiplexing kit which can be used to develop multiplex assays as disclosed herein. In some embodiments, the Universal Multiplexing kit comprises a UM probe as disclosed herein.

[0333] In some embodiments, the kits and compositions are useful for processing a sample for detection of a target component and / or rare target component.

[0334] Elements of the kit may be provided individually or in combinations. Elements of the kit may be provided in any suitable container. In some embodiments, the kit includes instructions in one or more languages. In some embodiments, the kit comprises one or more reagents for use in a process or method utilizing one or more of the elements described herein. Reagents may be provided in any suitable container. For example, a kit may provide one or more reaction or storage buffers. Reagents may be provided in a form that is usable in a particular assay, or in a form that may require addition of one or more other components before use (e.g., in concentrate or lyophilized form).

[0335] The kit can include a container and a label or package insert on or associated with the container. Suitable containers include, for example, bottles, vials, tubes (e.g., PCR tubes), syringes, etc. The containers may be formed from a variety of materials such as glass or plastic. The kit may further include other materials desirable from a commercial and user standpoint, including other buffers, diluents, filters, needles, and syringes.4. Computer Systems

[0336] The present disclosure provides computer systems that may be programmed to implement methods of the disclosure, FIG. 8 shows a computer system 901 that is programmed or otherwise configured to, for example, perform a digital analysis of a sample distributed across a set of partitions. Performing the digital analysis can include steps of methods described herein.

[0337] The computer system 901 can additionally or alternatively perform other aspects of digital multiplexed assays for characterizations involving other loci of interest, with applications of use described herein.

[0338] The computer system 901 can regulate various aspects of analysis, calculation, and generation of the present disclosure, such as, for example, generating a plurality of partitions (e.g., from an aqueous mixture including sample material and materials for an amplification reaction) within a collecting container at a desired rate, transmitting heat to and from the plurality of partitionswithin the collecting container, performing an optical interrogation operation with the plurality of partitions within the collecting container, and / or performing one or more digital multiplexed assay steps. The computer system 901 can be an electronic device of a user or a computer system that is remotely located with respect to the electronic device. The electronic device can be a mobile electronic device.

[0339] The computer system 901 includes a central processing unit (CPU, also “processor" and “computer processor" herein) 905, which can be a single core or multi core processor, or a plurality of processors for parallel processing. The computer system 901 also includes memory or memory location 910 (e.g., random-access memory, read-only memory, flash memory), electronic storage unit 915 (e.g., hard disk), communication interface 920 (e.g., network adapter) for communicating with one or more other systems, and peripheral devices 925, such as cache, other memory, data storage and / or electronic display adapters. The memory 910, storage unit 915, interface 920 and peripheral devices 925 are in communication with the CPU 905 through a communication bus (solid lines), such as a motherboard. The storage unit 915 can be a data storage unit (or data repository) for storing data. The computer system 901 can be operatively coupled to a computer network (“network") 930 with the aid of the communication interface 920. The network 930 can be the Internet, an internet and / or extranet, or an intranet and / or extranet that is in communication with the Internet.

[0340] In some embodiments, the network 930 is a telecommunication and / or data network. The network 930 can include one or more computer servers, which can enable distributed computing, such as cloud computing. For example, one or more computer servers may enable cloud computing over the network 930 (“the cloud") to perform various aspects of analysis, calculation, and generation of the present disclosure, such as, for example, generating a plurality of droplets within a collecting container at a predetermined rate or variation in polydispersity. Such cloud computing may be provided by cloud computing platforms such as, for example, Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, and IBM cloud. In some embodiments, the network 930, with the aid of the computer system 901, can implement a peer-to-peer network, which may enable devices coupled to the computer system 901 to behave as a client or a server.

[0341] The CPU 905 may comprise one or more computer processors and / or one or more graphics processing units (GPUs). The CPU 905 can execute a sequence of machine-readable instructions, which can be embodied in a program or software. The instructions may be stored in a memory location, such as the memory 910. The instructions can be directed to the CPU 905, which cansubsequently program or otherwise configure the CPU 905 to implement methods of the present disclosure. Examples of operations performed by the CPU 905 can include fetch, decode, execute, and writeback.

[0342] The CPU 905 can be part of a circuit, such as an integrated circuit. One or more other components of the system 901 can be included in the circuit. In some embodiments, the circuit is an application specific integrated circuit (ASIC).

[0343] The storage unit 915 can store files, such as drivers, libraries and saved programs. The storage unit 915 can store user data, e.g., user preferences and user programs. In some embodiments, the computer system 901 can include one or more additional data storage units that are external to the computer system 901, such as located on a remote server that is in communication with the computer system 901 through an intranet or the Internet.

[0344] The computer system 901 can communicate with one or more remote computer systems through the network 930. For instance, the computer system 901 can communicate with a remote computer system of a user. Examples of remote computer systems include personal computers (e.g., portable PC), slate or tablet PC’s (e.g., Apple® iPad, Samsung® Galaxy Tab), telephones, Smart phones (e.g., Apple® iPhone, Android-enabled device, Blackberry®), or personal digital assistants. The user can access the computer system 901 via the network 930.

[0345] Methods as described herein can be implemented by way of machine (e.g., computer processor) executable code stored on an electronic storage location of the computer system 901, such as, for example, on the memory 910 or electronic storage unit 915. The machine executable or machine- readable code can be provided in the form of software. During use, the code can be executed by the processor 905. In some embodiments, the code can be retrieved from the storage unit 915 and stored on the memory 910 for ready access by the processor 905, In some situations, the electronic storage unit 915 can be precluded, and machine-executable instructions are stored on memory 910.

[0346] The code can be pre-compiled and configured for use with a machine having a processer adapted to execute the code, or can be compiled during runtime. The code can be supplied in a programming language that can be selected to enable the code to execute in a pre-compiled or as-compiled fashion.

[0347] Embodiments of the systems and methods provided herein, such as the computer system 901, can be embodied in programming. Various aspects of the technology may be thought of as “products" or “articles of manufacture" and may be in the form of machine (or processor) executablecode and / or associated data that is carried on or embodied in a type of machine readable medium. Machine-executable code can be stored on an electronic storage unit, such as memory (e.g., readonly memory, random-access memory, flash memory) or a hard disk. “Storage" type media can include any or all of the tangible memory of the computers, processors or the like, or associated modules thereof, such as various semiconductor memories, tape drives, or disk drives, which may provide non-transitory storage at any time for the software programming. All or portions of the software may at times be communicated through the Internet or various other telecommunication networks. Such communications, for example, may enable loading of the software from one computer or processor into another, for example, from a management server or host computer into the computer platform of an application server. Thus, another type of media that may bear the software elements includes optical, electrical and electromagnetic waves, such as used across physical interfaces between local devices, through wired and optical landline networks and over various air-links. The physical elements that carry such waves, such as wired or wireless links, optical links or the like, also may be considered as media bearing the software. As used herein, unless restricted to non-transitory, tangible “storage" media, terms such as computer or machine “readable medium" refer to any medium that participates in providing instructions to a processor for execution.

[0348] Hence, a machine-readable medium, such as computer-executable code, may take many forms, including a tangible storage medium, a carrier wave medium or physical transmission medium. Non-volatile storage media include, for example, optical or magnetic disks, such as any of the storage devices in any computer(s) or the like, such as may be used to implement the databases, etc., shown in the drawings. Volatile storage media include dynamic memory, such as main memory of such a computer platform. Tangible transmission media include coaxial cables; copper wire and fiber optics, including the wires that comprise a bus within a computer system. Carrier-wave transmission media may take the form of electric or electromagnetic signals, or acoustic or light waves such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media therefore include for example: a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD or DVD-ROM, any other optical medium, punch cards, paper tape, any other physical storage medium with patterns of holes, a RAM, a ROM, a PROM and EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave transporting data or instructions, cables or links transporting such a carrier wave, or any other medium from which a computer may read programming code and / or data. Manyof these forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to a processor for execution.

[0349] The computer system 901 can include or be in communication with an electronic display 935 that comprises a user interface (UI) 940 for providing, for example, a visual display indicative of stages of or results from performing a digital analysis of a sample distributed across a set of partitions. Examples of UIs include, without limitation, a graphical user interface (GUI) and webbased user interface.

[0350] Methods and systems of the present disclosure can be implemented by way of one or more algorithms. An algorithm can be implemented by way of software upon execution by the central processing unit 905. The algorithm can, for example, generate a plurality of droplets within a collecting container with desired characteristics.

[0351] The FIGS, illustrate the architecture, functionality and operation of possible implementations of systems, methods and computer program products according to preferred embodiments, example configurations, and variations thereof. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block can occur out of the order noted in the FIGS.. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustration, and combinations of blocks in the block diagrams and / or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

[0352] It should be understood from the foregoing that, while particular implementations have been illustrated and described, various modifications may be made thereto and are contemplated herein. It is also not intended that the invention be limited by the specific examples provided within the specification. While the invention has been described with reference to the aforementioned specification, the descriptions and illustrations of the preferable embodiments herein are not meant to be construed in a limiting sense. Furthermore, it shall be understood that all aspects of the invention are not limited to the specific depictions, configurations or relative proportions set forth herein which depend upon a variety of conditions and variables. Various modifications in form and detail of the embodiments of the invention will be apparent to a person skilled in the art. It is-1 Oltherefore contemplated that the invention shall also cover any such modifications, variations and equivalents. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby.

[0353] As a person skilled in the art will recognize from the previous detailed description and from the figures and claims, modifications and changes can be made to the preferred embodiments of the invention without departing from the scope of this invention defined in the following claims.EXAMPLESExample #1. Countable PCR T. Cruzi Detection Assay

[0354] In a specific example, the Countable PCR detection assay is a T. cruzi detection assay which targets parasite-specific sites within the T. cruzi genome, as well as a synthetic gBlock exemplary internal amplification control (IAC) that is spiked-in as an inhibition indicator. This 3-plex PCR assay was based on hydrolysis probe chemistry. Each target was detected in separate channels on the Countable PCR platform. The input capacity of the platform enabled loading of up to 3 ug of plasma-extracted DNA per reaction.

[0355] To enhance sensitivity of detecting the parasitic DNA, the exemplary' assay targeted the repetitive sites (kinetoplast DNA [kDNA] and microsatellite repeats [sDNA]) within the T. cruzi genome. These repetitive elements (e.g., shorter nucleotide sequences) occur hundreds of times per genome. The exemplary protocol utilized restriction endonuclease digestion to liberate individual repeat elements within the parasitic genomes to increase the availability of these identifying elements to be assayed by Countable PCR,

[0356] Starting after sample extraction, described herein is an exemplary workflow of filtering and digestion steps that prepared samples for Countable PCR.

[0357] Exemplary Materials and Equipment: In addition to materials and equipment listed, the following were also used in the exemplary workflow: a Nanodrop or fluorometer for DNA mass quantitation; 0.1 gm pore filter centrifugation tubes (Millipore #UFC30); Msel (New England Biolabs™ catalog # R0525); and SacI-HF (New England Biolabs™ catalog # R3156).

[0358] Exemplary Protocol:

[0359] Step 1 - Total genomic DNA extraction from blood plasma: Total genomic DNA was extracted from blood plasma.

[0360] Step 2 - Filtration of extracted DN / X prior to Countable PCR processing: For optimal and reproducible results, samples were filtered after blood extraction. Any particulate residue canpotentially impede the flow of sample through the Matrix Column. For filtration: (I) each sample was added to a 0.1 pm pore filter tube; (2) spun at 12000 x g for 6 minutes; and (3) the concentration of each filtered sample measured via Nanodrop or a fluorometer to guide downstream sample input amount.

[0361] Step 3 - Restriction endonuclease digestion: Sample digestion occurred in the amplification mix prior to loading the Matrix Column. For sample digestion: (1) an amplification mix was prepared based on Table 7 below; (2) volumes were scaled up to account for all samples plus 10% overage; (3 ) 30 pL of the mix was aliquoted into a PCR strip tube per sample; (4) 20 pL of each filtered sample was loaded at the desired total mass concentration; and (5) incubated at 37 °C for 30 minutes in a thermal cycler. Note: sample input mass for the exemplary assay was optimized for 3 pg of genomic DNATable 7. Exemplary amplification mix composition for T. cruzi detection assay.*Note: IAC gBlock stock diluted to generate ~20k counts / pL experimentally.

[0362] Step 4 - Prepare swing bucket assemblies and thermal cycling protocol: For this step: (1) consumables were set up; (2) into each Matrix Tube, 40 pL of MR01 was loaded; (3 ) into each Matrix Tube, 90 pL of MR02 was loaded; (4) 50 pL of each sample (digested and in the amplification mix) was loaded into the Matrix Column; (5) 50 pL of MR03 was loaded to the top of each Matrix Column sample; (6) the Matrix Column Strip was sealed; (7) centrifuged at 16,000 x gfor 20 minutes at room temperature; (8) the tubes were handled, with the exemplary thermal cycling protocol described in Table 8 below used.Table Exemplary thermal cycler settings for T. cruzi detection assay.*Note: Ramp rate: 2 °C / s; Lid temperature: 105 °C; Sample volume: 125 pL

[0363] After completion of thermal cycling, the samples were imaged on the Countable PCR platform.

[0364] Exemplary Oligo Mixes: Lyophilized oligo stocks (primers, probes, probe additives, etc.) were diluted in 10 mM Tris, pH 8.0 with 0.1 mM EDTA to make a 100 pM stock concentration for each. The volume of each component taken from a 100 pM stock is listed in Table 9 to show how to make an exemplary 5 Ox oligo mix.

[0365] Exemplary Internal Amplification Control (IAC) Sequence: The IAC comprising a nucleotide sequence of SEQ ID NO: 13 (Table 10) was ordered from IDT.Table 10. Nucleotide sequence of exemplary IAC.

[0366] Exemplary Channel and Target Mapping: Channel and target mapping was performed according to Table 11.SEQUENCES

Claims

CLAIMSWHAT IS CLAIMED IS:

1. A method for processing a sample for detection of a target component, the method comprising:processing the sample comprising an amount of input nucleic acids greater than 1 microgram, wherein the target component of the nucleic acids is within a set of partitions comprising at least 30 million partitions within a single closed container, wherein processing the sample comprises:(a) generating a fragmented sample upon fragmenting the nucleic acids of the sample; (b) distributing the fragmented sample across the set of partitions, wherein each partition of the set of partitions comprises a portion of the fragmented sample and processing materials;(c) reacting the processing materials of each partition of the set of partitions with the portion of the fragmented sample, thereby driving the target component of the sample to a level of detection of a detection system configured to scan the single closed container and count a set of positive partitions of the set of partitions, wherein a positive partition of the set of positive partitions emits a signal associated with the target component;(d) detecting the set of positive partitions upon scanning the single closed container; and (e) returning an analysis of the target component.

2. The method of claim 1, wherein the target component comprises one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component.

3. The method of claim 2, wherein the target component comprises at least two shorter nucleotide sequences that are repetitive sequences characteristic of the target component.

4. The method of claim 2, wherein the target component comprises a rare target component associated with an infectious disease agent.

5. The method of claim 4, wherein the rare target component comprises DNA from Trypanosoma cruzi.

6. The method of claim 5, wherein the one or more shorter nucleotide sequences comprise kinetoplast DN / X (kDNA), microsatellite DNA, or a combination thereof.

7. The method of claim 1, wherein generating the fragmented sample comprises performing a mechanical fragmentation operation on the sample, wherein the mechanical fragmentation operation comprises acoustic shearing, sonication, or a combination thereof.

8. The method of claim 1, wherein generating the fragmented sample comprises performing an enzymatic fragmentation operation on the sample, wherein the enzymatic fragmentation operation comprises treatment with one or more restriction endonucleases.

9. The method of claim 8, wherein the one or more restriction endonucleases are selected from: a SacI restriction endonuclease, a Msel restriction endonuclease, and isoschizomers thereof.

10. The method of claim 1, wherein each partition of the set of partitions comprises at most one target of the target component of the sample.

11. The method of claim 1, wherein the sample comprises a target component and a background component.

12. The method of claim 11, wherein returning the analysis comprises:returning a first abundance of the target component and a second abundance of the background component, andreturning a relative abundance of the target component from the first abundance and the second abundance.

13. The method of claim 1, wherein the method is characterized by a limit of detection of less than 20 molecules representing the target component distributed across at least 30 million partitions.

14. The method of claim 1, wherein generating the fragmented sample upon fragmenting the nucleic acids of the sample increases the sensitivity of detection of one or more shorter nucleotide sequences of the fragmented sample that is characteristic of the target component by at least 3 -fold.

15. The method of claim 2, wherein the processing materials comprise, for a first shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of targetspecific primers comprising a target-specific primer configured to interact with a target region of the first shorter nucleotide sequence, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified.

16. The method of claim 15, wherein the processing materials further comprise, for a second shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the second shorter nucleotide sequence, and a second fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the second fluorophore-labeled oligonucleotide comprising a second fluorophore configured to transmit a second target signal if the target region is amplified.

17. The method of claim 2, wherein the processing materials comprise, for a first shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of targetspecific primers comprising a target-specific primer configured to interact with a target region of the first shorter nucleotide sequence, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified.

18. The method of claim 17, wherein the processing materials further comprise, for a second shorter nucleotide sequence of the one or more shorter nucleotide sequences that is a repetitive sequence characteristic of the target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the second shorter nucleotide sequence, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified.-1 Il19, The method of claim 3, wherein the processing materials comprise, for a first shorter nucleotide sequence and a second shorter nucleotide sequence of the at least two shorter nucleotide sequences that are repetitive sequences characteristic of the target component, a primer set comprising at least one primer configured to tag the first shorter nucleotide sequence with a first probe having a first fluorophore and the second shorter nucleotide sequence with a second probe having a second fluorophore.20, The method of claim 1, wherein the method provides at least a 6-log dynamic range that enables the simultaneous quantification of the at least two shorter nucleotide sequences that are repetitive sequences characteristic of the target component.

21. A method comprising:processing a sample comprising a rare target component, for detection of the rare target component within a set of partitions comprising at least 30 million partitions within a single closed container, wherein processing the sample comprises:(a) generating a pre-amplified sample upon pre-amplifying the rare target component with a set of pre-amplification cycles;(b) generating a purified sample upon performing a purification operation with the preamplified sample;(c) distributing the purified sample across the set of partitions, wherein each partition of the set of partitions comprises a portion of the purified sample and processing materials;(d) reacting the processing materials of each partition of the set of partitions with the portion of the purified sample, thereby driving the rare target component of the sample to a level of detection of a detection system configured to scan the single closed container and count a set of positive partitions of the set of partitions, wherein a positive partition of the set of positive partitions emits a signal associated with the rare target component;(e) detecting the set of positive partitions upon scanning the single closed container; and (f) returning an analysis of the rare target component.

22. The method of claim 21, wherein the method does not comprise (b) generating a purified sample upon performing a purification operation with the pre-amplified sample.

23. The method of claim 21, wherein the rare target component comprises a mutation in a JAK2 gene, and wherein returning the analysis comprises characterizing a myeloproliferative neoplasm.

24. The method of claim 23, wherein the mutation in the JAK2 gene comprises a V617F mutation.

25. The method of claim 21, wherein each partition of the set of partitions comprises at most one rare target of the rare target component of the sample.

26. The method of claim 21, wherein the sample further comprises a background component.

27. The method of claim 26, wherein the background component comprises a J AK2 wild type background component.

28. The method of claim 21, wherein the set of pre-amplification cycles comprises at least a number of cycles such that reacting the processing materials of each partition of the set of partitions with the portion of the purified sample drives the rare target component of the sample to a low count range of the detection system configured to scan the single closed container, wherein the low count range is a range of 1 to 1000 targets.

29. The method of claim 21, wherein the set of pre-amplification cycles comprises at least a number of cycles such that reacting the processing materials of each partition of the set of partitions with the portion of the purified sample drives the rare target component of the sample to a level of detection of the detection system where the rare target component can be accurately detected.

30. The method of claim 29, wherein the set of pre-amplification cycles comprises at least 12 cycles.

31. The method of claim 30, wherein the set of pre-amplification cycles comprising at least 12 cycles improves the counts of the rare target component by at least 20-fold.

32. The method of claim 26, wherein returning the analysis comprises:returning a first abundance of the rare target component and a second abundance of the background component,and returning a relative abundance of the rare target component from the first abundance and the second abundance.33, The method of claim 26, wherein the method provides at least a 6-log dynamic range that enables the simultaneous quantification of the rare target component and the background component.34, The method of claim 26, wherein the processing materials comprise, for the rare target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the rare target component, and a first fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the first fluorophore-labeled oligonucleotide comprising a first fluorophore configured to transmit a first target signal if the target region is amplified.35, The method of claim 34, wherein the processing materials further comprise, for the background component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the background component, and a second fluorophore-labeled oligonucleotide corresponding to the flanking sequence, the second fluorophore-labeled oligonucleotide comprising a second fluorophore configured to transmit a second target signal if the target region is amplified.36, The method of claim 26, wherein the processing materials comprise, for the rare target component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the rare target component, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, the fluorophore-labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified.37, The method of claim 36, wherein the processing materials further comprise, for the background component, a primer set comprising: a common primer and a set of target-specific primers comprising a target-specific primer configured to interact with a target region of the background component, the target-specific primer having a common adapter sequence, and a fluorophore-labeled oligonucleotide corresponding to the common adapter sequence, thefluorophore- labeled oligonucleotide comprising a fluorophore configured to transmit a target signal if the target region is amplified.38, The method of claim 26, wherein the processing materials comprise, for the rare target component and the background component, a primer set comprising at least one primer configured to tag the rare target component with a first probe having a first fluorophore and the background component with a second probe having a second fluorophore.39, The method of claim 21, wherein the method lowers the detection threshold for the rare target component, wherein the lowered detection threshold for the rare target component comprises a limit of detection (LoD) for detection of the rare target component decreased by at least 2-fold.40, The method of claim 21, wherein the analysis provides a sensitivity for detection of the rare target component with a limit of blank (LoB) less than 0,005 and a limit of detection (LoD) less than 0.02 in relation to variant allele frequency (VAF) percentage.

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