Generating and implementing structural variation map genomes

Abstract

The present disclosure describes methods, non-transitory computer-readable media, and systems by which a structure variation map genome having alternating consecutive sequences representing a structure variant haplotype can be generated. For example, the disclosed system may identify candidate structural variants that meet an occurrence threshold within a genomic sample database. The systems select structural variant haplotypes from the candidate structural variants based on one or both of the following: the structural variant haplotypes satisfy a relative haplotype frequency, and finding that a flanking variant is adjacent to a particular structural variant haplotype. These systems may also select a reference haplotype from a reference genome corresponding to the selected structural variant haplotype. Based on the selected haplotypes, the disclosed system generates a structure variation map genome comprising both alternating consecutive sequences representing the structure variant haplotypes and reference sequences representing the reference haplotypes.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of and priority to U.S. Provisional Application No. 63 / 367,075, entitled “GENERATING AND IMPLEMENTING A STRUCTURAL VARIATION GRAPH GENOME,” filed on June 27, 2022, which is hereby incorporated by reference in its entirety. Background Art

[0003] In recent years, biotechnology companies and research institutions have improved the hardware and software for nucleotide sequencing and determining the nucleobase detection of genomic samples. For example, some existing sequencers and sequencing data analysis software (collectively referred to as "existing sequencing systems") predict each nucleobase in a sequence by using conventional Sanger sequencing or sequencing by synthesis (SBS) methods. When using SBS, existing sequencing systems can monitor thousands of oligonucleotides synthesized in parallel from templates to predict the nucleobase detection of growing nucleotide reads. Cameras in many existing sequencing systems capture images of irradiated fluorescent labels incorporated into oligonucleotides. After capturing such images, some existing sequencing systems determine the nucleobase detection of the nucleotide reads corresponding to the oligonucleotides and send the base detection data to a computing device with sequencing data analysis software, which compares the nucleotide reads with the reference genome. Based on the difference between the compared nucleotide reads and the reference genome, the existing system further utilizes a variant detector to identify variants of genomic samples, such as single nucleotide polymorphisms (SNPs), insertions or deletions (indels) or other variants.

[0004] Despite these recent advances, existing sequencing systems often generate or use reference genomes that misrepresent certain populations and result in inaccurate read alignments and erroneous variant calls. For example, some existing sequencing systems use linear reference genomes that are said to represent consensus sequences or examples of genes and other nucleotide sequences of an organism. But for the most common linear human reference genome (GRCh38 from the Genome Reference Consortium), approximately 93% of the primary assemblies are based on libraries from only 11 individuals, with 70% of linear human reference genomes coming from 1 individual. Therefore, existing systems use linear human reference genomes that do not frequently represent certain populations or common variants. In fact, many linear human reference genomes fail to represent larger deletions or insertions (e.g., indels of more than 50 base pairs), translocations, inversions, copy number variations (CNVs), or other structural variants.

[0005] To address this lack of genomic representation in a linear reference genome, some existing sequencing systems generate or use reference map genomes. For example, some reference map genomes include a linear reference genome and map amplifications or alternating continuous sequences representing SNPs or small indels (e.g., 10 or fewer base pairs, 50 or fewer base pairs). Although such reference map genomes better represent the genomes of some populations, the extended representation of existing reference map genomes omits larger indels, translocations, inversions, or other structural variations that are frequently carried by genomic samples - similar to the shortcomings of existing linear reference genomes.

[0006] Because existing linear reference genomes and map reference genomes fail to represent structural variants, existing sequencing systems frequently misalign nucleotide reads of more diverse genomic samples with the reference genome, and generate inaccurate variant or other nucleobase calls based on such misalignments. In fact, in some cases, existing linear reference genomes or map reference genomes lack map amplifications or alternating continuous sequences that represent structural variants that can be accurately aligned with nucleotide reads. Because existing reference genomes often fail to represent structural variants, existing sequencing systems also often fail to accurately determine when different segments of nucleotide reads are optimally aligned with different parts of an existing reference genome in a segmented alignment. As a result of such segmented alignments or other complex alignments with structural variants, existing sequencing systems frequently generate incorrect variant calls that incorrectly identify the presence or absence of structural variants or fail to provide information about related structural variants.

[0007] In order to compensate for the defects that some existing reference genomes cannot represent structural variants, some existing sequencing systems use existing reference genomes and SBS (or other technologies) for whole genome sequencing (WGS), and use genotype probes targeting specific structural variants for microarrays. In fact, microarrays have been specially designed to target structural variants that are difficult to detect using existing sequencing equipment. By running both WGS and multiple microarrays and often using different dedicated sequencing equipment and microarray equipment, existing sequencing systems have multiplied computer processing and time to determine accurate variant calls for the following items: (i) SNPs and smaller insertions and deletions, and (ii) structural variants.

[0008] Although some existing sequencing systems attempt to address the alignment accuracy and base calling accuracy issues of map reference genomes, existing map reference genomes typically include an over-amplification of alleles that are sufficiently similar (or unrelated) to the alleles exhibited by many or most genomic samples. For example, some existing sequencing systems utilize universal map genomes that include a large number of map amplifications for common alleles and uncommon alleles (such as common and uncommon SNPs and small insertions and deletions) across different populations. Because such map amplifications may be similar to but not match the alleles of many sample genomes, universal map genomes frequently cause existing sequencing systems to misalign or miss variants for a large number of samples. Therefore, by utilizing a universal map reference genome with excess map amplification, existing sequencing systems can increase the chances of mismatched alignments with nucleotide reads from genomic samples.

[0009] In addition to alignment accuracy and nucleobase accuracy issues, some existing map reference genomes are large and consume considerable memory and computing resources. In fact, some existing map reference genomes may include countless map amplifications of SNPs or small insertions and deletions that are not relevant to a given genomic sample. These countless alternative paths consume unnecessary memory. In addition to wasting memory, universal map reference genomes typically increase the computer processing time of existing sequencing systems to determine whether to include or exclude matches with map amplifications when performing variant calls.

[0010] These problems and challenges, along with additional problems and challenges, exist with existing sequencing systems. Summary of the invention

[0011] The present disclosure describes one or more embodiments of systems, methods, and non-transitory computer-readable storage media that solve one or more of the above-mentioned problems or provide other advantages over the prior art. Specifically, the disclosed system can generate or implement a structural variation map genome having an alternating continuous sequence representing a structural variant haplotype. For example, the disclosed system can identify candidate structural variants that meet an occurrence threshold within a genomic sample database. These systems select structural variant haplotypes from these candidate structural variants based on one or both of the following items: these structural variant haplotypes meet relative haplotype frequencies, and flanking variants are found to be adjacent to specific structural variant haplotypes. These systems can also select reference haplotypes corresponding to the selected structural variant haplotypes from the reference genome. Based on the selected haplotypes, these systems generate a structural variation map genome including alternating continuous sequences representing these structural variant haplotypes and reference sequences representing these reference haplotypes. Based on the comparison of the nucleotide reads of the genomic sample with the alternating continuous sequences representing the structural variant haplotypes, the disclosed system can determine the nuclear base detection (e.g., structural variant detection) of the genomic sample.

[0012] Additional features and advantages of one or more embodiments of the present disclosure will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of such exemplary embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The detailed description refers to the accompanying drawings which are briefly described below.

[0014] Figure 1 An environment in which a structural variant-aware sequencing system according to one or more embodiments of the present disclosure may operate is shown.

[0015] Figure 2A A schematic diagram of a structural variant-aware sequencing system according to one or more embodiments of the present disclosure is shown, which generates a structural variation map genome including alternating continuous sequences representing structural variant haplotypes and a reference sequence representing a reference haplotype.

[0016] Figure 2B A schematic diagram of a structural variant-aware sequencing system according to one or more embodiments of the present disclosure is shown, which aligns nucleotide reads of a genomic sample with a structural variation map genome and determines nucleobase calls of the genomic sample based on the aligned nucleotide reads.

[0017] Figure 3 A schematic diagram of a structural variant-aware sequencing system according to one or more embodiments of the present disclosure is shown, which selects structural variant haplotypes of target genomic regions for a structural variation map genome based on one or both of phasing criteria and region occurrence thresholds.

[0018] Figure 4 A structural variant-aware sequencing system for a genome using a hash table to combine a reference sequence from a reference genome, selected structural variant haplotypes, and selected alternate haplotypes into a structural variation map is shown according to one or more embodiments of the present disclosure.

[0019] Figure 5 A structural variant-aware sequencing system is shown that aligns nucleotide reads of a genomic sample with a structural variation map genome and determines nucleobase calls of the genomic sample based on the aligned nucleotide reads according to one or more embodiments of the present disclosure.

[0020] Figure 6 A client device displaying a graphical user interface including variant calls of structural variant haplotypes according to one or more embodiments of the present disclosure is shown.

[0021] Figure 7A table is shown according to one or more embodiments of the present disclosure, which displays different accuracy measures for: (i) a sequencing system determining variant calls for deletions and insertions of more than 50 base pairs using an existing map reference genome that lacks alternating contiguous sequences representing structural variants, and (ii) a structural variant-aware sequencing system determining structural variant calls for such deletions and insertions using a structural variation map genome.

[0022] Figure 8 A series of actions for generating a structural variation graph genome according to one or more embodiments of the present disclosure are shown.

[0023] Fig. 9 A series of actions for aligning nucleotide reads of a genomic sample with a structural variation map genome and determining nucleobase calls of the genomic sample based on the aligned nucleotide reads according to one or more embodiments of the present disclosure are shown.

[0024] Fig.10 A block diagram of an exemplary computing device is shown in accordance with one or more embodiments of the present disclosure. DETAILED DESCRIPTION

[0025] The present disclosure describes one or more embodiments of a structural variant-aware sequencing system that can generate a structural variation map genome with alternating continuous sequences that represent structural variant haplotypes selected from candidate structural variants. For example, a structural variant-aware sequencing system can identify candidate structural variants of a threshold frequency (or otherwise satisfy another occurrence threshold) within a genomic sample database. Such candidate structural variants may include deletions or insertions of base pairs exceeding a threshold number (e.g., 50), duplications, inversions, translocations, copy number variations (CNVs), or other structural variants. The structural variant-aware sequencing system selects structural variant haplotypes from these candidate structural variants based on one or both of the following: satisfying another occurrence threshold, and finding that the flanking variants are adjacent to a specific structural variant haplotype. The system can also select reference haplotypes of genomic regions corresponding to the selected structural variant haplotypes from a reference genome. Based on the selected haplotype, the system generates a structural variation map genome comprising alternating continuous sequences representing these structural variant haplotypes and reference sequences representing these reference haplotypes.

[0026] As described above, the structural variant-aware sequencing system can identify candidate structural variants from a genomic sample database based on an occurrence threshold. For example, the structural variant-aware sequencing system can identify candidate structural variants that meet a specific variant frequency or a minimum count in a genomic sample database. Such a genomic sample database may include a digital directory of nucleotide reads, whole genomes, exomes, exons, or other nucleotide sequences from different collections of genomic samples. When identifying candidate structural variants, the structural variant-aware sequencing system can identify deletions or insertions exceeding a threshold number of base pairs (e.g., >50 base pairs) or various other structural variants at various genomic regions across a linear reference genome. Within a genomic sample database, the structural variant-aware sequencing system can identify such candidate structural variants from long nucleotide reads or other continuous sequences.

[0027] In some specific implementations, the structural variant-aware sequencing system selects a structural variant haplotype from the identified candidate structural variants. For example, in some cases, the structural variant-aware sequencing system selects a structural variant haplotype that satisfies a threshold frequency or threshold count at a target genomic region corresponding to a candidate structural variant. Additionally or alternatively, the structural variant-aware sequencing system selects a structural variant haplotype that is in phase with a flanking variant within a continuous sequence of a genomic sample database. Such flanking variants may include SNPs or insertions and deletions that are less than a threshold number of base pairs (e.g., <50 base pairs).

[0028] After selecting the structural variant haplotype, in some embodiments, the structural variant-aware sequencing system integrates the structural variant haplotype and the reference haplotype from the linear reference genome into a data organization structure. For example, in certain implementations, the structural variant-aware sequencing system maps the reference haplotype, SNP, and structural variant haplotype from the linear reference genome to the genomic coordinates within the linear reference genome. The structural variant-aware sequencing system can also associate the nucleobase identifiers (e.g., letters A, T, C, G, U) of the mapped reference haplotype, SNP, and structural variant haplotype with values ​​representing the genomic coordinates in the organization structure (e.g., hash table, matrix).

[0029] In some embodiments, in addition to or as an alternative to generating a structural variation map genome, a structural variant-aware sequencing system determines nucleobase calls for a genomic sample based on comparing nucleotide reads of the genomic sample to the structural variation map genome. For example, in some embodiments, the structural variant-aware sequencing system identifies nucleotide reads from the genomic sample. The structural variant-aware sequencing system further aligns a subset of the nucleotide reads to an alternating contiguous sequence representing a structural variant haplotype within the structural variation map genome. Based on the aligned subset of nucleotide reads, the structural variant-aware sequencing system generates nucleobase calls (e.g., variant calls) for the genomic sample.

[0030] In addition to generating nucleobase calls, in some embodiments, the structural variant-aware sequencing system reports various data corresponding to the nucleobase calls that correspond to structural variant haplotypes. For example, in some cases, the structural variant-aware sequencing system generates an alignment file or a variant call file that includes an annotation indicating a structural variant haplotype, the frequency of the structural variant haplotype, or the genomic coordinates of the structural variant haplotype corresponding to the nucleobase call.

[0031] In addition to reporting variant calls corresponding to structural variants, structural variant-aware sequencing systems can better align and generate variant calls for split read alignments. As described above, structural variant-aware sequencing systems can determine when nucleotide reads are aligned to structural variant haplotypes. For example, in some cases, the structural variant-aware sequencing system determines that a subset of nucleotide reads overlaps with breakpoints of alternating continuous sequences representing structural variant haplotypes in a structural variation map genome. Based on detecting such overlaps, the structural variant-aware sequencing system generates an alignment file or variant call file with the following annotations indicating alignments reflecting structural variant haplotypes within a genomic sample.

[0032] As described above, structural variant-aware sequencing systems provide several technical advantages over existing sequencing systems by improving read alignment and base calling accuracy, computational efficiency, and memory consumption relative to existing sequencing systems. For example, structural variant-aware sequencing systems improve read alignment and base calling accuracy by generating or utilizing a structural variation map genome that explains structural variants. Unlike existing linear reference genomes or existing map reference genomes that cannot accurately or adequately represent structural variants, structural variant-aware sequencing systems can generate or implement structural variation map genomes that include alternating continuous sequences representing structural variant haplotypes. By selecting structural variant haplotypes that are respectively in phase with flanking variants within the continuous sequence, in some cases, the structural variant-aware sequencing system incorporates the structural variant haplotypes into alternating continuous sequences that promote better alignment between (i) nucleotide reads reflecting such flanking variants and structural variants and (ii) intelligently selected alternating continuous sequences of the structural variation map genome. By further or alternatively selecting structural variant haplotypes that meet an occurrence threshold at a targeted genomic region, in some cases, the structural variant-aware sequencing system incorporates the structural variant haplotypes into alternating contiguous sequences that effectively promote better alignment between nucleotide reads reflecting more common structural variant haplotypes and the selected alternating contiguous sequences of the structural variation map genome.

[0033] Regardless of the disclosed selection method, the alternating contiguous sequences of the structural variant-aware sequencing system facilitate improved alignment with nucleotide reads, thereby indicating larger insertions and deletions, translocations, inversions, CNVs, or other structural variants. Due to the improved alignment with the structural variation map genome, the structural variant-aware sequencing system can also determine more accurate nucleobase calls with higher confidence than existing sequencing systems, i.e., such calls match (or differ from) the reference bases of the reference genome. In fact, the disclosed structural variation map genome facilitates variant calls or other nucleobase calls that are not (or cannot) facilitated by existing reference genomes with the same quality (e.g., Q score) or mapping quality (e.g., MAPQ).

[0034] In addition to improving alignment and base calling accuracy, structural variant-aware sequencing systems also improve the computational speed and memory of some sequencing systems that use map reference genomes. Compared to a universal map reference genome that includes map amplifications of unrelated or excess alleles and arbitrarily selects to represent countless SNPs and / or small indels (e.g., 10 base pairs or less), the structural variant-aware sequencing system reduces the memory required to store a structural variation map genome that is relatively smaller than the countless map amplified genetic map reference genomes. The structural variant-aware sequencing system saves computer processing and other resources by using the structural variation map genome, rather than inefficiently using computing resources (such as processing and memory storage), to make decisions between an excessive number of possible read alignment matches and arbitrarily selected alternating consecutive sequences of SNPs, small indels, or structural variants in a hypothetical universal map reference genome. To conserve such computational resources, in some embodiments, the structural variation map genome includes (i) fewer (but more relevant) alternating contiguous sequences representing selected flanking variants and corresponding structural variant haplotypes for comparison to the genomic region of the sample, and (ii) more efficient mapping due to fewer candidate alternating contiguous sequence matches than a hypothetical universal map reference genome that includes a plurality of arbitrarily selected alternating contiguous sequences that include SNPs, small indels, or structural variants.

[0035] In addition to improving the computational efficiency of structural variation map genomes with targeted alternating continuous sequences, in some embodiments, structural variant-aware sequencing systems improve computational efficiency by reducing the number of sequencing analysis and computing devices used to determine variant calls for structural variants. As described above, some existing sequencing systems consume a large amount of computer processing and time by running the following two: (i) WGS on a dedicated sequencing device for generating nucleotide reads of a genomic sample, and (ii) multiple genotype microarrays on a microarray device. By comparing the nucleotide reads with the reference genome of the WGS and analyzing the optical signals from the DNA probes in the microarray, the existing sequencing systems can determine accurate variant calls for both SNPs and small insertions and deletions based on the reference genome on the one hand, and can determine targeted structural variants from DNA probes on the other hand. Compared to such existing sequencing systems, in some embodiments, the structural variant-aware sequencing system promotes a more efficient computational method by using a dedicated sequencing device for determining nucleotide reads without using or using less genotype microarrays for targeting structural variants to determine variant calls corresponding to structural variants. Thus, by generating or utilizing a structural variation map genome having alternating contiguous sequences representing structural variant haplotypes, a structural variant-aware sequencing system can eliminate some or all genotyping microarrays for structural variants.

[0036] As shown in the above discussion, the present disclosure utilizes a variety of terms to describe the features and advantages of structural variants sensing sequencing systems. As used herein, for example, the term "structural variant" refers to a variation (e.g., deletion, insertion, translocation, inversion) in the structure of an organism's chromosome or a variation in the nucleotide sequence of an organism's chromosome. In some cases, structural variants include variations in a threshold number of base pairs (e.g., >50 base pairs) within the chromosome of an organism. Therefore, in some specific implementations, structural variants include insertions or deletions exceeding a threshold number of base pairs, duplications exceeding a threshold number of base pairs, inversions, translocations, or copy number variations (CNVs). Although the present disclosure describes some examples of 50 base pairs as a threshold number of base pairs, in some embodiments, the threshold number of base pairs of structural variants may be different, such as 35, 45, 100, or 1,000 base pairs.

[0037] Relatedly, the term "candidate structural variant" refers to a structural variant selected from a genomic sample database. In some cases, the candidate structural variant includes a structural variant that satisfies a threshold amount of occurrence within a genomic sample database. For example, a candidate structural variant may include a structural variant from a genomic sample database that satisfies a threshold frequency or threshold count at a target genomic region (e.g., a gene or promoter region) of a nucleotide sequence within the genomic sample database.

[0038] As just noted, the structural variant-aware sequencing system can select candidate structural variants from a genomic sample database. As used herein, the term "genomic sample database" refers to a database of digitally represented nucleotide sequences from a genomic sample, the database including an organization, index, or search function for identifying variants, reference alleles, or reference haplotypes. For example, a genomic sample database may include (i) digitally represented nucleotide reads, whole genomes, exomes, exons, or other nucleotide sequences from different collections of genomic samples, and (ii) an organization or index of genomic coordinates or regions by which the digitally represented nucleotide sequences of variants or reference alleles or haplotypes can be identified. For illustration, in some embodiments, the genomic sample database includes one or more of the following: International Genome Sample Resource (IGSR) from the 1000 Genomes Project, Genome Aggregation Database (gnomAD), Database of Genomic Variants (DGV), or other databases including nucleotide sequences representing structural variants, such as databases including nucleotide reads of more than 300 base pairs. In some cases, the genomic sample database represents a subset of nucleotide sequences selected from one or more of the above databases or other databases.

[0039] As described above, in some embodiments, the structural variant-aware sequencing system selects a structural variant haplotype from candidate structural variants within a genomic sample database. As used herein, the term "structural variant haplotype" refers to a structural variant that is present in an organism (or an organism from a population) and is inherited from one or more ancestors as part of a set of nucleotide sequences. Specifically, a structural variant haplotype may include a set of alleles that include (or represent) one or more structural variants that are present in organisms of a population and tend to be inherited together by such organisms from a single parent. Therefore, a structural variant haplotype may include structural variants and other variants that are part of a set of alleles and that may correspond to a specific gene.

[0040] In contrast, the term "reference haplotype" refers to a set of nucleotide sequences represented by a reference genome inherited from one or more ancestors as part of a set of nucleotide sequences. Specifically, a reference haplotype may include a set of alleles from a linear reference genome that tend to be inherited together by such an organism from a single parent. In some cases, a reference haplotype includes a set of alleles corresponding to a gene.

[0041] As also used herein, the term "reference genome" refers to a digital nucleic acid sequence assembled as a representative example (or multiple representative examples) of genes and other genetic sequences of an organism. Regardless of the sequence length, in some cases, a reference genome represents an exemplary set of genes or a set of nucleic acid sequences determined to represent a digital nucleic acid sequence of an organism. For example, a linear human reference genome can be GRCh38 (or other versions of a reference genome) from the Genome Reference Alliance. Although GRCh38 may include alternating continuous sequences representing alternating haplotypes, such as SNPs and small insertions and deletions (e.g., 10 or fewer base pairs, 50 or fewer base pairs), GRCh38 includes alternating haplotypes with restricted representations of population structural variants. In fact, the structural variants represented in GRCh38 include only those structural variants represented by the 11 individuals on which its library GRCh38 is constructed.

[0042] Additionally, as used herein, the term "map reference genome" refers to a reference genome that includes both a linear reference genome and an alternating continuous sequence (or map amplification) representing a variant haplotype sequence or other variant or alternative nucleic acid sequence. For example, a map reference genome may include a linear reference genome and an alternating continuous sequence corresponding to one or more population haplotype sequences identified from a genomic sample database. As an example, a map reference genome may include the Illumina DRAGEN map reference genome hg19.

[0043] As disclosed herein, the term "structural variation map genome" refers to a map reference genome that includes alternating contiguous sequences representing structural variant haplotypes and reference sequences representing reference haplotypes. For example, in some embodiments, the structural variation map genome includes a linear reference genome supplemented with alternating contiguous sequences representing structural variant haplotypes. In addition to such alternating contiguous sequences, in some embodiments, the structural variation map genome includes alternating nucleobases or additional alternating contiguous sequences representing alternating haplotypes, such as SNPs and / or indels that are below a threshold number of base pairs (e.g., <50 base pairs). Although the present disclosure uses the term structural variation map genome, a structural variant-aware sequencing system may represent and use a structural variation map genome in the form of a graph hash table or other digitally organized structure.

[0044] As further used herein, the term "contig" (or "contig" for short) refers to a common nucleotide sequence of a genomic region of a genomic sample (or multiple genomic samples of a species), which is based on a collection of overlapping nucleotide segments corresponding to the genomic region. Specifically, a contiguous sequence includes a common nucleotide sequence of a genomic region of one or more genomic samples, which is based on nucleotide reads of one or more genomic samples covering (or overlapping) the genomic region.

[0045] Relatedly, the term "alternating contiguous sequence" (or simply "alternating contig") refers to a contiguous sequence representing a population haplotype added to a linear reference genome (or other reference genome) at one or more specific genomic coordinates (e.g., promoted to a linear reference genome). In some embodiments, a structural variation map genome may include alternating contiguous sequences of genomic coordinates mapped to a primary assembly of a linear reference genome. For example, an alternating contiguous sequence may represent a population haplotype comprising a promoted structural variant having two or more genomic coordinates corresponding to two or more flanks of a structural variant breakpoint in a linear reference genome. In some cases, a hash table for a structural variation map genome includes an identifier that associates an alternating contiguous sequence representing a structural variant haplotype with a genomic coordinate representing a reference haplotype from a primary assembly of a linear reference genome.

[0046] Additionally, as used herein, the term "genomic coordinates" refers to the specific position or location of a nucleotide base in a genome (e.g., a genome or reference genome of an organism). In some cases, the genomic coordinates include the identifier of the specific chromosome of the genome and the identifier of the position of the nucleotide base in the specific chromosome. For example, one or more genomic coordinates may include the numbering, name or other identifiers (e.g., chr1 or chrX) of the chromosome and one or more specific locations, such as the numbered position (e.g., chr1:1234570 or chr1:1234570-1234870) after the identifier of the chromosome. In addition, in some specific implementations, the genomic coordinates refer to the source of the reference genome (e.g., mitochondrial DNA reference genome mt or SARS-CoV-2 reference genome of SARS-CoV-2 virus) and the position of the nucleotide base in the source of the reference genome (e.g., mt:16568 or SARS-CoV-2:29001). In contrast, in some cases, the genomic coordinates refer to the position of the nucleotide base in the reference genome, without reference to chromosomes or sources (e.g., 29727).

[0047] As used herein, "genomic region" refers to the range of genomic coordinates. Like genomic coordinates, in some specific implementations, a genomic region can be identified by a chromosome identifier and one or more specific positions (such as the numbered position after the chromosome identifier, e.g., chr1:1234570-1234870). In various specific implementations, genomic coordinates include positions within a reference genome. In some cases, genomic coordinates are specific to a specific reference genome.

[0048] As further used herein, the term "reference sequence" refers to a nucleotide sequence from a reference genome. For example, a reference sequence includes a nucleobase sequence digitally represented by a primary assembly of a linear reference genome. As described above, in some embodiments, a reference sequence digitally represents a reference haplotype from a primary assembly of a linear reference genome.

[0049] As further used herein, the term "flanking variant" refers to one or more variant core bases that are inconsistent or different with one or more corresponding core bases of a reference genome and are adjacent to (or are part of) a structural variant haplotype in a nucleotide sequence. For example, a flanking variant includes one or more variant core bases that are inconsistent or different with one or more reference core bases and are in phase with a structural variant haplotype in a nucleotide sequence (e.g., a continuous sequence) from a genomic sample database. As described above, a flanking variant may include a SNP, a deletion less than a threshold number of base pairs, or an insertion less than a threshold number of base pairs. In some cases, a flanking variant may also be a structural variant.

[0050] As further used herein, the term "nucleobase call" (or simply "base call") refers to the determination or prediction of a specific nucleobase (or nucleobase pair) of a genomic coordinate of an oligonucleotide (e.g., a nucleotide read) or a sample genome during a sequencing cycle. Specifically, a nucleobase call can indicate: (i) the determination or prediction of the type of nucleobase that has been incorporated into an oligonucleotide on a nucleotide sample slide (e.g., a read-based nucleobase call); or (ii) the determination or prediction of the type of nucleobase present at a genomic coordinate or region within a genome, including variant calls or non-variant calls in a digital output file. In some cases, for a nucleotide read, a nucleobase call includes determining or predicting a nucleobase based on an intensity value generated by a fluorescently labeled nucleotide of an oligonucleotide added to a nucleotide sample slide (e.g., in a cluster of a flow cell). Alternatively, a nucleobase call includes determining or predicting a nucleobase based on chromatographic peaks or current changes generated by nucleotides passing through a nanopore of a nucleotide sample slide. In contrast, based on the nucleotide reads corresponding to the genomic coordinates, the nucleobase call may also include the nucleobase at the genomic coordinates of the sample genome of the final predicted variant call file (VCF) or another base call output file. Therefore, the nucleobase call may include base calls corresponding to the genomic coordinates and the reference genome, such as an indication of a variant or non-variant at a specific position corresponding to the reference genome. In fact, the nucleobase call may refer to a variant call, including but not limited to a single nucleotide variant (SNV), an insertion or deletion (indel), or a base call as part of a structural variant. As mentioned above, a single nucleobase call may be an adenine (A) call, a cytosine (C) call, a guanine (G) call, a thymine (T) call, or a uracil (U) call.

[0051] As further used herein, the term "nucleotide read" (or simply "read") refers to a sequence of one or more nucleobases (or nucleobase pairs) inferred from all or part of a sample nucleotide sequence (e.g., a sample genomic sequence, cDNA). Specifically, a nucleotide read includes a determined or predicted sequence of nucleobase calls from a nucleotide sequence (or a monoclonal nucleotide sequence set) of a sample library fragment corresponding to a genomic sample. For example, in some cases, a sequencing device determines a nucleotide read by generating nucleobase calls of nucleobases that pass through a nanopore of a nucleotide sample slide, by determining via fluorescent labeling, or by determining based on clusters in a flow cell.

[0052] As further used herein, the term "alignment score" refers to other quantitative measurements of the accuracy of a comparison between a nucleotide read or a fragment of the nucleotide read and another nucleotide sequence from a reference genome. Specifically, the alignment score includes a measure of the degree to which the core base of the indication nucleotide read matches or is similar to the reference sequence or alternating continuous sequence from the reference genome. In some specific implementations, the alignment score takes the form of a variation or version of the Smith-Waterman score or the Smith-Waterman score for local alignment, such as various settings or configurations used by Illumina, Inc. for the DRAGEN used for Smith-Waterman score.

[0053] Relatedly, the term "alt-contig fragment alignment score" refers to an alignment score for the alignment between one or more read fragments and an alternating continuous sequence. Specifically, the alternating contig fragment alignment score may include an alignment score for the alignment of one or more internal read fragments and one or more external read fragments of a nucleotide read to an alternating continuous sequence. As explained below, in some cases, the alternating contig fragment alignment score may replace or be used as the segmentation group score.

[0054] As further used herein, the term "alignment file" refers to a digital file indicating the relative alignment or mapping of nucleotide reads to a nucleotide sequence of a reference genome or other reference nucleotide sequence. Specifically, the alignment file may include data indicating the relative mapping position of nucleotide reads to a nucleotide sequence of a reference genome. In some embodiments, the alignment file includes or constitutes a sequence alignment / mapping (SAM) file, a binary alignment mapping (BAM) file, a FAST-All (FASTA) file, or a FASTQ file.

[0055] As used herein, for example, the term "configurable processor" refers to a circuit or chip that can be configured or customized to perform a specific application. For example, a configurable processor includes an integrated circuit chip designed to be configured or customized on-site by an end-user's computing device to perform a specific application. Configurable processors include, but are not limited to, ASICs, ASSPs, coarse-grained reconfigurable arrays (CGRAs), or FPGAs. In contrast, a configurable processor does not include a CPU or GPU. In some embodiments, a structural variant-aware sequencing system uses a configurable processor (e.g., FPGA) or a processor (e.g., CPU) to perform various embodiments described herein.

[0056] The following paragraphs describe the structural variant-aware sequencing system with respect to illustrative drawings depicting exemplary embodiments and specific implementations. For example, Figure 1 A schematic diagram of a computing system 100 in which a structural variant-aware sequencing system 106 operates according to one or more embodiments is shown. As shown, the computing system 100 includes a sequencing device 102 connected to a local device 108 (e.g., a local server device), one or more server devices 110, and a client device 114. Figure 1 As shown, sequencing device 102, local device 108, server device 110, and client device 114 can communicate with each other via network 118. Network 118 includes any suitable network over which computing devices can communicate. Fig.10 The exemplary network is discussed in more detail. Figure 1 An embodiment of a structural variant-aware sequencing system 106 is shown, but the present disclosure describes the following alternative embodiments and configurations.

[0057] like Figure 1 As indicated, the sequencing device 102 includes a computing device or sequencing device system 104 for sequencing a genomic sample or other nucleic acid polymer. In some embodiments, the sequencing device 102 analyzes nucleotide fragments or oligonucleotides extracted from the genomic sample by executing the sequencing device system 104 using a processor to generate nucleotide reads or other data directly or indirectly on the sequencing device 102 using computer-implemented methods and systems. More specifically, the sequencing device 102 receives a nucleotide sample slide (e.g., a flow cell) including nucleotide fragments extracted from the sample, and then copies and determines the nucleobase sequence of such extracted nucleotide fragments.

[0058] In one or more embodiments, the sequencing device 102 utilizes SBS to sequence nucleotide fragments into nucleotide reads and determine the nucleobase calls of the nucleotide reads. In addition or alternatively to communicating across the network 118, in some embodiments, the sequencing device 102 bypasses the network 118 and communicates directly with the local device 108 or the client device 114. By executing the sequencing device system 104, the sequencing device 102 may also store the nucleobase calls as part of the base call data formatted as a binary base call (BCL) file and send the BCL file to the local device 108 and / or the server device 110.

[0059] like Figure 1 As further indicated, the local device 108 is located at or near the same physical location as the sequencing device 102. In fact, in some embodiments, the local device 108 and the sequencing device 102 are integrated into the same computing device. The local device 108 can operate the structural variant-aware sequencing system 106 to generate, receive, analyze, store, and transmit digital data, such as by receiving base call data or determining variant calls based on analyzing such base call data. Figure 1 As shown, the sequencing device 102 can send (and the local device 108 can receive) base call data generated during a sequencing run of the sequencing device 102. By executing software in the form of a structural variant-aware sequencing system 106, the local device 108 can align the nucleotide reads with the structural variation map genome 112 and determine genetic variations based on the aligned nucleotide reads. The local device 108 can also communicate with a client device 114. Specifically, the local device 108 can send data to the client device 114, which includes a variant call file (VCF) or other information indicating a nuclear base call, sequencing metrics, error data, or other metrics.

[0060] like Figure 1 As further indicated, the server device 110 is located remotely from the local device 108 and the sequencing device 102. Similar to the local device 108, in some embodiments, the server device 110 includes a version of the structural variant-aware sequencing system 106. Thus, the server device 110 can generate, receive, analyze, store, and transmit digital data, such as by receiving base call data or determining variant calls based on analyzing such base call data. As described above, the sequencing device 102 can send (and the server device 110 can receive) base call data from the sequencing device 102. The server device 110 can also communicate with the client device 114. Specifically, the server device 110 can send data to the client device 114, which includes VCF or other sequencing-related information.

[0061] In some embodiments, server device 110 comprises a distributed server collection, where server device 110 includes many server devices distributed across network 118 and located in the same or different physical locations. In addition, server device 110 may include a content server, an application server, a communication server, a web hosting server, or another type of server.

[0062] As described above, as part of the server device 110 or the local device 108, the structural variant-aware sequencing system 106 can generate or implement a structural variation map genome having alternating continuous sequences representing structural variant haplotypes. For example, the structural variant-aware sequencing system 106 can identify candidate structural variants of a threshold frequency (or otherwise satisfying another occurrence threshold) within a genomic sample database. The structural variant-aware sequencing system 106 selects a structural variant haplotype from these candidate structural variants based on one or both of the following items: satisfying another occurrence threshold, and finding that the flanking variant is adjacent to a specific structural variant haplotype. The structural variant-aware sequencing system 106 can also select a reference haplotype of a genomic region corresponding to the selected structural variant haplotype from a reference genome. Based on the selected haplotype, the structural variant-aware sequencing system 106 generates a structural variation map genome including both alternating continuous sequences representing these structural variant haplotypes and reference sequences representing these reference haplotypes. Based on a comparison of the nucleotide reads of the genomic sample with the alternating continuous sequences representing the structural variant haplotypes, the structural variant-aware sequencing system 106 can determine the nucleobase calls of the genomic sample.

[0063] like Figure 1 As further shown and indicated, by executing the sequencing application 116, the client device 114 can generate, store, receive and send digital data. Specifically, the client device 114 can receive sequencing data from the local device 108, or receive a call file (e.g., BCL) and sequencing metrics from the sequencing device 102. In addition, the client device 114 can communicate with the local device 108 or the server device 110 to receive a VCF, which includes nuclear base calls and / or other metrics, such as base call quality metrics or passband filter metrics. The client device 114 can accordingly present or display information related to variant calls or other nuclear base calls to a user associated with the client device 114 within a graphical user interface of the sequencing application 116. For example, the client device 114 can present structural variant calls and / or sequencing metrics for sequenced genomic samples within a graphical user interface of the sequencing application 116.

[0064] although Figure 1The client device 114 is depicted as a desktop computer or laptop computer, but the client device 114 may include various types of client devices. For example, in some embodiments, the client device 114 includes a non-mobile device, such as a desktop computer or server, or other types of client devices. In still other embodiments, the client device 114 includes a mobile device, such as a laptop, tablet computer, mobile phone, or smartphone. Fig.10 Additional details regarding client device 114 are discussed.

[0065] like Figure 1 As further shown, the client device 114 includes a sequencing application 116. The sequencing application 116 may be a web application or a native application (e.g., a mobile application, a desktop application) stored and executed on the client device 114. The sequencing application 116 may include instructions that, when executed, cause the client device 114 to receive data from the structural variant-aware sequencing system 106 and present base call data or data from the VCF for display at the client device 114. In addition, the sequencing application 116 may direct the client device 114 to display a summary for a plurality of sequencing runs.

[0066] like Figure 1 As further shown, a version of the structural variant-aware sequencing system 106 may be located and implemented (e.g., completely or partially) on a client device 114 or a sequencing device 102. In yet other embodiments, the structural variant-aware sequencing system 106 is implemented by one or more other components of the computing system 100, such as a local device 108. Specifically, the structural variant-aware sequencing system 106 may be implemented in a variety of different ways across the sequencing device 102, the local device 108, the server device 110, and the client device 114. For example, the structural variant-aware sequencing system 106 may be downloaded from the server device 110 to the structural variant-aware sequencing system 106 and / or the local device 108, wherein all or part of the functionality of the structural variant-aware sequencing system 106 is executed at each corresponding device within the computing system 100.

[0067] As described above, the structural variant-aware sequencing system 106 can generate and implement a structural variation graph genome. Figure 2A and Figure 2B An overview of such an embodiment of a structural variant-aware sequencing system 106 is depicted. According to one or more embodiments, Figure 2A An example of a structural variant-aware sequencing system 106 for generating a structural variation map genome 212 including alternating contiguous sequences representing structural variant haplotypes and reference sequences representing reference haplotypes is shown. According to one or more embodiments, Figure 2BAn example of a structural variant-aware sequencing system 106 that aligns nucleotide reads of a genomic sample to a structural variation map genome 212 and determines nucleobase calls for the genomic sample based on the aligned nucleotide reads is shown.

[0068] like Figure 2A As shown, the structural variant-aware sequencing system 106 identifies candidate structural variants 204a to 204n from the genomic sample database 202 based on an occurrence threshold. For example, the structural variant-aware sequencing system 106 identifies candidate structural variants 204a to 204n that meet a threshold amount of occurrences within the genomic sample database 202. By selecting structural variants that meet a threshold count (e.g., 3 or more occurrences) or a threshold frequency (e.g., 10%, 30% variant frequency) at the target genome coordinates in the genomic sample database 202, in some specific implementations, the structural variant-aware sequencing system 106 selects candidate structural variants 204a to 204n from the genomic sample database 202. As described above, the genomic sample database 202 may include a variety of databases that include nucleotide reads from different collections of genomic samples, such as a combination of one or more of IGSR, gnomAD, or DGV from the 1000 Genomes Project.

[0069] like Figure 2A As further indicated, the structural variant-aware sequencing system 106 identifies multiple structural variant types in the candidate structural variants 204a to 204n. Based on satisfying a threshold amount of occurrences, for example, the structural variant-aware sequencing system 106 identifies candidate structural variants 204a and 204c that exhibit deletions exceeding a threshold number of base pairs; candidate structural variants 204b and 204d that exhibit translocations; candidate structural variants 204f and 204g that exhibit insertions exceeding a threshold number of base pairs; and candidate structural variants 204e and 204n that exhibit duplications exceeding a threshold number of base pairs. For illustrative purposes and space limitations, Figure 2A The candidate structural variants 204a to 204n are depicted as examples only. The structural variant-aware sequencing system 106 can identify different types of structural variants (e.g., translocations, CNVs) and structural variants not found in the genomic sample database 202. Figure 2A Additional structural variants are depicted in .

[0070] like Figure 2AAs further shown, the structural variant-aware sequencing system 106 selects structural variant haplotypes from the candidate structural variants 204a to 204n. In some cases, the structural variant-aware sequencing system 106 selects structural variant haplotypes that meet a threshold amount of additional occurrences at a particular genomic region, as classified in the genomic sample database 202. For example, in some implementations, the structural variant-aware sequencing system 106 selects structural variant haplotypes that meet a threshold variant frequency (e.g., 15%, 25%) or a threshold count (3 times, 10 times) at the target genomic coordinates corresponding to the candidate structural variants 204a to 204n.

[0071] In addition or alternatively to the occurrence threshold, in some embodiments, the structural variant-aware sequencing system 106 selects structural variant haplotypes that are adjacent to flanking variants within the continuous sequence of the genomic sample database 202. In some cases, these flanking variants are in phase with the corresponding structural variant haplotypes in the nucleotide sequence of the genomic sample database 202. Figure 2A As indicated, for example, the structural variant-aware sequencing system 106 determines that the candidate structural variant 204c is in phase with the flanking variant 206a within the continuous sequence (or other nucleotide sequence) of the genomic sample database 202. Similarly, the structural variant-aware sequencing system 106 determines that the candidate structural variant 204d is in phase with the flanking variant 206b, the candidate structural variant 204g is in phase with the flanking variants 206c and 206d, and the candidate structural variant 204n is in phase with the flanking variant 206e - each flanking variant is located within a corresponding continuous sequence (or other nucleotide sequence) of the genomic sample database 202. Therefore, as Figure 2A As indicated by the dashed circle, in some embodiments, the structural variant-aware sequencing system 106 selects candidate structural variants 204c, 204d, 204g, and 204n as structural variant haplotypes to include in the structural variation map genome 212.

[0072] In addition to selecting candidate structural variants 204c, 204d, 204g and 204n as structural variant haplotypes, as Figure 2A As further shown, the structural variant-aware sequencing system 106 identifies reference haplotypes 210a to 210n corresponding to the selected structural variant haplotypes from the linear reference genome 208. For example, in some cases, the structural variant-aware sequencing system 106 identifies the reference haplotypes 210a to 210n at the genomic coordinates of the linear reference genome 208 corresponding to the selected structural variant haplotypes. In practice, the structural variant-aware sequencing system 106 can identify the genomic coordinates of the reference haplotypes 210a to 210n at which the selected variant haplotypes are incorporated into the structural variation map genome 212 as liftover groups.

[0073] like Figure 2A As further shown, the structural variant-aware sequencing system 106 generates a structural variation map genome 212. As shown, the structural variation map genome 212 includes alternating continuous sequences 214a, 214b, 214c, and 214n representing the selected structural variant haplotype. In some embodiments, one or more of these alternating continuous sequences also include flanking variants 206a to 206e.

[0074] To organize different structural variant haplotypes for a particular genomic region, in some cases, the structural variant-aware sequencing system 106 generates the structural variation map genome 212 by sorting different subsets of alternating contiguous sequences corresponding to different genomic regions according to the frequencies of structural variants within the genomic sample database 202. Thus, in some cases, the structural variant-aware sequencing system 106 generates the structural variation map genome 212 by (i) sorting a first subset of alternating contiguous sequences corresponding to a first genomic region according to the frequencies within the genomic sample database 202; and (ii) sorting a second subset of alternating contiguous sequences corresponding to a second genomic region according to the frequencies within the genomic sample database 202.

[0075] like Figure 2A As further shown, the structural variation map genome 212 includes reference sequences 216a, 216b, 216c, and 216n representing reference haplotypes corresponding to selected structural variant haplotypes. Indeed, in some embodiments, the structural variation map genome 212 includes and is backward compatible with the linear reference genome 208. As further explained below, in some embodiments, the structural variant-aware sequencing system 106 generates the structural variation map genome 212 by constructing a hash table or other organizational structure.

[0076] In addition or alternatively to generating the structural variation map genome 212, in some embodiments, the structural variant-aware sequencing system 106 aligns nucleotide reads of a genomic sample with the structural variation map genome 212 and determines nucleobase calls for the genomic sample based on the aligned nucleotide reads. Figure 2B An example of one such implementation of the structural variation graph genome 212 is depicted. Figure 2BAs shown, the structural variant-aware sequencing system 106 identifies or receives nucleotide reads 218 of a genomic sample. In some cases, for example, the structural variant-aware sequencing system 106 receives base call data (e.g., a BCL file or a FASTQ file) from a sequencing device that has sequenced oligonucleotides extracted from the genomic sample and determined individual nucleobase calls of the nucleotide reads 218 in the base call data. Depending on the type of sequencing performed, in some embodiments, the structural variant-aware sequencing system 106 identifies single end reads or paired end reads as well as short nucleotide reads (e.g., <300 base pairs or <10,000 base pairs) or long nucleotide reads (e.g., >300 base pairs or >10,000 base pairs) as nucleotide reads 218.

[0077] like Figure 2B As further shown, the structural variant-aware sequencing system 106 aligns the nucleotide reads 218 with different sequences of the structural variation map genome 212. Specifically, the structural variant-aware sequencing system 106 aligns a subset 220 of the nucleotide reads from the nucleotide reads 218 with the alternating contiguous sequences 214b of the structural variation map genome 212. Figure 2B As shown, some or all of the subset 220 of nucleotide reads overlap with the alternating contiguous sequence 214b. In this particular example, the subset 220 of nucleotide reads overlaps with the alternating contiguous sequence 214b representing a candidate structural variant 204f (ie, an insertion of more than a threshold number of bases).

[0078] In addition to the alternating contiguous sequence 214b, in some embodiments, the structural variant-aware sequencing system 106 aligns different subsets of nucleotide reads of the genomic sample to one or more of the alternating contiguous sequences 214a, 214c, or 214n or reference sequences 216a to 216n of the structural variation map genome 212. Thus, in some specific implementations, the structural variant-aware sequencing system 106 aligns certain nucleotide reads to alternating contiguous sequences representing different types of structural variant haplotypes (including, but not limited to, insertions, deletions, duplications, inversions, translocations, or CNVs). Likewise, in some cases, the structural variant-aware sequencing system 106 aligns certain nucleotide reads to a reference sequence representing a reference haplotype from a linear reference genome.

[0079] like Figure 2BAs further shown, the structural variant-aware sequencing system 106 determines the nucleobase calls 222 of the genomic sample based on the alignment of the subset 220 of nucleotide reads with the alternating continuous sequence 214b. For example, the structural variant-aware sequencing system 106 generates one or more variant calls corresponding to the structural variant haplotype represented by the alternating continuous sequence 214b. The structural variant-aware sequencing system 106 determines such variant calls in part because the alignment of the subset 220 of nucleotide reads with the alternating continuous sequence 214b exhibits a better mapping metric, base call quality metric, or other sequencing metric than the alignment of the subset 220 of nucleotide reads with the reference sequence 216b. In some embodiments, the structural variant-aware sequencing system 106 generates a variant call file 224 including the nucleobase calls 222 and other nucleobase calls based on the read alignment.

[0080] As described above, the structural variant-aware sequencing system 106 can select structural variant haplotypes from a genomic sample database to include in a structural variation map genome. According to one or more embodiments, Figure 3 The structural variant-aware sequencing system 106 is shown selecting a structural variant haplotype for a target genomic region of a structural variation map genome based on one or both of a phasing criterion 308 and a region occurrence threshold 310. Figure 3 , but in some implementations, the structural variant-aware sequencing system 106 also selects structural variant haplotypes for other target genomic regions to be included in the structural variation map genome consistent with the following disclosure.

[0081] like Figure 3 As shown, the structural variant-aware sequencing system 106 identifies candidate structural variants from a genomic sample database 300. Consistent with the above disclosure, the genomic sample database 300 may include long nucleotide reads (e.g., reads>300 base pairs or>1,000 base pairs) containing various structural variants. In some embodiments, the genomic sample database 300 includes continuous sequences from different collections of genomic samples containing structural variants (e.g., from different geographic regions or countries in the world). In fact, the genomic sample database 300 may include continuous sequences organized according to haplotypes containing one or more structural variants. As explained below, the structural variant-aware sequencing system 106 may utilize some such continuous sequences that include flanking variants in phase with the corresponding structural variant haplotypes for improved alignment, mapping, and base calling.

[0082] like Figure 3As depicted, in some embodiments, the structural variant-aware sequencing system 106 identifies candidate structural variants based on a population occurrence threshold 301. The population occurrence threshold 301 provides an example of a threshold amount of occurrence. For example, the structural variant-aware sequencing system 106 identifies candidate structural variants that occur at a threshold frequency or above a threshold frequency within a population represented by a genomic sample database 300. In some cases, the threshold frequency constitutes a specific percentage (e.g., 1%, 5%) of genomic samples represented by a continuous sequence (or other nucleotide sequence) within the genomic sample database 300. Additionally or alternatively, the structural variant-aware sequencing system 106 identifies candidate structural variants that occur at a threshold count or above a threshold count within a genomic sample represented by a continuous sequence (or other nucleotide sequence) within the genomic sample database 300. In some cases, the threshold count constitutes a specific number (e.g., 3, 10, 25, 100) of genomic samples represented by such continuous sequences or other nucleotide sequences within the genomic sample database 300.

[0083] In addition to generally identifying candidate structural variants from a population, in some embodiments, the structural variant-aware sequencing system 106 determines candidate structural variants corresponding to specific genomic regions. Figure 3 As shown, for example, the structural variant-aware sequencing system 106 identifies a candidate structural variant 302 for a target genomic region 314. In some cases, the target genomic region 314 represents a gene, a promoter region, or other genomic region.

[0084] For a given target genomic region, the structural variant-aware sequencing system 106 can identify different types of candidate structural variants. Figure 3 As shown, for example, the structural variant-aware sequencing system 106 identifies candidate structural variants 302 for a target genomic region 314. Based on satisfying a population occurrence threshold 301, the structural variant-aware sequencing system 106 identifies, for the target genomic region 314, candidate structural variants 304a and 304b that exhibit deletions exceeding a threshold number of base pairs (e.g., <50, 100, or 1,000 base pairs); candidate structural variants 304c and 304d that exhibit duplications exceeding a threshold number of base pairs; candidate structural variants 304e and 304f that exhibit insertions exceeding a threshold number of base pairs; candidate structural variants 304g and 304h that exhibit inversions; and candidate structural variants 304i and 304j that exhibit translocations.

[0085] For illustrative purposes and space limitations, Figure 3 The candidate structural variants 204a to 204n for the target genomic region 314 are depicted for example only. The structural variant-aware sequencing system 106 can identify different types of structural variants (e.g., CNVs) and the like from the genomic sample database 300. Figure 3 Similarly, in some embodiments, the structural variant-aware sequencing system 106 can identify different sets of candidate structural variants (or no candidate structural variants) for different target genomic regions corresponding to the genomic coordinates of the linear reference genome from the genomic sample database 300.

[0086] In addition to identifying the candidate structural variants 302, in some embodiments, the structural variant-aware sequencing system 106 selects structural variant haplotypes 312 from the candidate structural variants 302 based on one or both of the phasing criteria 308 and the region occurrence threshold 310. For example, in some implementations, the structural variant-aware sequencing system 106 selects the structural variant haplotypes 312 based on the phasing criteria 308 by selecting the structural variant haplotypes that are in phase with the flanking variants within the continuous sequence, respectively. Figure 3 As shown, candidate structural variants 304b, 304d, 304f, 304h, and 304j are in phase with flanking variants 306a, 306b, 306c, 306d, and 306e, respectively, which are adjacent to candidate structural variants 304b, 304d, 304f, 304h, and 304j within the corresponding continuous sequence. In contrast, candidate structural variants 304a, 304e, 304e, 304g, and 304i are not in phase with the flanking variants within the corresponding continuous sequence. Therefore, in some embodiments, the structural variant-aware sequencing system 106 selects candidate structural variants 304b, 304d, 304f, 304h, and 304j as the structural variant haplotype 312 of the target genomic region 314. In some such embodiments, the structural variant-aware sequencing system 106 excludes candidate structural variants 304a, 304e, 304e, 304g, and 304i from consideration or filters them out.

[0087] By selecting structural variant haplotypes that are in phase with flanking variants within a contiguous sequence or other nucleotide sequence, respectively, the structural variant-aware sequencing system 106 can select such structural variant haplotypes: these structural variant haplotypes promote better mapping and alignment with nucleotide reads in the structural variation map genome compared to other structural variant haplotypes lacking such phased flanking variants. When the structural variation map genome includes structural variant haplotypes with such phased flanking variants, when the nucleotide reads also include flanking variants that are also represented by the alternating contiguous sequence of the structural variation map genome, the structural variant-aware sequencing system 106 is more likely to align nucleotide reads of a genomic sample including some or all of the corresponding structural variants. When mapping to an alternating contiguous sequence with a flanking variant of a structural variation map genome, the structural variant-aware sequencing system 106 is also more likely to determine that the mapping and alignment of the nucleotide read to the alternating contiguous sequence has a relatively high mapping quality metric (e.g., MAPQ) and local alignment score (e.g., Smith-Waterman score) compared to the mapping and alignment to a reference sequence (or other alternating contiguous sequence) lacking such flanking variants.

[0088] In addition or alternatively to the phasing criteria 308, the structural variant-aware sequencing system 106 selects a structural variant haplotype 312 from the candidate structural variants 302 based on a regional occurrence threshold 310. The regional occurrence threshold 310 provides another example of an occurrence threshold amount. For example, the structural variant-aware sequencing system 106 selects a structural variant haplotype 312 by selecting a candidate structural variant that occurs at a threshold frequency or above a threshold frequency at the target genomic region 314. In some cases, the threshold frequency constitutes a specific percentage (e.g., 10%, 25%) of the genomic samples represented by a continuous sequence (or other nucleotide sequence) for the target genomic region 314 within the genomic sample database 300 (e.g., having at least one overlapping genomic coordinate of the target genomic region 314). Additionally or alternatively, the structural variant-aware sequencing system 106 selects a structural variant haplotype 312 by selecting a candidate structural variant that occurs at a threshold count or above a threshold count within a continuous sequence (or other nucleotide sequence) for the target genomic region 314 within the genomic sample database 300 (e.g., at least one overlapping genomic coordinate). In some cases, the threshold count constitutes a particular number (eg, 3, 10, 15) of contiguous or other nucleotide sequences corresponding to target genomic region 314 .

[0089] By selecting structural variant haplotypes based on one or both of the phasing criteria 308 and the region occurrence threshold 310, in some cases, the structural variant-aware sequencing system 106 improves the computational speed and memory of sequencing systems using certain map reference genomes. Compared to a universal map reference genome that would include alternating contiguous sequences of mostly unrelated or excess alleles at target genomic regions, the structural variant-aware sequencing system 106 reduces the memory required to maintain a relatively small structural variation map genome in terms of more targeted alternating contiguous sequences and corresponding structural variant haplotypes. In some embodiments, the structural variant-aware sequencing system 106 intelligently selects targeted alternating contiguous sequences representing structural variant haplotypes based on one or both of the phasing criteria 308 and the region occurrence threshold 310, rather than a plurality of alternating contiguous sequences randomly selected in the universal map reference genome.

[0090] After selecting the structural variant haplotype and other alternate haplotypes, the structural variant-aware sequencing system 106 can generate a structural variation map genome using the digital tissue structure. According to one or more embodiments, Figure 4 A structural variant-aware sequencing system 106 for combining a reference sequence, selected structural variant haplotypes, and selected alternate haplotypes from a reference genome into a structural variation graph genome using a graph hash table is shown. As explained below, the graph hash table associates the encoded nucleotide sequence of the reference sequence, the selected structural variant haplotypes, and the selected alternate haplotypes with genomic coordinates.

[0091] In addition to choosing Figure 2B or Figure 3 In addition to the depicted structural variant haplotypes, in some embodiments, the structural variant-aware sequencing system 106 identifies or selects an alternate haplotype for inclusion in a structural variation map genome. For example, in some cases, the structural variant-aware sequencing system 106 selects one or more of a SNP, a deletion of less than a threshold number of base pairs (e.g., >50 base pairs), or an insertion of less than a threshold number of base pairs from a genomic sample database. Such alternate haplotypes differ from structural variant haplotypes in size and (in some cases) kind. Consistent with the above disclosure, in some such cases, the structural variant-aware sequencing system 106 selects alternate haplotypes based on a regional occurrence threshold for a target genomic region of a linear reference genome. After selecting an alternate haplotype, in some embodiments, the structural variant-aware sequencing system 106 generates a structural variation map genome comprising: (i) a reference sequence representing a reference haplotype, (ii) an alternate continuous sequence representing a selected structural variant haplotype, and (iii) an alternate nucleobase or additional alternate continuous sequence representing a selected alternate haplotype.

[0092] In order to organize and associate such reference sequences, alternating nucleobases, and alternating continuous sequences, in some embodiments, the structural variant-aware sequencing system 106 generates a digital organizational structure that associates the above-mentioned reference sequences and alternating sequences with genomic coordinates. For example, in some specific implementations, the structural variant-aware sequencing system 106 generates an alignment file that maps the selected structural variant haplotype to the genomic coordinates of the selected reference haplotype within the linear reference genome. In some cases, the alignment file constitutes a sequence alignment / mapping (SAM) promotion file. By utilizing the alignment file, the structural variant-aware sequencing system 106 generates a structural variation map genome by associating an identifier (e.g., a single letter code, a binary code) representing an alternating continuous sequence of a structural variant haplotype with the value of the genomic coordinates of the reference haplotype within an organizational structure (e.g., a hash table).

[0093] In order to integrate the reference sequence and the alternate nucleobase or additional alternate continuous sequence representing the reference haplotype, in some embodiments, the structural variant-aware sequencing system 106 also generates a file representing the nucleobase or nucleotide sequence of the reference haplotype and the selected alternate haplotype. For example, the structural variant-aware sequencing system 106 generates a sequence file representing the reference genome including the reference haplotype and a variant call file representing the selected alternate haplotype. In some embodiments, by utilizing the sequence file, the alignment file, and the variant call file, the structural variant-aware sequencing system 106 generates a structural variation map genome by associating the nucleobase identifiers of the following items with the values ​​of the genomic coordinates representing the reference haplotype within a hash table: (i) a reference sequence representing the reference haplotype, (ii) an alternate continuous sequence representing the selected structural variant haplotype, and (iii) an alternate nucleobase or additional alternate continuous sequence.

[0094] Figure 4 The structural variant-aware sequencing system 106 is shown as generating a graph hash table 422 based on the corresponding files as such an organizational structure. Figure 4 As shown, for example, the structural variant-aware sequencing system 106 identifies a reference genome 402, such as a linear reference genome. For example, the structural variant-aware sequencing system 106 identifies GRCh38 (or other versions of the reference genome) from the Genome Reference Consortium as the reference genome 402. Based on the reference genome 402, the structural variant-aware sequencing system 106 generates a reference genome sequence file 404 including an encoded version of the reference genome 402. For example, in some embodiments, the structural variant-aware sequencing system 106 generates a FASTA format file as the reference genome sequence file 404. Such a FASTA file includes text with single-letter codes (e.g., A, C, T, G, U, R, Y, M, S, W) that represent the nucleobases (e.g., A, C, T, G) of the nucleotide sequence of the reference genome 402.

[0095] In addition to the reference genome 402, such as Figure 4 As further shown, the structural variant-aware sequencing system 106 identifies candidate structural variants 406 from the genomic sample database and selects structural variant haplotypes 408 from the candidate structural variants 406 for inclusion in the structural variation map genome. For example, the structural variant-aware sequencing system 106 uses Figure 3 The method shown and described above is used to select structural variant haplotype 408. Thus, in some cases, structural variant haplotype 408 includes a structural variant haplotype that is in phase with a flanking variant (e.g., SNP or indel) within the contiguous sequence.

[0096] Based on the structural variant haplotype 408, the structural variant-aware sequencing system 106 generates a structural variant (SV) haplotype alignment file 410. For example, the structural variant-aware sequencing system 106 generates a sequence alignment / mapping (SAM) boost file that maps the structural variant haplotype 408 to the genomic coordinates of the corresponding reference haplotype within the reference genome 402. By generating the SAM boost file, the structural variant-aware sequencing system 106 generates a file that maps the structural variant haplotype 408 to genomic coordinates for which alternating consecutive sequences will form boost groups in the structural variation map genome. Alternatively, the structural variant-aware sequencing system 106 generates a binary alignment mapping (BAM) file compressed into a binary format, such as a mapping of the structural variant haplotype to the genomic coordinates of the corresponding reference haplotype.

[0097] Based on structural variant haplotype 408, e.g. Figure 4 As further shown, the structural variant-aware sequencing system 106 generates a structural variant (SV) haplotype sequence file 412. For example, in some embodiments, the structural variant-aware sequencing system 106 generates a FASTA formatted file as the SV haplotype sequence file 412. Such a FASTA file includes text with single-letter codes representing individual nucleobases of the nucleotide sequence of the structural variant haplotype 408. In some cases, the FASTA file includes a descriptor or other header that identifies the target genomic region of each structural variant haplotype.

[0098] like Figure 4As further shown, the structural variant-aware sequencing system 106 identifies candidate alternate haplotypes 414. For example, in some cases, the structural variant-aware sequencing system 106 selects SNPs or indels with a threshold number of base pairs in a low-confidence call region of the reference genome 402. For illustration, a low-confidence call region may include a genomic region containing (in whole or in part) a variable number of tandem repeats (VNTRs), insertions, or deletions, or a region with a variety of different variations. Low-confidence call regions may also include genomic regions that have historically resulted in the following nucleobase calls that exhibit low-quality sequencing metrics, such as below-threshold base call quality metrics (e.g., Q20, Q30, Q37) or threshold mapping quality metrics (e.g., relative MAPQ score or MAPQ 40). Consistent with the above disclosure, in some embodiments, the structural variant-aware sequencing system 106 selects an alternate haplotype 416 based on a region occurrence threshold for a target genomic region (such as a low-confidence call region) of the reference genome 402.

[0099] Based on the alternate haplotype 416, Figure 4 As further shown, the structural variant-aware sequencing system 106 generates an alternate haplotype variant call file 418. For example, the structural variant-aware sequencing system 106 generates a VCF formatted file that identifies alternate haplotypes with single-letter codes (e.g., A, T, C, G) to compare with the single-letter code of the corresponding reference haplotype at a specific genomic coordinate. In some embodiments, the structural variant-aware sequencing system 106 generates a VCF file that includes more than 400,000 such alternate haplotypes for low-confidence call regions.

[0100] Based on one or more of the reference genome sequence file 404, the SV haplotype alignment file 410, the SV haplotype sequence file 412, or the alternate haplotype variant call file 418, the structural variant-aware sequencing system 106 generates a graph hash table 422. The graph hash table 422 represents an embodiment of the structural variation graph genome. For example, the structural variant-aware sequencing system 106 generates the graph hash table 422 by associating each of the following items with the genomic coordinates of the reference haplotype: (i) a reference sequence representing a reference haplotype from the reference genome sequence file 404, (ii) an alternate continuous sequence representing a structural variant haplotype 408 from the SV haplotype sequence file 412, and (iii) an alternate nucleobase or additional alternate continuous sequence from the alternate haplotype variant call file 418. The structural variant-aware sequencing system 106 uses the SV haplotype alignment file 410 to map the structural variant haplotype 408 to genomic coordinates at which the alternate continuous sequences will form a boosted group in the graph hash table 422. Graph hash table 422 thus represents an organization that maps nucleobase identifiers (e.g., single letter codes) of the following items to specific genomic coordinates: (i) reference haplotypes from reference genome 402, (ii) structural variant haplotypes 408, and (iii) alternate haplotypes 416.

[0101] In addition to the above files, in some embodiments, the structural variant-aware sequencing system 106 generates a mask file 420. The mask file 420 partially masks the sequence or nucleobase identifiers (e.g., A, T, C, G) of the structural variant haplotype 408 or the alternate haplotype 416 with "N" from the FASTA file. By masking the sequence or nucleobases of either or both of the structural variant haplotype 408 or the alternate haplotype 416, the structural variant-aware sequencing system 106 can create a masked genome file based on custom annotations or masked (e.g., hidden) target genomic regions when aligning sequence data from nucleotide reads. By partially masking certain sequences, such as repetitive sequences or low-complexity genomic regions using the mask file 420, the structural variant-aware sequencing system 106 can selectively hide or mask a reference sequence or alternative contiguous sequence for alignment, thereby ensuring that nucleotide reads are not aligned to such hidden nucleotide sequences. In some cases, the structural variant-aware sequencing system 106 generates a browser extensible data (BED) file as the mask file 420. Therefore, in some embodiments, certain nucleotide sequences in the graph hash table 422 are masked.

[0102] In addition or alternatively to generating a structural variation map genome in an organized structure, in some embodiments, the structural variant-aware sequencing system 106 implements a structural variation map genome to determine variant calls or other nucleobase calls for a genomic sample. According to one or more embodiments, Figure 5A structural variant-aware sequencing system 106 is shown that (i) aligns nucleotide reads of a genomic sample to a structural variation map genome and (ii) determines nucleobase calls for the genomic sample based on the aligned nucleotide reads. As described below, the structural variant-aware sequencing system 106 can determine variant calls (or other nucleobase calls) based on aligning a subset of nucleotide reads to an alternating contiguous sequence representing a structural variant haplotype or an alternating haplotype.

[0103] like Figure 5 As shown, the structural variant-aware sequencing system 106 identifies or receives nucleotide reads 502 of a genomic sample. In some cases, for example, the structural variant-aware sequencing system 106 receives base call data (e.g., a BCL file or a FASTQ file) from a sequencing device. In some such cases, the base call data takes the form of a base call data file that organizes a single end read or a paired end read according to an index sequence attached to an oligonucleotide extracted from the genomic sample. As described above, in some embodiments, the structural variant-aware sequencing system 106 may sequence or analyze short nucleotide reads (e.g., <300 base pairs or <10,000 base pairs) as nucleotide reads 502, or in other embodiments, sequence or analyze long nucleotide reads (e.g., >300 base pairs or >10,000 base pairs) as nucleotide reads 502.

[0104] like Figure 5 As further shown, the structural variant-aware sequencing system 106 aligns the nucleotide reads 502 with different sequences within the structural variation map genome 504. For example, the structural variant-aware sequencing system 106 aligns subsets 506a, 506c, and 506e of the nucleotide reads in whole or in part with reference sequences 508a, 508b, and 508c, respectively. As described above, each of the reference sequences 508a to 508c represents a different reference haplotype from a reference genome (e.g., GRCh38). As another example, the structural variant-aware sequencing system 106 aligns subset 506b of the nucleotide reads in whole or in part with an alternating nucleobase or an alternating continuous sequence 510 representing an alternating haplotype. Finally, the structural variant-aware sequencing system 106 aligns subset 506d of the nucleotide reads in whole or in part with an alternating continuous sequence 512a (or an alternating continuous sequence 512b) representing a structural variant haplotype.

[0105] For illustrative purposes and space limitations, Figure 5The subsets 506a to 506e of nucleotide reads, the reference sequences 508a to 508c, the alternating nucleobase or alternating continuous sequence 510, and the alternating continuous sequences 512a and 512b are depicted by way of example only. As described above, the sequencing equipment may generate many additional subsets of nucleotide reads, and the structural variation map genome 504 may include many other types of reference sequences, alternating nucleobases, or alternating continuous sequences. In practice, Figure 5 The depicted structural variation map genome 504 is but one illustration of a visualization of a reference sequence and alternating contiguous sequences of a structural variation map genome embodied by a hash table, matrix, or other digital organizational structure.

[0106] like Figure 5 As shown, the structural variant-aware sequencing system 106 determines that a subset 506d of nucleotide reads completely or partially overlaps with an alternating contiguous sequence 512a representing a structural variant haplotype. For example, the structural variant-aware sequencing system 106 determines that an alignment score (e.g., a Smith-Waterman score or a modified version of a Smith-Waterman score) exceeds other alignment scores for alternative alignments of the subset 506a of nucleotide reads with the corresponding reference sequence. Based in part on the alignment score for the alignment of the subset 506d of nucleotide reads with the alternating contiguous sequence 512a exceeding other alignment scores for the subset of nucleotide reads, in some embodiments, the structural variant-aware sequencing system 106 generates a variant call indicating that the genomic sample exhibits a structural variant haplotype represented by the alternating contiguous sequence 512a.

[0107] As just noted, in some embodiments, the structural variant-aware sequencing system 106 determines an alternating contiguous segment alignment score (e.g., a Smith-Waterman score or a modified version of a Smith-Waterman score) for the alignment of the subset 506d of nucleotide reads to the alternating contiguous sequence 512a. The structural variant-aware sequencing system 106 may also determine a segmentation group score for a segmentation alignment of the subset 506d of nucleotide reads to one or more reference sequences. If the alternating contiguous segment alignment score exceeds the segmentation group score for the segmentation alignment of the subset 506d of nucleotide reads, and exceeds the alignment score (e.g., Smith-Waterman score) for other alignments with other alternating contiguous sequences (such as the alternating contiguous sequence 512b), the structural variant-aware sequencing system 106 selects and reports the segmentation alignment of the primary assembly of the reference genome corresponding to the alternating contiguous sequence 512a by a promotion relationship. By selecting and reporting such a split alignment, the structural variant-aware sequencing system 106 can use the reported split alignment to determine the base call based on the alignment of the subset 506d of nucleotide reads with the alternating continuous sequence 512a. However, if the split group score of the split alignment for the subset 506d of nucleotide reads exceeds the alternating contiguous group segment alignment score, the structural variant-aware sequencing system 106 determines the base call based on a different split alignment with one or more reference sequences of the reference genome, which may not represent an alignment with the alternating continuous sequence 512a. In some embodiments, the structural variant-aware sequencing system 106 determines the alternating contiguous group segment alignment score and the split group score, as described in U.S. Patent Application No. 63 / 367,002, “Improving Split-Read Alignment by Intelligently Identifying and Scoring Candidate Split Groups” (filed on June 24, 2022), which is incorporated herein by reference in its entirety.

[0108] Based on the alignment of the subset of nucleotide reads 506a to 506e with different sequences of the structural variation map genome 504, such as Figure 5As further shown, the structural variant-aware sequencing system 106 generates nucleobase calls 514. For example, in some embodiments, the structural variant-aware sequencing system 106 determines nucleobase calls for subsets 506a, 506c, and 506e of nucleotide reads based on alignments of subsets 506a, 506c, and 506e of nucleotide reads with reference sequences 508a, 508b, and 508c, respectively. In some such cases, the nucleobase calls may indicate a reference base (e.g., represented as 0) in a variant call file 516. As another example of nucleobase calls 514, the structural variant-aware sequencing system 106 determines one or more variant calls for subset 506b of nucleotide reads based on alignments of subset 506b of nucleotide reads with an alternating nucleobase or alternating continuous sequence 510.

[0109] Unlike existing sequencing systems, the structural variant-aware sequencing system 106 can also determine variant calls corresponding to structural variants based on the structural variation map genome. For example, based on the alignment of the subset 506a of nucleotide reads and the alternating continuous sequence 512a, the structural variant-aware sequencing system 106 generates one or more variant calls indicating that the genomic sample exhibits a structural variant haplotype represented by the alternating continuous sequence 512a. In some cases, the structural variant-aware sequencing system 106 generates a variant call file 516 or an alignment file 518 including the following annotations: (i) an annotation indicating one or more variant calls or other nucleobase calls representing a structural variant haplotype, and / or (ii) an annotation indicating an alignment reflecting a structural variant haplotype within a genomic sample. Consistent with the above disclosure, a variant call or nucleobase call can correspond to a structural variant haplotype including: a deletion exceeding a threshold number of base pairs, an insertion exceeding a threshold number of base pairs, a duplication exceeding a threshold number of base pairs, an inversion, a translocation, or a copy number variation (CNV).

[0110] The structural variant-aware sequencing system 106 can recover nucleobase calls that would not otherwise be reported in the output file by aligning the subset 506a to 506e of nucleotide reads to the alternating contiguous sequences representing structural variant haplotypes of the structural variation map genome 504. For example, in some embodiments, the structural variant-aware sequencing system 106 determines that the alignment score for the subset 506d of nucleotide reads does not meet the threshold alignment score for a candidate alignment between the subset 506a of nucleotide reads and the primary assembled region of the linear reference genome within the structural variation map genome 504.

[0111] To illustrate this recovery, the alignment score for the candidate alignment of the subset 506a of nucleotide reads with various reference sequences may be below the threshold alignment score. In contrast, the alternating contig fragment alignment score for the alignment of the subset 506d of nucleotide reads with the alternating contiguous sequence 512a may meet the threshold alignment score. Therefore, in some embodiments, the structural variant-aware sequencing system 106 generates a variant call file 516 or an alignment file 518, wherein one or more nucleobase calls are made to the genomic sample based on the alignment of the subset 506d of the aligned nucleotide reads with the alternating contiguous sequence 512a, but no nucleobase calls are made to the genomic sample based on the candidate alignment of the subset 506d of nucleotide reads with various reference sequences that do not meet the threshold alignment score.

[0112] As described above, the structural variant-aware sequencing system 106 generates a variant call file 516 or an alignment file 518 including the following annotations, which indicate information about the structural variant haplotypes detected in the genomic sample. For example, in one or more embodiments, the structural variant-aware sequencing system 106 generates a variant call file 516 or an alignment file 518 including one or more of the following annotations: (i) annotations indicating variant calls or other nucleobase calls corresponding to structural variant haplotypes, (ii) annotations indicating the frequency of structural variant haplotypes (e.g., the frequency of structural variant haplotypes within a genomic sample database), (iii) annotations indicating the genomic coordinates of the structural variant haplotype corresponding to the nucleobase calls, or (iv) annotations indicating alignments reflecting structural variant haplotypes within a genomic sample.

[0113] After generating one or more such annotation data, in some embodiments, the structural variant-aware sequencing system 106 provides a variant call file 516 or an alignment file 518 for display on a computing device. According to one or more embodiments, Figure 6 The client device 114 is shown displaying a graphical user interface 602 including variant calls for structural variant haplotypes. Figure 6 The graphical user interface 602 displayed when the client device 114 implements the computer-executable instructions of the sequencing application 116 is depicted, but the present disclosure does not repeatedly refer to the computer-executable instructions that cause the client device 114 to perform specific actions of the structural variant-aware sequencing system 106, but rather describes the client device 114 or the structural variant-aware sequencing system 106 that performs those actions in the following paragraphs. In some embodiments, the variant call file 516 or the alignment file 518 provides part of the computer-executable instructions and data to be presented within the graphical user interface 602.

[0114] like Figure 6As shown, for example, the client device 114 presents variant calls 604a and 604b reflecting different structural variant haplotypes exhibited by the genomic sample. Consistent with the above disclosure, variant calls 604a and 604b represent graphical representations of nucleobase calls corresponding to the above structural variant haplotypes. As part of or in addition to each of the variant calls 604a and 604b, the client device 114 presents a reference sequence indicator for the reference sequence of the reference haplotype (e.g., REF: GGGGCC 30X or REF: ACGTTAA...) and an alternate sequence indicator for some or all of the alternate continuous sequences corresponding to the structural variant haplotype (e.g., ALT: GGGGCC 101X or ALT: duplication-inversion-inversion-deletion). Additionally, as part of or in addition to each of the variant calls 604a and 604b, the client device 114 presents the genomic coordinates of the variant calls 604a and 604b (eg, Chr9:614260 or Chr6:156,776,025-157).

[0115] like Figure 6 As further shown, in some embodiments, the client device 114 presents annotations for genes and variant frequencies corresponding to variant calls 604a and 604b. For example, the client device 114 presents genes 606a and 606b (e.g., c9orf72 or ARID1B) corresponding to variant calls 604a and 604b, respectively. In addition to specific gene identifications, the client device 114 also presents variant frequencies 608a and 608b (e.g., 1.2% or 0.6%) indicating the frequencies of structural variant haplotypes represented by variant calls 604a and 604b, respectively (e.g., from a genomic sample database). By providing reference sequence identifiers, alternate sequence identifiers, genomic coordinates, genes, and variant frequencies, the structural variant-aware sequencing system 106 provides key information indicating structural variant calls for certain genes to clinicians, test subjects, or others.

[0116] As described above, the structural variant-aware sequencing system 106 improves the accuracy of read alignment and base calling by generating or utilizing a structural variation graph genome representing structural variants. To test the accuracy of read alignment and base calling of the structural variant-aware sequencing system 106, researchers compared the accuracy of the sequencing system detecting structural variants using an existing graph reference genome with the accuracy of the structural variant-aware sequencing system 106 identifying structural variants using a structural variation graph genome. According to one or more embodiments, Figure 7A table 700 is shown, which shows different accuracy measures for: (i) variant calls for deletions and insertions greater than 50 base pairs determined by a sequencing system using an existing map reference genome that lacks alternating contiguous sequences representing structural variants, and (ii) variant calls for such deletions and insertions determined by a structural variant-aware sequencing system 106 using a structural variation map genome. As shown in table 700, the structural variant-aware sequencing system 106 improves true positive genotype calls, false negative genotype calls, recall, and F-scores for variant calls for deletions and insertions greater than 50 base pairs by using a structural variation map genome instead of an existing map reference genome.

[0117] like Figure 7 As indicated, the researcher inputs nucleotide read data from a query call set including new deletions and insertions of more than 50 base pairs into a sequencing system and a structural variant-aware sequencing system 106. The sequencing system aligns the nucleotide read data from the query call set with an existing map reference genome (here, the Illumina DRAGEN map reference genome hg19), and determines variant calls based on the aligned nucleotide read data. The structural variant-aware sequencing system 106 also aligns the nucleotide read data in the query call set with an embodiment of the structural variation map genome, and determines variant calls based on the aligned nucleotide read data.

[0118] To evaluate the accuracy of the genotype calls of the query call set, the researchers compared the genotype calls of the query call set sequencing system and the structural variant-aware sequencing system 106 with the true call set. The true call set includes known deletions and insertions greater than 50 base pairs. For example, the true call set includes a list of structural variant events identified by other technologies or manually verified.

[0119] As indicated in Table 700, the researcher also determined (i) a number of true positive (TP) genotype calls, where the sequencing system or structural variant-aware sequencing system 106 correctly determined the corresponding insertions and deletions, and (ii) a number of false negative (FN) genotype calls, where the sequencing system or structural variant-aware sequencing system 106 incorrectly determined the corresponding insertions and deletions. Based on the number of true positive genotype calls and false negative genotype calls, the researcher also determined recall, precision, and F-score, as indicated in Table 700.

[0120] As shown in Table 700, by using the structural variation graph genome instead of the existing graph reference genome, the structural variant-aware sequencing system 106 improves true positive genotype calls, reduces false negative genotype calls, and improves recall for deletions greater than 50 base pairs in the true call set. Similarly, by using the structural variation graph genome, the structural variant-aware sequencing system 106 improves true positive genotype calls, reduces false negative genotype calls, improves precision, and improves F scores for deletions greater than 50 base pairs in the query call set compared to the sequencing system's existing graph reference genome.

[0121] As further shown in Table 700, by using the structural variation graph genome in place of the existing graph reference genome, the structural variant-aware sequencing system 106 improves true positive genotype calls, reduces false negative genotype calls, and improves recall for insertions greater than 50 base pairs in the true call set. Similarly, by using the structural variation graph genome, the structural variant-aware sequencing system 106 improves true positive genotype calls, reduces false negative genotype calls, improves precision, and improves F-scores for insertions greater than 50 base pairs in the query call set compared to the sequencing system's existing graph reference genome.

[0122] Now go to Figure 8 , which shows a flow chart of a series of actions 800 for generating a structural variation graph genome according to one or more embodiments of the present disclosure. Figure 8 Actions according to one embodiment are shown, but alternative embodiments may omit, add, reorder, and / or modify Figure 8 Any action shown. Figure 8 The actions of may be performed as part of a method. Alternatively, a non-transitory computer-readable storage medium may include a computer program that, when executed by one or more processors, causes a computing device or system to perform Figure 8 In some further embodiments, the system includes at least one processor and a non-transitory computer-readable medium, which includes instructions that, when executed by one or more processors, cause the system to perform the actions depicted. Figure 8 In some cases, the at least one processor comprises a configurable processor, and executing the at least one processor comprises configuring the configurable processor.

[0123] like Figure 8 As shown, act 800 includes act 810 of identifying a candidate structural variant. Specifically, in some embodiments, act 810 includes identifying a candidate structural variant that meets a threshold amount of occurrence within a genomic sample database.

[0124] For example, in some cases, identifying a candidate structural variant comprises selecting a structural variant representing one or more of a deletion of more than fifty base pairs, an insertion of more than fifty base pairs, a duplication of more than fifty base pairs, an inversion, a translocation, or a copy number variation (CNV). As another example, in some cases, identifying a candidate structural variant comprises selecting a structural variant representing one or more of a deletion of more than a threshold number of base pairs, an insertion of more than a threshold number of base pairs, a duplication of more than a threshold number of base pairs, an inversion, a translocation, or a copy number variation (CNV).

[0125] like Figure 8 As further shown, action 800 includes action 820 of selecting a structural variant haplotype from the candidate structural variants. Specifically, in some embodiments, action 820 includes selecting a structural variant haplotype from the candidate structural variants. For example, in some cases, selecting a structural variant haplotype includes selecting a specific structural variant haplotype from the candidate structural variants that satisfies a threshold amount of additional occurrences at a specific genomic region.

[0126] To illustrate, in some embodiments, selecting a structural variant haplotype includes: selecting a first structural variant haplotype from candidate structural variants that satisfies a threshold amount of additional occurrences at a first genomic region; and selecting a second structural variant haplotype from candidate structural variants that satisfies a threshold amount of additional occurrences at a second genomic region.

[0127] Additionally or alternatively, in some embodiments, selecting a structural variant haplotype includes selecting a specific structural variant haplotype adjacent to a specific flanking variant within a nucleotide sequence of a genomic sample database. In some cases, flanking variants include single nucleotide polymorphisms (SNPs), deletions of less than fifty base pairs, or insertions of less than fifty base pairs. Specifically, in certain specific implementations, selecting a specific structural variant haplotype includes: selecting a first structural variant haplotype that is in phase with a first flanking variant within a first nucleotide sequence of a genomic sample database; and selecting a second structural variant haplotype that is in phase with a second flanking variant within a second nucleotide sequence of a genomic sample database.

[0128] For illustration, in some embodiments, selecting a structural variant haplotype comprises: selecting a first structural variant haplotype adjacent to a first flanking variant within a first nucleotide sequence of a genomic sample database; and selecting a second structural variant haplotype adjacent to a second flanking variant within a second nucleotide sequence of a genomic sample database. As described above, in some cases, the first flanking variant or the second flanking variant comprises a single nucleotide polymorphism (SNP), a deletion of less than a threshold number of base pairs, or an insertion of less than a threshold number of base pairs.

[0129] like Figure 8As further shown, act 800 includes an act of identifying a reference haplotype corresponding to the structural variant haplotype 830. Specifically, in some implementations, act 830 includes identifying a reference haplotype corresponding to the structural variant haplotype from a linear reference genome.

[0130] like Figure 8 As further shown, act 800 includes an act 840 of generating a structural variation map genome comprising structural variant haplotypes and reference haplotypes. Specifically, in certain implementations, act 840 includes generating a structural variation map genome comprising alternating contiguous sequences representing structural variant haplotypes and reference sequences representing reference haplotypes. As described above, in some embodiments, act 840 includes generating a structural variation map genome comprising specific alternating contiguous sequences representing specific structural variant haplotypes and specific flanking variants.

[0131] To illustrate, in some cases, generating a structural variation map genome includes generating a structural variation map genome including: a first alternating contiguous sequence representing a first structural variant haplotype and a first flanking variant; and a second alternating contiguous sequence representing a second structural variant haplotype and a second flanking variant. In addition, in some cases, generating a structural variation map genome includes ranking a subset of alternating contiguous sequences corresponding to a genomic region according to frequency within a genomic sample database.

[0132] In addition or as an alternative to actions 810 to 840, in some embodiments, action 800 also includes identifying, from a genomic sample database, alternate haplotypes comprising one or more of single nucleotide polymorphisms (SNPs), deletions of less than fifty base pairs, or insertions of less than fifty base pairs; and generating a structural variation map of the genome that also includes alternate nucleobases or additional alternate continuous sequences representing alternate haplotypes.

[0133] As described above, in some embodiments, act 800 includes generating an alignment file that maps structural variant haplotypes to genomic coordinates of reference haplotypes within a linear reference genome; and generating a structural variation map genome by associating alternating consecutive sequences representing structural variant haplotypes with identifiers of genomic coordinates of reference haplotypes within an organizational structure. For example, in some specific implementations, generating an alignment file includes generating a sequence alignment / mapping (SAM) boost file that maps structural variant haplotypes to genomic coordinates of reference haplotypes; and generating a structural variation map genome includes generating a structural variation map genome using the organizational structure by associating nucleobase identifiers of nucleobases from alternating consecutive sequences with values ​​representing genomic coordinates of reference haplotypes within a hash table.

[0134] Now turn to Fig. 9, which shows a flowchart of a series of actions 900 for aligning nucleotide reads of a genomic sample with a structural variation map genome and determining a nucleobase call of the genomic sample based on the aligned nucleotide reads according to one or more embodiments of the present disclosure. Fig. 9 Actions according to one embodiment are shown, but alternative embodiments may omit, add, reorder, and / or modify Fig. 9 Any action shown. Fig. 9 The actions of may be performed as part of a method. Alternatively, a non-transitory computer-readable storage medium may include a computer program that, when executed by one or more processors, causes a computing device or system to perform Fig. 9 In some further embodiments, the system includes at least one processor and a non-transitory computer-readable medium, which includes instructions that, when executed by one or more processors, cause the system to perform the actions depicted. Fig. 9 In some cases, the at least one processor comprises a configurable processor, and executing the at least one processor comprises configuring the configurable processor.

[0135] like Fig. 9 As shown, act 900 includes act 910 of identifying nucleotide reads from a genomic sample. Fig. 9 As further shown, act 900 includes aligning a subset of nucleotide reads to structural variant haplotypes within the structural variation map genome at act 920. Specifically, in some embodiments, act 920 includes aligning a subset of nucleotide reads to alternating contiguous sequences representing structural variant haplotypes within the structural variation map genome.

[0136] In some cases, the structural variant haplotype includes a deletion of more than fifty base pairs, an insertion of more than fifty base pairs, a duplication, an inversion, a translocation, or a copy number variation (CNV). Alternatively, in some cases, the structural variant haplotype includes a deletion of more than a threshold number of base pairs, an insertion of more than a threshold number of base pairs, a duplication, an inversion, a translocation, or a copy number variation (CNV) of more than a threshold number of base pairs.

[0137] like Fig. 9 As further shown, act 900 includes an act 930 of generating a nucleobase call for the genomic sample based on the subset of aligned nucleotide reads. Specifically, in some implementations, act 930 includes generating one or more nucleobase calls for the genomic sample based on the subset of aligned nucleotide reads.

[0138] In addition or alternatively to acts 910 to 930, in some embodiments, act 900 includes generating an alignment file or variant call file including annotations indicating structural variant haplotypes corresponding to one or more nucleobase calls. Additionally or alternatively, in some cases, act 900 includes generating an alignment file or variant call file including annotations indicating the frequency of structural variant haplotypes corresponding to one or more nucleobase calls within a genomic sample database. Additionally or alternatively, in certain embodiments, act 900 includes generating an alignment file or variant call file including genomic coordinates of a linear reference genome that is part of a structural variation map genome and corresponds to one or more nucleobase calls.

[0139] As described above, in some embodiments, action 900 includes determining that a subset of nucleotide reads overlaps with breakpoints of an alternating contiguous sequence representing a structural variant haplotype; and generating an alignment file or variant call file including the following annotations, which indicate alignments reflecting structural variant haplotypes within a genomic sample.

[0140] Additionally or alternatively, in some embodiments, action 900 includes determining that the alignment score for the subset of nucleotide reads does not satisfy a threshold alignment score for a candidate alignment between the subset of nucleotide reads and a primary assembled region of a linear reference genome; and generating a variant call file or alignment file with one or more nucleobase calls for the genomic sample based on the subset of nucleotide reads aligned to the alternating contiguous sequence, and generating a variant call file or alignment file without nucleobase calls for the genomic sample based on the candidate alignments that do not satisfy the threshold alignment score.

[0141] Methods described herein can be used in combination with multiple nucleic acid sequencing techniques. Particularly suitable techniques are those in which nucleic acids are attached to fixed positions in an array so that their relative positions do not change and in which the array is repeatedly imaged. Embodiments in which images are obtained in different color channels (e.g., matching different markers for distinguishing a type of core base from another type of core base) are particularly suitable. In some embodiments, the process of determining the nucleotide sequence of a target nucleic acid (i.e., nucleic acid polymer) can be an automated process. Preferred embodiments include sequencing by synthesis (SBS) technology.

[0142] SBS techniques generally include enzymatic extension of nascent nucleic acid chains by repeated addition of nucleotides to the template strand. In traditional SBS methods, a single nucleotide monomer can be provided to the target nucleotide in the presence of a polymerase in each delivery. However, in the methods described herein, more than one type of nucleotide monomer can be provided to the target nucleic acid in the presence of a polymerase in the delivery.

[0143] SBS can utilize nucleotide monomers with terminator parts or lack nucleotide monomers of any terminator parts.The method utilizing the nucleotide monomers lacking terminator includes for example pyrophosphate sequencing and the sequencing of nucleotides using gamma-phosphate labeling, as described in further detail below.In the method using the nucleotide monomers lacking terminator, the number of nucleotides added in each cycle is usually variable, and the number depends on the mode of template sequence and nucleotide delivery.For utilizing the SBS technology of the nucleotide monomers with terminator parts, terminator can be effectively irreversible under the sequencing conditions used, such as the situation of traditional Sanger sequencing utilizing dideoxynucleotides, or terminator can be reversible, such as the situation of the sequencing method developed by Solexa (now Illumina, Inc.).

[0144] The SBS technique can utilize nucleotide monomers with a labeling portion or nucleotide monomers lacking a labeling portion. Thus, incorporation events can be detected based on the following items: properties of the label, such as the fluorescence of the label; properties of the nucleotide monomer, such as molecular weight or charge; byproducts of the incorporated nucleotide, such as the release of pyrophosphate; and the like. In embodiments where two or more different nucleotides are present in the sequencing reagent, the different nucleotides may be distinguishable from each other, or alternatively, the two or more different labels may be indistinguishable under the detection technology used. For example, different nucleotides present in the sequencing reagent may have different labels, and they may be distinguished using appropriate optical devices, as exemplified by the sequencing method developed by Solexa (now Illumina, Inc.).

[0145] Preferred embodiments include pyrophosphate sequencing technology. Pyrophosphate sequencing detects the release of inorganic pyrophosphate (PPi) when a specific nucleotide is incorporated into a nascent chain (Ronaghi, M., Karamohamed, S., Pettersson, B., Uhlen, M., and Nyren, P. (1996), "Real-time DNA sequencing using detection of pyrophosphate release.", Analytical Biochemistry 242 (1), 84-9; Ronaghi, M. (2001), "Pyrosequencing sheds light on DNA sequencing.", Genome Res. 11 (1), 3-11; Ronaghi, M., Uhlen, M., and Nyren, P. (1998), "A sequencing method based on real-time pyrophosphate.", Science 281 (5375), 363; U.S. Pat. No. 6,210,891; U.S. Pat. No. 6,258,568 and U.S. Pat. No. 6,274,320, the disclosures of which are incorporated herein by reference in their entirety). In pyrophosphate sequencing, the released PPi can be detected by being immediately converted into ATP by adenosine triphosphate (ATP) sulfurylase, and the level of ATP generated is detected by photons generated by luciferase. The nucleic acid to be sequenced can be attached to a feature in an array, and the array can be imaged to capture the chemiluminescent signal generated by the incorporation of nucleotides at the feature of the array. The image can be obtained after treating the array with a specific nucleotide type (e.g., A, T, C or G). The images obtained after adding each nucleotide type will differ in which features in the array are detected. These differences in the image reflect the different sequence contents of the features on the array. However, the relative orientation of each feature will remain unchanged in the image. The images can be stored, processed and analyzed using the methods described herein. For example, images obtained after treating the array with each different nucleotide type can be processed in the same manner as exemplified herein for images obtained from different detection channels for a reversible terminator-based sequencing method.

[0146] In another exemplary type of SBS, cycle sequencing is accomplished by the stepwise addition of reversible terminator nucleotides, which contain, for example, cleavable or photobleachable dye labels, as described in, for example, WO 04 / 018497 and U.S. Patent No. 7,057,026, the disclosures of which are incorporated herein by reference. The method is commercialized by Solexa (now Illumina Inc.) and is also described in WO 91 / 06678 and WO 07 / 123,744, the disclosures of each of which are incorporated herein by reference. The availability of fluorescently labeled terminators, in which termination can be reversible and the fluorescent label can be cleaved, facilitates efficient cyclic reversible termination (CRT) sequencing. Polymerases can also be co-engineered to efficiently incorporate these modified nucleotides and extend from these modified nucleotides.

[0147] Preferably, in the sequencing embodiment based on reversible terminator, the label does not substantially inhibit extension under SBS reaction conditions. However, the detection label can be removable, such as removed by cleavage or degradation. Images can be captured after the label is incorporated into the arrayed nucleic acid feature. In a specific embodiment, each cycle involves four different nucleotide types being delivered to the array simultaneously, and each nucleotide type has a label that is spectrally different. Four images can then be obtained, each image using a detection channel that is selective to one label in the four different labels. Alternatively, different nucleotide types can be added sequentially, and the image of the array can be obtained between each addition step. In such embodiments, each image will show the nucleic acid feature that has been incorporated with a specific type of nucleotide. Due to the different sequence content of each feature, different feature portions are present or absent in different images. However, the relative position of the feature portion will remain unchanged in the image. The image obtained by such reversible terminator-SBS method can be stored, processed and analyzed as described herein. After the image capture step, the label can be removed and the reversible terminator portion can be removed for subsequent cycles of nucleotide addition and detection. Removing labels after they have been detected in a particular cycle and before subsequent cycles can provide the advantage of reducing background signal and crosstalk between cycles. Examples of useful labeling and removal methods are set forth below.

[0148] In a specific embodiment, some or all of the nucleotide monomers may include a reversible terminator. In such embodiments, the reversible terminator / cleavable fluorophore may include a fluorophore (Metzker, Genome Res. 15: 1767-1776 (2005), which is incorporated herein by reference) connected to a ribose moiety via a 3' ester bond. Other methods have separated terminator chemistry from the cleavage of a fluorescent label (Ruparel et al., Proc Natl Acad Sci USA 102: 5932-7 (2005), which is incorporated herein by reference in its entirety). Ruparel et al. describe the development of reversible terminators that use small 3' allyl groups to block extension, but can be easily deblocked by a short treatment with a palladium catalyst. The fluorophore is attached to the base via a photocleavable linker that can be easily cleaved by exposure to long wavelength ultraviolet light for 30 seconds. Therefore, disulfide reduction or photocleavage can be used as a cleavable linker. Another method of reversible termination is to use natural termination, which occurs after a bulky dye is placed on a dNTP. The presence of a charged bulky dye on a dNTP can act as an efficient terminator by steric hindrance and / or electrostatic hindrance. Unless the dye is removed, the presence of an incorporation event prevents further incorporation. The cracking of the dye removes the fluorophore and effectively reverses termination. The example of modified nucleotides is also described in U.S. Patent No. 7,427,673 and U.S. Patent No. 7,057,026, the disclosure of which is incorporated herein by reference in its entirety.

[0149] Additional exemplary SBS systems and methods that may be utilized with the methods and systems described herein are described in U.S. Patent Application Publication No. 2007 / 0166705, U.S. Patent Application Publication No. 2006 / 0188901, U.S. Patent No. 7,057,026, U.S. Patent Application Publication No. 2006 / 0240439, U.S. Patent Application Publication No. 2006 / 0281109, PCT Publication No. WO05 / 065814, U.S. Patent Application Publication No. 2005 / 0100900, PCT Publication No. WO 06 / 064199, PCT Publication No. WO07 / 010,251, U.S. Patent Application Publication No. 2012 / 0270305, and U.S. Patent Application Publication No. 2013 / 0260372, the disclosures of which are incorporated herein by reference in their entireties.

[0150] Some embodiments can use the detection of four different nucleotides using less than four different marks.For example, the method and system described in the material of the U.S. Patent Application Publication No. 2013 / 0079232 incorporated can be used to perform SBS.As a first example, a pair of nucleotide types can be detected at the same wavelength, but based on the intensity difference of a member in the pair relative to another member, or based on a member in the pair causing a change (for example, by chemical modification, photochemical modification or physical modification) that a signal that is obvious compared with the signal of another member of the pair detected appears or disappears.As a second example, three of the four different nucleotide types can be detected under specific conditions, and the fourth nucleotide type lacks a mark (for example, the minimum detection caused by background fluorescence, etc.) that can be detected under those conditions or detected minimally under those conditions.The first three nucleotide types can be determined to be incorporated into nucleic acid based on the existence of its corresponding signal, and the fourth nucleotide type can be determined to be incorporated into nucleic acid based on the absence of any signal or the minimum detection of any signal.As a third example, a nucleotide type can include a mark detected in two different channels, and other nucleotide types are detected in no more than one channel. The three exemplary configurations described above are not considered mutually exclusive and can be used in various combinations. An exemplary embodiment combining all three examples is a fluorescence-based SBS method that uses a first nucleotide type detected in a first channel (e.g., dATP with a label detected in the first channel when excited by a first excitation wavelength), a second nucleotide type detected in a second channel (e.g., dCTP with a label detected in the second channel when excited by a second excitation wavelength), a third nucleotide type detected in both the first channel and the second channel (e.g., dTTP with at least one label detected in both channels when excited by the first excitation wavelength and / or the second excitation wavelength), and a fourth nucleotide type that lacks a label detected or minimally detected in either channel (e.g., dGTP without a label).

[0151] In addition, as described in the materials of incorporated U.S. Patent Application Publication No. 2013 / 0079232, a single channel can be used to obtain sequencing data. In such so-called single dye sequencing methods, a first nucleotide type is marked, but the mark is removed after the first image is generated, and a second nucleotide type is marked only after the first image is generated. A third nucleotide type retains its mark in both the first image and the second image, and a fourth nucleotide type remains unmarked in both images.

[0152] Some embodiments can utilize sequencing technology while connecting. Such technology utilizes DNA ligase to incorporate oligonucleotides and recognize the incorporation of such oligonucleotides. Oligonucleotides generally have different labels related to the identity of specific nucleotides in the sequence of oligonucleotide hybridization. As with other SBS methods, images can be obtained after the array of nucleic acid features is treated with labeled sequencing reagents. Each image will show the nucleic acid features that have been incorporated with a specific type of label. Due to the different sequence content of each feature, different features are present or absent in different images, but the relative position of the features will remain unchanged in the image. The images obtained by the sequencing method based on connection can be stored, processed and analyzed as described herein. Exemplary SBS systems and methods that can be used with the methods and systems described herein are described in U.S. Patent No. 6,969,488, U.S. Patent No. 6,172,218 and U.S. Patent No. 6,306,597, and the disclosures of these patents are incorporated herein by reference in their entirety.

[0153] Some embodiments may utilize nanopore sequencing (Deamer, DW and Akeson, M., "Nanopores and nucleic acids: prospects for ultrarapid sequencing.", Trends Biotechnol. 18, 147-151 (2000); Deamer, D. and D. Branton, "Characterization of nucleic acids by nanopore analysis.", Acc. Chem. Res. 35: 817-825 (2002); Li, J., M. Gershow, D. Stein, E. Brandin and JA Golovchenko, "DNA molecules and configurations in a solid-state nanopore microscope", Nat. Mater., 2: 611-615 (2003), the disclosures of which are incorporated herein by reference in their entirety). In such embodiments, the target nucleic acid passes through the nanopore. The nanopore may be a synthetic pore or a biological membrane protein, such as α-hemolysin. As the target nucleic acid passes through the nanopore, each base pair can be identified by measuring the fluctuations in the conductivity of the pore. (U.S. Pat. No. 7,001,792; Soni, GV and Meller, "A. Progress toward ultrafast DNA sequencing using solid-state nanopores.", Clin. Chem. 53, 1996-2001 (2007); Healy, K., "Nanopore-based single-molecule DNA analysis.", Nanomed., 2, 459-481 (2007); Cockroft, SL, Chu, J., Amorin, M. and Ghadiri, MR, "A single-molecule nanopore device detects DNA polymerase activity with single-nucleotide resolution.", J. Am. Chem. Soc. 130, 818-820 (2008), the disclosures of which are incorporated herein by reference in their entirety). The data obtained from nanopore sequencing can be stored, processed and analyzed as described herein. In particular, according to the exemplary processing of optical images and other images described herein, the data can be processed like an image.

[0154] Some embodiments may utilize methods involving real-time monitoring of DNA polymerase activity. Nucleotide incorporation may be detected by fluorescence resonance energy transfer (FRET) interactions between a polymerase carrying a fluorophore and a γ-phosphate labeled nucleotide, as described, for example, in U.S. Pat. No. 7,329,492 and U.S. Pat. No. 7,211,414 (each of which is incorporated herein by reference), or may be detected by zero-mode waveguides, as described, for example, in U.S. Pat. No. 7,315,019 (which is incorporated herein by reference), and may be detected by fluorescent nucleotide analogs and engineered polymerases, as described, for example, in U.S. Pat. No. 7,405,281 and U.S. Patent Application Publication No. 2008 / 0108082 (each of which is incorporated herein by reference). Illumination can be limited to a volume of the order of magnitude surrounding the surface-tethered polymerase, so that the incorporation of fluorescently labeled nucleotides can be observed under low background (Levene, MJ et al., "Zero-mode waveguides for single-molecule analysis at high concentrations.", Science 299, 682-686 (2003); Lundquist, PM et al., "Parallel confocal detection of single molecules in real time.", Opt. Lett. 33, 1026-1028 (2008); Korlach, J. et al., "Selective aluminum passivation for targeted immobilization of single DNA polymerase molecules in zero-mode waveguide nano structures.", Proc. Natl. Acad. Sci. USA 105, 1176-1181 (2008), the disclosures of which are incorporated herein by reference in their entirety). Images obtained by such methods can be stored, processed, and analyzed as described herein.

[0155] Some SBS embodiments include detecting the proton released when nucleotides are incorporated into extension products. For example, sequencing based on the detection of releasing protons can use the commercially available electrical detectors and related technologies available from Ion Torrent company (Guilford, CT, it is a Life Technologies subsidiary) or the sequencing methods and systems described in US 2009 / 0026082A1, US2009 / 0127589 A1, US2010 / 0137143 A1 or US 2010 / 0282617A1, each of which is incorporated herein by reference. The method for amplifying target nucleic acids using kinetic exclusion set forth herein can be easily applied to substrates for detecting protons. More specifically, the method set forth herein can be used to produce amplicon clone colonies for detecting protons.

[0156] The above-mentioned SBS method can be advantageously carried out in a variety of formats so that a plurality of different target nucleic acids are manipulated simultaneously. In a specific embodiment, different target nucleic acids can be processed in a common reaction vessel or on the surface of a specific substrate. This allows to conveniently deliver sequencing reagents, remove unreacted reagents and detect incorporation events in a variety of ways. In the embodiment using the target nucleic acid of surface binding, the target nucleic acid can be an array format. In the array format, the target nucleic acid can be attached to the surface in a spatially distinguishable manner generally. The target nucleic acid can be attached by direct covalent attachment, attached to beads or other particles or attached to a polymerase or other molecules attached to the surface to combine. The array can include a single copy of the target nucleic acid at each site (also referred to as a feature portion), or multiple copies with the same sequence can be present at each site or feature portion. Multiple copies can be produced by an amplification method (such as bridge amplification or emulsion PCR as described in further detail below).

[0157] The methods described herein may use arrays having features at any of a variety of densities, including, for example, at least about 10 features / cm2, 100 features / cm2, 500 features / cm2, 1,000 features / cm2, 5,000 features / cm2, 10,000 features / cm2, 50,000 features / cm2, 100,000 features / cm2, 1,000,000 features / cm2, 5,000,000 features / cm2, or more.

[0158] The advantage of the method described herein is that they provide rapid and effective detection of multiple target nucleic acids in parallel. Therefore, the present disclosure provides an integrated system that can use technology known in the art (such as those illustrated above) to prepare and detect nucleic acids. Therefore, the integrated system of the present disclosure may include a fluid assembly that can deliver amplification reagents and / or sequencing reagents to one or more fixed DNA fragments, and the system includes components such as pumps, valves, reservoirs, fluid pipelines, etc. The circulation cell can be configured for and / or for detecting target nucleic acids in the integrated system. Exemplary circulation cells are described in, for example, US 2010 / 0111768A1 and U.S. Serial No. 13 / 273,666, each of which is incorporated herein by reference. As illustrated for the circulation cell, one or more fluid assemblies of the integrated system can be used for amplification method and detection method. Taking nucleic acid sequencing embodiment as an example, one or more fluid assemblies of the integrated system can be used for the amplification method described herein and for delivering sequencing reagents in sequencing method (such as those illustrated above). Alternatively, the integrated system may include a separate fluid system to perform amplification method and perform detection method. Examples of integrated sequencing systems capable of producing amplified nucleic acids and also determining nucleic acid sequences include, but are not limited to, MiSeq TM The ELISA platform (Illumina, Inc., San Diego, CA) and the apparatus described in U.S. Ser. No. 13 / 273,666, which is incorporated herein by reference.

[0159] The above-mentioned sequencing system sequences the nucleic acid polymers present in the sample received by the sequencing device. As defined herein, "sample" and its derivatives are used in their broadest sense, including any specimens, cultures, etc. suspected of containing a target. In some embodiments, the sample includes DNA, RNA, PNA, LNA, chimeric or hybridized nucleic acids. The sample may include any biological, clinical, surgical, agricultural, atmospheric or aquatic animal and plant specimens containing one or more nucleic acids. The term also includes any isolated nucleic acid sample, such as genomic DNA, fresh frozen or formalin-fixed paraffin-embedded nucleic acid specimens. It is also envisioned that the sample may come from: a single individual, a collection of nucleic acid samples from genetically related members, a nucleic acid sample from a genetically unrelated member, a nucleic acid sample (matched therewith) from a single individual (such as a tumor sample and a normal tissue sample), or a sample from a single source containing two different forms of genetic material (such as maternal DNA and fetal DNA obtained from a maternal subject), or there is contaminating bacterial DNA in a sample containing plant or animal DNA. In some embodiments, the source of nucleic acid material may include nucleic acids obtained from newborns, such as nucleic acids commonly used for newborn screening.

[0160] Nucleic acid samples may include high molecular weight substances, such as genomic DNA (gDNA). Samples may include low molecular weight substances, such as nucleic acid molecules obtained from FFPE samples or archived DNA samples. In another embodiment, low molecular weight substances include DNA of enzymatic fragmentation or mechanical fragmentation. Samples may include cell-free circulating DNA. In some embodiments, samples may include nucleic acid molecules obtained from biopsy tissue, tumor, scrapings, swabs, blood, mucus, urine, blood plasma, semen, hair, laser capture microdissection, surgical resection and other clinical or laboratory samples. In some embodiments, samples may be epidemiological samples, agricultural samples, forensic samples or pathogenic samples. In some embodiments, samples may include nucleic acid molecules obtained from animals (such as humans or mammalian sources). In another embodiment, samples may include nucleic acid molecules obtained from non-mammalian sources (such as plants, bacteria, viruses or fungi). In some embodiments, the source of nucleic acid molecules may be archived or extinct samples or species.

[0161] In addition, the methods and compositions disclosed herein can be used to amplify nucleic acid samples with low-quality nucleic acid molecules, such as degraded and / or fragmented genomic DNA from forensic samples. In one embodiment, forensic samples may include nucleic acids obtained from crime scenes, nucleic acids obtained from missing persons DNA databases, nucleic acids obtained from laboratories associated with forensic investigations, or include forensic samples obtained by law enforcement agencies, one or more military services, or any such personnel. Nucleic acid samples can be purified samples or lysates containing crude DNA, such as from oral swabs, paper, fabrics, or other substrates that can be impregnated with saliva, blood, or other body fluids. Therefore, in some embodiments, the nucleic acid sample may include a small amount of DNA (such as genomic DNA), or a fragmented portion of DNA. In some embodiments, the target sequence may be present in one or more body fluids, wherein body fluids include but are not limited to blood, sputum, plasma, semen, urine, and serum. In some embodiments, the target sequence may be obtained from the victim's hair, skin, tissue sample, autopsy, or remains. In some embodiments, nucleic acids comprising one or more target sequences may be obtained from dead animals or humans. In some embodiments, the target sequence may include a nucleic acid obtained from non-human DNA (such as microbial, plant, or insect DNA). In some embodiments, the target sequence or amplified target sequence is directed to the purpose of human identification. In some embodiments, the disclosure as a whole relates to methods for identifying the characteristics of forensic samples. In some embodiments, the disclosure as a whole relates to human identification methods using one or more target-specific primers disclosed herein or one or more target-specific primers designed using the primer design standards outlined herein. In one embodiment, a forensic sample or human identification sample containing at least one target sequence can be amplified using any one or more target-specific primers disclosed herein or using the primer standards outlined herein.

[0162] The components of the structural variant-aware sequencing system 106 may include software, hardware, or both. For example, the components of the structural variant-aware sequencing system 106 may include one or more instructions stored on a computer-readable storage medium and executable by a processor of one or more computing devices (e.g., client devices 114). When executed by one or more processors, the computer-executable instructions of the structural variant-aware sequencing system 106 may cause the computing device to perform the bubble detection method described herein. Alternatively, the components of the structural variant-aware sequencing system 106 may include hardware, such as a dedicated processing device for performing a certain function or group of functions. Additionally or alternatively, the components of the structural variant-aware sequencing system 106 may include a combination of computer-executable instructions and hardware.

[0163] In addition, the components of the structural variant-aware sequencing system 106 that perform the functions described herein for the structural variant-aware sequencing system 106 can be implemented, for example, as part of a stand-alone application, as a module of an application, as a plug-in for an application, as one or more library functions that can be detected by other applications, and / or as a cloud computing model. Therefore, the components of the structural variant-aware sequencing system 106 can be implemented as part of a stand-alone application on a personal computing device or a mobile device. Additionally or alternatively, the components of the structural variant-aware sequencing system 106 can be implemented in any application that provides sequencing services, including but not limited to Illumina BaseSpace, Illumina DRAGEN, or Illumina TruSight software. "Illumina", "BaseSpace", "DRAGEN", and "TruSight" are registered trademarks or trademarks of Illumina, Inc. in the United States and / or other countries.

[0164] As discussed in more detail below, embodiments of the present disclosure may include or utilize a special-purpose or general-purpose computer including computer hardware (such as, for example, one or more processors and system memory). Embodiments within the scope of the present disclosure also include physical and other computer-readable media for carrying or storing computer-executable instructions and / or data structures. Specifically, one or more of the processes described herein may be implemented at least in part as instructions embodied in a non-transitory computer-readable medium and executable by one or more computing devices (e.g., any of the media content access devices described herein). In general, a processor (e.g., a microprocessor) receives instructions from a non-transitory computer-readable medium (e.g., a memory, etc.) and executes those instructions, thereby performing one or more processes, including one or more of the processes described herein.

[0165] Computer readable media can be any available media that can be accessed by a general or special purpose computer system. A computer readable medium that stores computer executable instructions is a non-transitory computer readable storage medium (device). A computer readable medium that carries computer executable instructions is a transmission medium. Therefore, by way of example and not limitation, embodiments of the present disclosure may include at least two distinct types of computer readable media: a non-transitory computer readable storage medium (device) and a transmission medium.

[0166] Non-transitory computer-readable storage media (devices) include RAM, ROM, EEPROM, CD-ROM, solid-state drives (SSD) (e.g., RAM-based), flash memory, phase-change memory (PCM), other types of memory, other optical disk storage devices, magnetic disk storage devices or other magnetic storage devices, or any other media that can be used to store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general or special purpose computer.

[0167] "Network" is defined as one or more data links that enable the transmission of electronic data between computer systems and / or modules and / or other electronic devices. When information is transferred or provided to a computer via a network or another communication connection (hardwired, wireless, or a combination of hardwired or wireless), the computer appropriately regards the connection as a transmission medium. The transmission medium may include a network and / or data link, which can be used to carry the desired program code means in the form of computer executable instructions or data structures, and which can be accessed by general or special computers. The above combinations should also be included in the scope of computer-readable media.

[0168] Furthermore, upon reaching various computer system components, program code means in the form of computer executable instructions or data structures may be automatically transferred from a transmission medium to a non-transitory computer readable storage medium (device) (or vice versa). For example, a computer executable instruction or data structure received over a network or data link may be buffered in RAM within a network interface module (e.g., NIC), and then ultimately transferred to the computer system RAM and / or to a less volatile computer storage medium (device) at the computer system. Thus, it should be understood that a non-transitory computer readable storage medium (device) may be included in a computer system component that also (or even primarily) utilizes a transmission medium.

[0169] Computer executable instructions include, for example, instructions and data that make a general-purpose computer, a special-purpose computer, or a special-purpose processing device perform a certain function or function group when executed at a processor. In some embodiments, computer executable instructions are executed on a general-purpose computer to turn a general-purpose computer into a special-purpose computer that implements an element of the present disclosure. Computer executable instructions can be, for example, binary numbers, intermediate format instructions such as assembly language, or even source code. Although the subject matter has been described in a language specific to structural features and / or method actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the described features or actions. On the contrary, the described features and actions are disclosed as exemplary forms of implementing the claims.

[0170] Those skilled in the art will appreciate that the present disclosure can be practiced in a network computing environment with many types of computer system configurations, including personal computers, desktop computers, portable computers, message processors, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile phones, PDAs, tablet computers, pagers, routers, switches, etc. The present disclosure can also be practiced in a distributed system environment, where both local and remote computer systems linked by a network (by a hardwired data link, a wireless data link, or a combination of hardwired and wireless data links) perform tasks. In a distributed system environment, program modules can be located in both local and remote memory storage devices.

[0171] Embodiments of the present disclosure may also be implemented in a cloud computing environment. In this specification, "cloud computing" is defined as a model for implementing on-demand network access to a shared pool of configurable computing resources. For example, cloud computing may be employed in the marketplace to provide ubiquitous and convenient on-demand access to a shared pool of configurable computing resources. A shared pool of configurable computing resources may be quickly provisioned via virtualization and released with low management effort or service provider interaction, and then scaled accordingly.

[0172] The cloud computing model may consist of various characteristics, such as, for example, on-demand self-service, broad network access, resource pooling, rapid elasticity, metered services, etc. The cloud computing model may also exhibit various service models, such as, for example, software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS). The cloud computing model may also be deployed using different deployment models, such as private cloud, community cloud, public cloud, hybrid cloud, etc. In this specification and in the claims, a "cloud computing environment" is an environment in which cloud computing is employed.

[0173] Fig.10 1000 is a block diagram of a computing device 1000 that can be configured to perform one or more of the above processes. It will be appreciated that one or more computing devices such as computing device 1000 can implement the structural variant-aware sequencing system 106 and the structural variant-aware sequencing system 106. Fig.10 As shown, computing device 1000 may include a processor 1002, memory 1004, storage device 1006, I / O interface 1008, and communication interface 1010 that may be communicatively coupled via communication infrastructure 1012. In some embodiments, computing device 1000 may include Fig.10 The following paragraphs describe in more detail Fig.10 Components of computing device 1000 are shown.

[0174] In one or more embodiments, the processor 1002 includes hardware for executing instructions such as those constituting a computer program. As an example and not by way of limitation, in order to execute instructions for dynamically modifying a workflow, the processor 1002 may retrieve (or fetch) instructions from an internal register, an internal cache, a memory 1004, or a storage device 1006, and decode and execute them. The memory 1004 may be a volatile or non-volatile memory for storing data, metadata, and programs executed by the processor. The storage device 1006 includes a storage device for storing data or instructions for executing the methods described herein, such as a hard disk, a flash drive, or other digital storage device.

[0175] I / O interface 1008 allows a user to provide input to computing device 1000, receive output from the computing device and otherwise transfer data to the computing device and receive data from the computing device. I / O interface 1008 may include a combination of a mouse, a keypad or keyboard, a touch screen, a camera, an optical scanner, a network interface, a modem, other known I / O devices or such I / O interfaces. I / O interface 1008 may include one or more devices for presenting output to a user, including but not limited to a graphics engine, a display (e.g., a display screen), one or more output drivers (e.g., a display driver), one or more audio speakers and one or more audio drivers. In certain embodiments, I / O interface 1008 is configured to provide graphics data to a display for presentation to a user. Graphics data may represent one or more graphical user interfaces and / or may serve any other graphical content of a specific implementation.

[0176] The communication interface 1010 may include hardware, software, or both. In any case, the communication interface 1010 may provide one or more interfaces for communication (such as, for example, packet-based communication) between the computing device 1000 and one or more other computing devices or networks. As an example and not by way of limitation, the communication interface 1010 may include a network interface controller (NIC) or network adapter for communicating with an Ethernet or other wired-based network, or a wireless NIC (WNIC) or wireless adapter for communicating with a wireless network such as WI-FI.

[0177] Additionally, the communication interface 1010 can facilitate communication with various types of wired or wireless networks. The communication interface 1010 can also facilitate communication using various communication protocols. The communication infrastructure 1012 can also include hardware, software, or both that couple the components of the computing device 1000 to each other. For example, the communication interface 1010 can use one or more networks and / or protocols to enable multiple computing devices connected through a particular infrastructure to communicate with each other to perform one or more aspects of the processes described herein. For illustration, the sequencing process can allow multiple devices (e.g., client devices, sequencing devices, and server devices) to exchange information such as sequencing data and error notifications.

[0178] In the foregoing description, the present disclosure has been described with reference to specific exemplary embodiments thereof. Various embodiments and aspects of the present disclosure are described with reference to the details discussed herein, and the accompanying drawings illustrate various embodiments. The above description and drawings are illustrative of the present disclosure and should not be construed as limiting the present disclosure. Many specific details are described to provide a thorough understanding of the various embodiments of the present disclosure.

[0179] The present disclosure can be embodied in other specific forms without departing from its spirit or essential characteristics. The embodiments described should be considered as being only exemplary and not restrictive in all respects. For example, the methods described herein can be performed with fewer or more steps / actions, or the steps / actions can be performed in different orders. Additionally, the steps / actions described herein can be repeated or performed in parallel with each other or in parallel with different examples of the same or similar steps / actions. Therefore, the scope of the application is indicated by the appended claims rather than the foregoing description. All changes within the equivalent meaning and scope of the claims will be included within their scope.

Claims

1. A non-transitory computer-readable medium comprising instructions that, when executed by at least one processor, cause a computing device to: identifying candidate structural variants that meet a threshold amount of occurrence within a database of genomic samples; selecting a structural variant haplotype from among the candidate structural variants; identifying a reference haplotype from a linear reference genome that corresponds to the structural variant haplotype; and A structural variation map genome is generated that includes alternating contiguous sequences representing the structural variant haplotypes and a reference sequence representing the reference haplotypes.

2. The non-transitory computer-readable medium of claim 1, further comprising instructions that, when executed by the at least one processor, cause the computing device to select the structural variant haplotype in the following manner: selecting a specific structural variant haplotype from the candidate structural variants that satisfies a threshold amount of additional occurrences at a specific genomic region.

3. The non-transitory computer-readable medium of claim 1, further comprising instructions which, when executed by the at least one processor, cause the computing device to select the structural variant haplotype in the following manner: selecting a specific structural variant haplotype adjacent to a specific flanking variant within a nucleotide sequence of the genomic sample database.

4. The non-transitory computer-readable medium of claim 3, further comprising instructions that, when executed by the at least one processor, cause the computing device to select the particular structural variant haplotype by: Selecting a first structural variant haplotype that is in phase with a first flanking variant within a first nucleotide sequence in the genomic sample database; and A second structural variant haplotype that is in phase with a second flanking variant within a second nucleotide sequence in the genomic sample database is selected.

5. The non-transitory computer-readable medium of claim 3, further comprising instructions that, when executed by the at least one processor, cause the computing device to generate the structural variation map genome comprising specific alternating continuous sequences representing the specific structural variant haplotype and the specific flanking variant.

6. The non-transitory computer readable medium of claim 3, wherein the flanking variant comprises a single nucleotide polymorphism (SNP), a deletion of less than fifty base pairs, or an insertion of less than fifty base pairs.

7. The non-transitory computer-readable medium of claim 1 , further comprising instructions that, when executed by the at least one processor, cause the computing device to: identifying, from the genomic sample database, an alternate haplotype comprising one or more of a single nucleotide polymorphism (SNP), a deletion of less than fifty base pairs, or an insertion of less than fifty base pairs; and Generating the structural variation map genome further comprising alternate nucleobases or additional alternate continuous sequences representing the alternate haplotypes.

8. The non-transitory computer-readable medium of claim 1, further comprising instructions that, when executed by the at least one processor, cause the computing device to identify the candidate structural variants by selecting structural variants representing one or more of a deletion of more than fifty base pairs, an insertion of more than fifty base pairs, a duplication of more than fifty base pairs, an inversion, a translocation, or a copy number variation (CNV).

9. The non-transitory computer-readable medium of claim 1, wherein the at least one processor comprises a configurable processor and executing the at least one processor comprises configuring the configurable processor.

10. A system, comprising: at least one processor; and a non-transitory computer readable medium comprising instructions that, when executed by the at least one processor, cause the system to: identifying candidate structural variants that meet a threshold amount of occurrence within a database of genomic samples; selecting a structural variant haplotype from among the candidate structural variants; identifying a reference haplotype from a linear reference genome that corresponds to the structural variant haplotype; and A structural variation map genome is generated that includes alternating contiguous sequences representing the structural variant haplotypes and a reference sequence representing the reference haplotypes.

11. The system of claim 10, further comprising instructions that, when executed by the at least one processor, cause the system to select the structural variant haplotype by: selecting a first structural variant haplotype from the candidate structural variants that satisfies a threshold amount of additional occurrence at a first genomic region; and A second structural variant haplotype is selected from the candidate structural variants that satisfies the threshold amount of additional occurrences at a second genomic region.

12. The system of claim 10, further comprising instructions that, when executed by the at least one processor, cause the system to select the structural variant haplotype by: Selecting a first structural variant haplotype adjacent to a first flanking variant within a first nucleotide sequence in the genomic sample database; and A second structural variant haplotype adjacent to a second flanking variant within a second nucleotide sequence in the genomic sample database is selected.

13. The system of claim 12, wherein the first flanking variant or the second flanking variant comprises a single nucleotide polymorphism (SNP), a deletion of less than a threshold number of base pairs, or an insertion of less than the threshold number of base pairs.

14. The system of claim 12, further comprising instructions that, when executed by the at least one processor, cause the system to identify the candidate structural variants by selecting structural variants representing one or more of a deletion exceeding a threshold number of base pairs, an insertion exceeding the threshold number of base pairs, a duplication exceeding the threshold number of base pairs, an inversion, a translocation, or a copy number variation (CNV).

15. The system of claim 12, further comprising instructions that, when executed by the at least one processor, cause the system to generate the structural variation graph genome comprising: a first alternating contiguous sequence representing a first structural variant haplotype and a first flanking variant; and A second alternating contiguous sequence representing a second structural variant haplotype and a second flanking variant.

16. The system of claim 10, further comprising instructions that, when executed by the at least one processor, cause the system to: generating an alignment file that maps the structural variant haplotypes to the genomic coordinates of the reference haplotypes within the linear reference genome; and The structural variation map genome is generated by associating the alternating contiguous sequences representing the structural variant haplotypes with identifiers of the genomic coordinates of the reference haplotypes within an organized structure.

17. The system of claim 16, further comprising instructions that, when executed by the at least one processor, cause the system to: generating the alignment file by generating a sequence alignment / map (SAM) boost file that maps the structural variant haplotypes to the genomic coordinates of the reference haplotype; and The structural variation map genome is generated using the organizational structure by associating nucleobase identifiers of nucleobases from the alternating contiguous sequence with values ​​of the genomic coordinates representing the reference haplotype within a hash table.

18. The system of claim 10, further comprising instructions that, when executed by the at least one processor, cause the system to generate the structural variation map genome by sorting a subset of alternating contiguous sequences corresponding to genomic regions according to their frequencies within the genomic sample database.

19. A method comprising: identifying nucleotide reads from genomic samples; aligning a subset of nucleotide reads to alternating contiguous sequences representing structural variant haplotypes within the structural variation map genome; as well as One or more nucleobase calls are generated for the genomic sample based on a subset of the aligned nucleotide reads.

20. The method of claim 19, further comprising generating an alignment file or variant call file comprising annotations indicating the structural variant haplotype corresponding to the one or more nucleobase calls.

21. The method of claim 19, further comprising generating an alignment file or variant call file comprising annotations indicating the frequency of the structural variant haplotype corresponding to the one or more nucleobase calls within a genomic sample database.

22. The method of claim 19, further comprising generating an alignment file or variant call file comprising genomic coordinates of a linear reference genome that is part of the structural variation map genome and corresponds to the one or more nucleobase calls.

23. The method according to claim 19, further comprising: determining that a subset of the nucleotide reads overlaps with breakpoints of the alternating contiguous sequence representing the structural variant haplotype; as well as An alignment file or variant call file is generated that includes annotations indicating alignments that reflect the structural variant haplotype within the genomic sample.

24. The method according to claim 19, further comprising: determining that an alignment score for the subset of nucleotide reads does not satisfy a threshold alignment score for a candidate alignment between the subset of nucleotide reads and a primary assembled region of a linear reference genome; as well as A variant call file or an alignment file is generated with the one or more nucleobase calls for the genomic sample based on a subset of the aligned nucleotide reads to the alternating contiguous sequence, and a variant call file or an alignment file is generated without the nucleobase calls for the genomic sample based on the candidate alignments that do not meet the threshold alignment score.

25. The method of claim 19, wherein the structural variant haplotype comprises a deletion of more than fifty base pairs, an insertion of more than fifty base pairs, a duplication, an inversion, a translocation, or a copy number variation (CNV).

26. The method of claim 19, wherein the structural variant haplotype comprises a deletion exceeding a threshold number of base pairs, an insertion exceeding the threshold number of base pairs, a duplication exceeding the threshold number of base pairs, an inversion, a translocation, or a copy number variation (CNV).

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