Gene mutation detection methods, devices, terminal equipment, and readable storage media

Abstract

This application provides a method, apparatus, terminal device, and readable storage medium for gene variation detection. The method involves: acquiring a BAM file; extracting fusion signals from the BAM file and outputting detection results; merging split reads and discordant paired reads with identical gene fusion pairs and the same exons or introns at the breakpoints; performing structural variation detection on the BAM file using pre-set detection software, and annotating the fusion detection results to obtain annotation results; merging the annotation results and the merged sequences to obtain structural variation results; constructing a ref to obtain a spliced ​​sequence; performing a re-alignment on the spliced ​​sequence, and calculating the fusion value of the spliced ​​sequence when it is determined to be a sequence supporting a fusion event based on the re-alignment results; calculating the final fusion value for each gene pair based on the fusion value; and determining the final structural variation gene pair based on the final fusion value. This method enables comprehensive structural variation detection of DNA data.

Description

Technical Field

[0001] This application relates to the field of data processing technology, specifically to a gene variation detection method, apparatus, terminal device, and computer-readable storage medium. Background Technology

[0002] Gene mutation detection, also known as high-throughput mutation detection, works by randomly fragmenting sample DNA and performing high-throughput sequencing to obtain a large number of reads. Bioinformatics analysis software is then used to align the reads to a reference genome to obtain the location information of each read on the reference genome.

[0003] The purpose of high-throughput clinical testing is to detect gene variations in patients, annotate and interpret these variations to guide clinical diagnosis and treatment. These variations include point mutations (SNVs), insertion / deletion mutations (INDELs), structural variations (SVs), and copy number changes (CNVs). Major structural variations (SVs) are the most important. It is estimated that each human genome contains over 20,000 structural variations, which may lead to over 1,000 diseases, such as ALS, schizophrenia, and cancer. As a major genetic marker of the tumor genome, structural variations affect the expression of tumor-related functional genes and drive tumor development. Therefore, accurate detection of tumor structural variations is a crucial step in cancer diagnosis and treatment and is a current research focus. Inferring tumor development and identifying tumor-targeting genes through gene structural variations provides important evidence for tumor diagnosis and treatment.

[0004] Genomic structural variations can be categorized into large-fragment (greater than 50 bp) insertions, deletions, inversions, translocations, and duplications. Since high-throughput sequencing produces short reads, while structural variation fragments are generally longer, bioinformatics analysis of structural variations in high-throughput sequencing data employs two methods: First, it utilizes information about the breakpoints of structural variations for identification. This involves a read where part aligns to one location in the genome, and another part aligns to a different location; these are called split reads (reads covering the breakpoint). If a complete gene cannot be fully aligned during alignment, the alignment software attempts to match other genes using a more lenient local alignment. If a match is found, this portion of the sequence is preserved and labeled with a CIGAR value. This mechanism is called soft-clipped, and these reads will be referred to as SC reads. Second, there are discordant-paired reads, where the pair of reads has an anomalous relationship, with one read aligning to one gene and another to a different gene.

[0005] Compared to pair-read methods for identifying structural variants (SVs), split-read methods can be accurate to individual bases. However, because the number of reads is generally smaller, and the tolerance for experimental interruptions and data noise is lower, using split-read methods alone for SV identification can sometimes lead to insufficient accuracy and an excessive number of false positives. In addition, there are de novo assembly and sequencing methods for the above structural variant types, which have relatively high requirements for assembly accuracy and quality.

[0006] Existing SV detection software is primarily based on split reads and discordant pair reads. However, due to the lack of a "gold standard," different software programs vary in their internal filtering conditions, detection methods, and various parameters. The types of structural variations that existing software can detect also differ. While all the above software programs can perform partial detection of structural variations, few can guarantee both sensitivity and accuracy in detecting all five types of structural variations. For example, LUMPY software mainly detects deletions, duplications, inversions, and translocations, and has limitations in detecting insertions. Manta software can detect all five types—insertions, deletions, translocations, inversions, and duplications—but its detection sensitivity is low after standard testing, exhibiting instability that can lead to missed detections. Summary of the Invention

[0007] In view of this, the present application provides a gene mutation detection method, apparatus, terminal device and computer-readable storage medium to overcome the problems of poor sensitivity and accuracy of gene mutation detection in the prior art.

[0008] In a first aspect, embodiments of this application provide a method for detecting gene mutations, the method comprising: obtaining a BAM file; wherein the BAM file is a sequencing file obtained by high-throughput sequencing of a sequencing sample and then aligned with a reference genome;

[0009] Perform fusion signal detection on the BAM file to output split reads detection results and discordant-paired reads detection results;

[0010] Based on the results of the split reads detection and the discordant paired reads detection, split reads and discordant paired reads that correspond to the same gene and have the same exons or introns at the breakpoints are merged to obtain a merged sequence.

[0011] The merged sequence is subjected to structural variation detection using preset detection software, and the abnormal detection results are annotated to obtain the annotation results;

[0012] The annotation results and the merged sequence are merged to obtain the structural variation results;

[0013] Based on the structural variation results, ref construction is performed using the breakpoint locations of the genes to obtain the spliced ​​sequence;

[0014] The spliced ​​sequence is re-aligned, and the spliced ​​sequence is determined to be a sequence that supports fusion events based on the re-alignment results;

[0015] If so, calculate the fusion value of the spliced ​​sequences;

[0016] The final fusion value of each gene pair is calculated based on the fusion value of the spliced ​​sequence;

[0017] The final structural variant gene pair is determined based on the final fusion value.

[0018] Secondly, embodiments of this application provide a gene mutation detection device, the device comprising:

[0019] The BAM file acquisition module is used to acquire BAM files; wherein the BAM file is a sequencing file obtained by high-throughput sequencing of sequencing samples and then aligned with a reference genome.

[0020] The signal detection module is used to perform fusion signal detection on the BAM file to output the detection results of split reads and discordant paired reads.

[0021] The first merging module is used to merge split reads and discordant paired reads that correspond to the same gene and have the same exons or introns at the breakpoint, based on the split reads detection results and the discordant paired reads detection results, to obtain a merged sequence.

[0022] The mutation detection module is used to perform structural mutation detection on the BAM file using preset detection software, and to annotate the mutation detection results to obtain annotation results.

[0023] The second merging module is used to merge the annotation results and the merging sequence to obtain the structural variation results;

[0024] The Ref construction module is used to construct refs based on the structural variation results and the breakpoint positions of genes to obtain the spliced ​​sequence;

[0025] The judgment module is used to perform a re-comparison on the spliced ​​sequence and determine whether the spliced ​​sequence is a sequence that supports fusion events based on the re-comparison result;

[0026] The fusion value calculation module is used to calculate the fusion value of the spliced ​​sequence when the spliced ​​sequence is a sequence that supports fusion events;

[0027] The final fusion value calculation module is used to calculate the final fusion value of each pair of genes based on the fusion value of the spliced ​​sequence;

[0028] A variant gene pair determination module is used to determine the final structural variant gene pair based on the final fusion value.

[0029] Thirdly, embodiments of this application provide a terminal device, including: a memory; one or more processors coupled to the memory; and one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the one or more processors, and the one or more application programs are configured to perform the gene variation detection method provided in the first aspect above.

[0030] Fourthly, embodiments of this application provide a computer-readable storage medium storing program code, which can be called by a processor to execute the gene mutation detection method provided in the first aspect.

[0031] The gene variation detection method, apparatus, terminal device, and computer-readable storage medium provided in this application embodiment obtain a BAM file; wherein the BAM file is a sequencing file obtained by high-throughput sequencing of sequencing samples and obtained by comparison with a reference genome; fusion signal detection is performed on the BAM file to output split read detection results and discordant paired read detection results; based on the split read detection results and discordant paired read detection results, split reads and discordants corresponding to the same gene and with the same exon or intron at the breakpoint are paired. Paired reads are merged to obtain a merged sequence; structural variation detection is performed on the BAM file using pre-defined detection software, and the variation detection results are annotated to obtain annotation results; the annotation results and the merged sequence are merged to obtain structural variation results; based on the structural variation results, refs are constructed using gene breakpoints to obtain spliced ​​sequences; the spliced ​​sequences are re-aligned, and the re-alignment results are used to determine whether the spliced ​​sequences support fusion events; if so, the fusion value of the spliced ​​sequences is calculated; the final fusion value of each gene pair is calculated based on the fusion value of the spliced ​​sequences; the final structural variation gene pairs are determined based on the final fusion value.

[0032] The gene variation detection method in this application embodiment, based on split reads and discordant paired reads and incorporating pre-set detection software, can perform structural variation detection for multiple variation types, thus achieving comprehensive structural variation detection of DNA data; the detection of all variation types ensures both sensitivity and accuracy. Furthermore, the reliability of the final output is increased through sequence splicing-realignment verification. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0034] Figure 1 This is a schematic diagram illustrating an application scenario of the gene mutation detection method provided in the embodiments of this application;

[0035] Figure 2 A schematic flowchart of a gene mutation detection method provided in one embodiment of this application;

[0036] Figure 3 A schematic diagram of a fusion signal provided in one embodiment of this application;

[0037] Figure 4 This is a schematic diagram of a splicing sequence provided in one embodiment of this application;

[0038] Figure 5 This is a schematic diagram of the structure of a terminal device provided in one embodiment of this application;

[0039] Figure 6 This is a schematic diagram of the structure of a computer-readable storage medium provided in one embodiment of this application. Detailed Implementation

[0040] The technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0041] To provide a more detailed description of this application, the following description, in conjunction with the accompanying drawings, details a gene variation detection method, apparatus, terminal device, and computer-readable storage medium provided in this application.

[0042] Please refer to Figure 1 , Figure 1 This illustration shows an application scenario of the gene mutation detection method provided in this application embodiment. The application scenario includes a terminal device 100 provided in this application embodiment. The terminal device 100 can be various electronic devices with a display screen (such as structural diagrams 102, 104, 106, and 108), including but not limited to smartphones and computer devices. The computer device can be at least one of a desktop computer, portable computer, laptop computer, tablet computer, etc. Terminal device 100 can refer to one of multiple terminal devices; this embodiment only uses terminal device 100 as an example. Those skilled in the art will understand that the number of terminal devices can be more or less. For example, there may be only a few terminal devices, or dozens or hundreds of terminal devices, or even more. This application embodiment does not limit the number and type of terminal devices. Terminal device 100 can be used to execute a gene mutation detection method provided in this application embodiment.

[0043] In one optional implementation, the application scenario may include not only the terminal device 100 provided in this embodiment, but also a server, wherein a network is established between the server and the terminal device. The network serves as a medium for providing a communication link between the terminal device and the server. The network may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0044] It should be understood that the number of terminal devices, networks, and servers is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be used. For example, a server can be a server cluster composed of multiple servers. The terminal devices interact with the server through the network to receive or send messages, etc. The server can provide various services. The server can be used to execute steps in the gene mutation detection method provided in this application embodiment, excluding visualization (e.g., aggregated data display). Furthermore, when executing the gene mutation detection method provided in this application embodiment, some steps can be executed on the terminal device and some steps on the server; this is not limited here.

[0045] Based on this, this application provides a method for detecting gene mutations. Please refer to [link / reference]. Figure 2 , Figure 2 This paper illustrates a flowchart of a gene variation detection method provided in an embodiment of this application, demonstrating its application in... Figure 1 Taking a terminal device as an example, the explanation includes the following steps:

[0046] Step S110: Obtain the bam file.

[0047] The BAM file is a sequencing file obtained by high-throughput sequencing of sequencing samples and then aligned with a reference genome.

[0048] Specifically, a BAM file, also known as an alignment BAM file, is obtained by aligning a sequencing file (i.e., an FQ file) generated through high-throughput sequencing with a BWA. The sequencing sample can be any DNA sample, RNA sample, etc., that can be sequenced using high-throughput sequencing.

[0049] Step S120: Perform fusion signal detection on the BAM file to output the split reads detection results and discordant paired reads detection results.

[0050] The fusion signal refers to the signal generated in the BAM file when gene fusion occurs. This signal can be used to identify which genes(s) have fused. Gene fusion refers to the fusion of partial or complete sequences of two different genes due to some mechanism (such as genomic variation), forming a new gene.

[0051] Fusion signals mainly fall into two categories: one is the fusion signal of split reads, also known as the fusion signal of soft-clipped reads; the other is the fusion signal of discordant paired-end reads. Please refer to [link / reference needed] for details. Figure 3 As shown, Figure 3 Two types of fused signals are shown. The two types of reads that are fused are soft-clipped reads (i.e., split reads) that cross the breakpoint, and discordant paired-end reads that match the breakpoint twice.

[0052] By performing fusion signal detection on BAM files, structural variation detection and analysis can be performed on BAM files, and split read detection results and discordant paired read detection results can be obtained.

[0053] In one embodiment, step S120, which involves detecting fusion signals in the BAM file to output split reads detection results and discordant paired reads detection results, includes: detecting S signals in the BAM file, calculating the breakpoints where fusion occurs based on alignment information, and outputting split reads detection results; wherein the split reads detection results include information on each gene that has fused and information on the breakpoints where fusion occurs between genes.

[0054] Specifically, the fusion signal of split reads is represented as an S signal in the BAM file. S is an abbreviation for softclip in high-throughput sequencing BAM files. 83M10S indicates that the sequence is 93 bp in total, of which 83 bp aligned to a position such as chr1***822524 as the initial alignment location. 10S indicates that the alignment of the remaining 10 bp to a position in the genome is uncertain. This is the principle behind fusion softclip detection, and the sequence information of this signal needs to be extracted. Typically, the S signal appears in the 6th column of the BAM file.

[0055] After determining the S signal, the breakpoints where fusion occurs can be calculated based on the alignment information, and the original split read detection results can be output. The split read detection results include information about each gene involved in the fusion and the breakpoint information between the fusions; for example, if the genes involved in the fusion are gene1 and gene2, the breakpoint information for the fusion between gene1 and gene2, etc. In addition, the split read detection results also include information such as the number of reads involved in the fusion.

[0056] In one embodiment, step S120 involves detecting fusion signals in the BAM file to output split read detection results and discordant paired read detection results. This includes: detecting the length of the inserted fragment in the BAM file; when the length of the inserted fragment is greater than a preset length value, normalizing the comparison positions; selecting discordant reads whose comparison positions after distance normalization are within a preset range for clustering; recording the median value of the comparison positions obtained after clustering as the breakpoint of fusion; and outputting discordant paired read detection results based on the fusion breakpoint. The discordant paired read detection results include information on each gene involved in the fusion and information on the breakpoints between genes where fusion occurs.

[0057] Specifically, discordant paired read fusion mainly falls into two categories: one where a pair of discordant reads aligns to the same chromosome, and the other where they align to different chromosomes. In the case where a pair of discordant reads aligns to the same chromosome, the insert fragment length is abnormally large. This abnormally large insert fragment length can be used as a discordant paired read fusion signal. The insert fragment is located in column 9 of the alignment BAM file. A normal insert fragment length fluctuates around 200 bp. An excessively large insert fragment indicates that the sequencing reads may have aligned to two genes in the reference genome, which is a signal of discordant read fusion.

[0058] The preset length value can be a pre-set value, usually greater than 200bp, and the specific value can be set according to actual needs.

[0059] When the length of the inserted fragment exceeds a preset length value, it indicates that discordant read fusion has occurred. Then, the alignment positions can be normalized, and then a clustering algorithm can be used to select discordant reads whose alignment positions are within a preset range (e.g., within 200 bp) for clustering. The median value of all read alignment positions is selected as the breakpoint to output the original discordant read detection results.

[0060] In one embodiment, step S120 involves detecting fusion signals in the BAM file to output split read detection results and discordant paired read detection results. This includes: detecting the length of the inserted fragment and the chromosomes corresponding to the paired-end reads in the BAM file; when the length of the inserted fragment is 0 and the paired-end reads correspond to different chromosomes, normalizing the comparison positions; selecting discordant reads whose comparison positions after distance normalization are within a preset range for clustering; recording the median value of the comparison positions obtained after clustering as the breakpoint of fusion; and outputting discordant paired read detection results based on the fusion breakpoints. The discordant paired read detection results include information on each gene that has undergone fusion and information on the breakpoints where fusion occurs between genes.

[0061] When a pair of discordant paired reads aligns to different chromosomes, the insert length is 0. Specifically, in the BAM file, the insert length in column 9 is 0, but columns 3 and 7 represent the chromosomes aligned to by reads1 and reads2 of a pair of PE reads, respectively. If the chromosome numbers are different, it can be identified as a translocation-type structural variation.

[0062] When the inserted fragment length is 0 and paired-end reads correspond to different chromosomes, it indicates that discordant read fusion has occurred. Then, the alignment positions can be normalized, and a clustering algorithm can be used to select discordant reads whose alignment positions are within a preset range (e.g., within 200 bp) for clustering. The median value of all read alignment positions is selected as the breakpoint to output the original discordant read detection results.

[0063] Step S130: Based on the split read detection results and discordant paired read detection results, split reads and discordant paired reads that correspond to the same gene and have the same exons or introns at the breakpoint are merged to obtain the merged sequence.

[0064] Since both split reads and discordant paired reads are gene fusions, split reads and discordant paired reads annotated to the same gene and with identical breakpoint exons / introns can be merged to produce a merged sequence. The last column of the output merged sequence can be tagged with SC and PE. SC indicates split reads (reads crossing breakpoints), and PE indicates discordant paired reads (reads not crossing breakpoints). Furthermore, annotation software can be used to annotate the fusion information in the SC and PE sections, with the annotation results including gene, transcript, and information about the exon or intron where the breakpoint is located.

[0065] Step S140: Use preset detection software to perform structural variation detection on the BAM file, and annotate the variation detection results to obtain the annotation results.

[0066] The pre-defined detection software is a structural variation detection software, such as Manta. Manta is a publicly available third-party software that can detect five types of structural variations. It is primarily developed for detecting germline variations in single samples and somatic variations in torsion / normal paired samples. It can discover, assemble, and score a wide range of SVs, medium-sized indels, and large insertions in a single workflow. Manta's continuous assembly method allows for base-level resolution, which is more beneficial for downstream annotation and clinical significance analysis. Manta accepts input BAM or CRAM format files and reports all SV and indel mutations in VCF4.1 format. However, the sensitivity of two-sample detection is low; therefore, in this embodiment, only the case bam is analyzed, and the fusion detection results from the software are integrated and annotated. The assembly algorithm of Manta is used to detect structural variations in the bam file, and the Manta software's structural variation information is annotated. This annotation result will be used as a parameter for later result filtering.

[0067] Step S150: The annotation results and the merged sequence are merged to obtain the structural variation results.

[0068] The detection results from the Manta software are merged into the merged sequence obtained in step S130 to complete the original detection results for the five types of structural variations.

[0069] Step S160: Based on the structural variation results, ref construction is performed through the breakpoint locations of the genes to obtain the spliced ​​sequence.

[0070] Specifically, based on the structural variation detection results, refs are constructed using the breakpoint locations of the genes. Reads are re-aligned and spliced ​​according to the fusion direction at the 5'-3' ends. There are multiple splicing methods, which can be determined according to the type of structural variation. For example, if the structural variation is of the insertion type, the structural variation containing the insertion fragment needs to be constructed by splicing the insertion sequence and its inverse complement sequence on the basis of the original four types of refs.

[0071] To facilitate understanding of the splicing process, a detailed example is provided. Assume that gene A and gene B are genes undergoing fusion, with breakpoints as shown in Table 1. The splicing method can then be:

[0072] Table 1 shows the distribution of breakpoints for gene A and gene B.

[0073]

[0074] Therefore, according to the 5'-3' connection method, there are a total of 8 types:

[0075] ①geneA_up+geneB_down

[0076] ②geneA_down_rev+geneB_down (geneA_down_rev is the reverse complement of geneA_down)

[0077] ③geneA_up + geneB_up_rev (geneB_up_rev is the reverse complement of geneB_up)

[0078] ④geneA_down_rev+geneB_up_rev (geneA_down_rev is the reverse complement of geneA_down, and geneB_up_rev is the reverse complement of geneB_up)

[0079] ⑤geneB_up+geneA_down

[0080] ⑥geneB_up + geneA_up_rev (geneA_up_rev is the reverse complement of geneA_up)

[0081] ⑦ geneB_down_rev + geneA_down (geneB_down_rev is the reverse complement of geneB_down)

[0082] ⑧geneB_down_rev+geneA_up_rev (geneB_down_rev is the reverse complement of geneB_down, and geneA_up_rev is the reverse complement of geneA_up)

[0083] Among them, ⑤ is the reverse complement of ④; ⑥ is the reverse complement of ③; ⑦ is the reverse complement of ②; and ⑧ is the reverse complement of ①. During the reference genome alignment process, these 8 types can be classified into 4 categories. Please refer to [the relevant documentation] for details. Figure 4 As shown.

[0084] Step S170: Perform a re-alignment on the spliced ​​sequence and determine whether the spliced ​​sequence is a sequence that supports fusion events based on the re-alignment result.

[0085] Step S180: If yes, calculate the fusion value of the spliced ​​sequence.

[0086] Step S190: Calculate the final fusion value of each pair of genes based on the fusion value of the spliced ​​sequences.

[0087] Step S1110: Determine the final structural variant gene pair based on the final fusion value.

[0088] In one embodiment, in performing step S1110, determining the final structural variant gene pair based on the final fusion value includes: selecting gene pairs corresponding to the final fusion value that is greater than the preset fusion value, and recording them as the initial structural variant gene pair; using a blacklist and a whitelist to screen and filter the initial structural variant gene pair in order to output the final structural variant gene pair.

[0089] Specifically, after the ref is constructed and the sequence is assembled, reads marked with the cigar value S in the 6th column of the BAM file can be extracted from the assembled sequence. BWA re-alignment is then performed. If a read can cross the structural variant sequence to assemble the ref and reach a given threshold, it is recorded as a read supporting the fusion event, and its fusion score is incremented by 1; otherwise, the score is not incremented. This calculation is repeated to obtain the score value for each pair of genes with structural variants. Based on the detection threshold (i.e., the preset fusion value), the final reliable structural variant gene pair is given. This method constructs highly accurate and reliable structural variant gene pairs, ensuring the reliability of the detection.

[0090] The gene variation detection method in this application embodiment, based on split reads and discordant paired reads and incorporating pre-set detection software, can perform structural variation detection for multiple variation types, thus achieving comprehensive structural variation detection of DNA data; the detection of all variation types ensures both sensitivity and accuracy. Furthermore, the reliability of the final output is increased through sequence splicing-realignment verification.

[0091] Next, an implementation method for constructing blacklists and whitelists is given, described in detail below:

[0092] In one embodiment, the gene mutation detection method further includes: constructing a blacklist and a whitelist of structural mutations based on a preset database; wherein the blacklist consists of homologous genes or pseudogenes; and the whitelist consists of one or more pre-configured structural mutation genes.

[0093] Specifically, the preset database can be the COSMIC database, etc. Based on the COSMIC database, a blacklist and whitelist of structural variants can be constructed, where the blacklist and whitelist are used to define different thresholds. The whitelist mainly includes hotspot structural variants, such as EML4-ALK; the blacklist mainly includes homologous genes or pseudogenes. By using the blacklist and whitelist, different thresholds and filters (i.e., setting screening conditions) can be applied to ensure the accuracy of hotspot genes and reduce the noisy output caused by blacklist genes, thereby reducing missed detections, improving accuracy, and reducing invalid fusion outputs.

[0094] Optionally, screening criteria may include, but are not limited to, pseudogenes, homologous genes, internal blacklists, intragene fusions, hotspots, and the presence of Manta rays.

[0095] Furthermore, an embodiment for calculating gene fusion frequencies is provided, as detailed below:

[0096] In one embodiment, after obtaining the merged sequence, the method further includes: calculating the gene fusion frequency, wherein the fusion frequency is calculated using the following formula:

[0097]

[0098] Where freq represents the fusion frequency of gene 1 and gene 2; split reads represent the number of breakpoints where split reads occur in gene 1 and gene 2; discordant paired reads represent the number of breakpoints where discordant paired reads occur in gene 1 and gene 2; depth(gene 1 split The distance () indicates the depth of the breakpoint in the splitreads where gene 1 undergoes fusion; depth(gene 2) represents the depth of the breakpoint in the splitreads. split The depth(gene1) indicates the depth of the breakpoint in the split reads where gene 2 undergoes fusion; discordant The depth(gene2) indicates the breakpoint of gene 1 in discordant paired reads where the fusion occurred; depth(gene2) discordant The value indicates the depth of the breakpoint in discordant paired reads where gene 2 undergoes fusion.

[0099] The numerator of the formula is the sum of split reads and discordant paired reads, representing all reads that indicate fusion. The denominator is the maximum depth of the two fused genes at four breakpoints (two breakpoints of split reads and two breakpoints of discordant paired reads).

[0100] This method can be used to calculate the frequency of structural variations, thereby enabling comprehensive structural variation detection in DNA data.

[0101] Example of effect:

[0102] To verify the detection effect of the gene mutation detection method in the embodiments of this application, a detailed example is provided. The gene mutation detection method of this application is used as a sample for verification, and the specific process is as follows:

[0103] S1, Data Preparation; Collect structural variation data of various known answers to validate the gene variation detection method. The collected standard data of existing answers are as follows:

[0104] 1) Horizon standard products HD753 and HD786 are shown in Table 2.

[0105] Table 2 lists Horizon's standard products HD753 and HD786.

[0106]

[0107]

[0108]

[0109] 2) National standard sample data: a total of 17 fusion-positive national standard samples were collected, and each sample was replicated in 3 batches; please refer to Table 3 for specific data.

[0110] Table 3 shows the data for national standard products.

[0111]

[0112]

[0113] 3) Enterprise reference data: a total of 6 fusion-positive national standard samples were collected. Each sample was tested in 3 batches. Please refer to Table 4 for specific data.

[0114] Table 4 shows the enterprise reference data.

[0115]

[0116]

[0117] S2 processes the raw files, including standard whole-genome sequencing workflows such as raw data quality control, alignment, sorting, deduplication, and quality value correction, to obtain the input files.

[0118] S3, integrating the original detection analysis, uses the gene variation detection method of this application to detect structural variations, and uses split reads and discordant reads to jointly determine the occurrence and breakpoints of structural variations, and provides breakpoint information.

[0119] S4, Annotation and Merging: Genes are annotated using annotation software, and split reads and discordant paired reads that match breakpoint exons and introns and are associated with the same gene are merged. Taking Horizon standards, HD753, and TESTCD210825002 as examples, the annotated and merged information includes gene name, breakpoint location and depth, number of supported reads, read type, positive and negative strand information for each gene, annotated exons / introns, and transcript names.

[0120] S5 analyzes and annotates the Manta software detection information. It calls Manta to perform structural variation detection on the BAM file and annotates the results. The results include intron / exon information, positive and negative strand information, gene and breakpoint information, as well as the types of variations detected by Manta and whether there are insertion variations. If an insertion variation is detected, the inserted sequence will be output.

[0121] S6 merges the results from the Manta software, integrating them into S3 to complete the five types of raw detection.

[0122] S7. Construct a structural variation blacklist and whitelist. Based on the database, construct the blacklist and whitelist. The whitelist is partially listed in Table 5.

[0123] Table 5 shows the whitelist.

[0124]

[0125]

[0126]

[0127] S8 involves constructing a structural variation reference sequence based on the breakpoint and re-aligning it. 200 sequences before and after the breakpoint are taken from the reference genome and assembled using four different modes, while simultaneously calculating the sequence complexity. Reads without breakpoints are filtered out, and the assembled sequences are linked with "N".

[0128] S9 calculates the score value based on the re-comparison results and outputs the final result. After re-comparing the standard data according to the above splicing ref, the score value is calculated, filtered, and the result is output. The filtered result will be recorded in another file.

[0129] S10, comparison results with the standard and detection performance.

[0130] Table 6 shows the comparison results and detection performance of the standard samples.

[0131]

[0132]

[0133] In this context, nan indicates that no detection was detected. This result shows that the fusion of different theoretical frequencies of the HD752 positive standard was detected.

[0134] Table 7 shows the comparison results and detection performance of the standard samples.

[0135]

[0136]

[0137] The result indicates that the HD786 positive standard has poor detection performance at the 0.5% detection limit, with more than 1% of samples missing one detection.

[0138] Table 8 shows the test results for national standard data.

[0139]

[0140] Among them, lot1, lot2, and lot3 represent three replicates. The results above show that the reference samples from all countries were detected 100% of the time.

[0141] Table 9 shows the test results for the enterprise's reference samples.

[0142]

[0143]

[0144] Lot1, Lot2, and Lot3 were repeated three times. The results show that all enterprise reference samples were detected 100% of the time.

[0145] It should be understood that, although Figure 2 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise explicitly stated in this document, there is no strict order in which these steps are executed; they can be performed in other orders. Figure 2 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0146] The above-described embodiments of this application disclose a method for detecting gene mutations. The above-described method can be implemented using various types of devices. Therefore, this application also discloses a gene mutation detection device corresponding to the above method. Specific embodiments are given below for detailed description.

[0147] This application discloses a gene mutation detection device, which mainly includes:

[0148] The BAM file acquisition module is used to acquire BAM files; BAM files are sequencing files obtained by high-throughput sequencing of sequencing samples and then aligned with a reference genome.

[0149] The signal detection module is used to perform fusion signal detection on the BAM file to output the detection results of split reads and discordant paired reads.

[0150] The first merging module is used to merge split reads and discordant paired reads that correspond to the same gene and have the same exons or introns at the breakpoint, based on the split reads detection results and discordant paired reads detection results, to obtain the merged sequence.

[0151] The mutation detection module is used to perform structural mutation detection on the BAM file using preset detection software, and to annotate the mutation detection results to obtain the annotation results.

[0152] The second merging module is used to merge the annotation results and the merging sequence to obtain the structural variation results;

[0153] The Ref building module is used to construct refs based on the structural variation results and the breakpoint locations of genes to obtain the spliced ​​sequence;

[0154] The judgment module is used to perform re-comparison on the spliced ​​sequence and determine whether the spliced ​​sequence is a sequence that supports fusion events based on the re-comparison results;

[0155] The fusion value calculation module is used to calculate the fusion value of the spliced ​​sequence when the spliced ​​sequence is a sequence that supports fusion events;

[0156] The final fusion value calculation module is used to calculate the final fusion value of each pair of genes based on the fusion value of the spliced ​​sequences;

[0157] The variant gene pair determination module is used to determine the final structural variant gene pairs based on the final fusion value.

[0158] In one embodiment, the apparatus further includes:

[0159] The list construction module is used to construct a blacklist and a whitelist of structural variations based on a preset database; wherein, the blacklist consists of homologous genes or pseudogenes; and the whitelist consists of one or more pre-configured structural variation genes.

[0160] In one embodiment, the final fusion value calculation module is used to select gene pairs corresponding to final fusion values ​​greater than a preset fusion value, and record them as initial structural variation gene pairs; and to screen and filter the initial structural variation gene pairs using a blacklist and a whitelist to output the final structural variation gene pairs.

[0161] In one embodiment, the signal detection module is used to perform S-signal detection on the bam file, calculate the breakpoints where fusion occurs based on the alignment information, and output the split reads detection results; wherein, the split reads detection results include information on each gene that has fused and information on the breakpoints where fusion occurs between each gene.

[0162] In one embodiment, the signal detection module is used to detect the length of the inserted fragment in the BAM file. When the length of the inserted fragment is greater than a preset length value, the comparison position is normalized. Discordant reads whose comparison positions after distance normalization are within a preset range are selected for clustering. The median value of the comparison positions obtained after clustering is recorded as the breakpoint of fusion. The discordant paired read detection result is output based on the breakpoint of fusion. The discordant paired read detection result includes information on each gene that has fused and information on the breakpoints where fusion occurs between genes.

[0163] In one embodiment, the signal detection module is used to detect the length of the inserted fragment and the chromosome corresponding to the paired-end reads in the BAM file; when the length of the inserted fragment is 0 and the paired-end reads correspond to different chromosomes, the comparison position is normalized; discrete reads whose comparison positions after distance normalization are within a preset range are selected for clustering; the median value of the comparison position obtained after clustering is recorded as the breakpoint of fusion; the discrete paired read detection result is output based on the fusion breakpoint; wherein, the discrete paired read detection result includes the information of each gene that has fused and the breakpoint information of the fusion between each gene.

[0164] In one embodiment, the apparatus further includes: a fusion frequency calculation module for calculating the fusion frequency of genes, wherein the fusion frequency is calculated using the following formula:

[0165]

[0166] Where freq represents the fusion frequency of gene 1 and gene 2; split reads represent the number of breakpoints where split reads occur in gene 1 and gene 2; discordant paired reads represent the number of breakpoints where discordant paired reads occur in gene 1 and gene 2; depth(gene 1 split The distance () indicates the depth of the breakpoint in the splitreads where gene 1 undergoes fusion; depth(gene 2) represents the depth of the breakpoint in the splitreads. split The depth(gene1) indicates the depth of the breakpoint in the split reads where gene 2 undergoes fusion; discordant The depth(gene2) indicates the breakpoint of gene 1 in discordant paired reads where the fusion occurred; depth(gene2) discordant The value indicates the depth of the breakpoint in discordant paired reads where gene 2 undergoes fusion.

[0167] Specific limitations regarding the gene mutation detection device can be found in the method limitations section above, and will not be repeated here. Each module in the aforementioned device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independently of the processor in the terminal device, or stored in software in the memory of the terminal device, so that the processor can call and execute the corresponding operations of each module.

[0168] Please refer to Figure 5 , Figure 5 This illustration shows a structural block diagram of a terminal device provided in an embodiment of this application. The terminal device 50 can be a computer device. The terminal device 50 in this application may include one or more of the following components: a processor 52, a memory 54, and one or more application programs. The one or more application programs may be stored in the memory 54 and configured to be executed by the one or more processors 52. The one or more application programs are configured to execute the methods described in the above-described method embodiments applied to the terminal device, and may also be configured to execute the methods described in the above-described method embodiments applied to gene variation detection.

[0169] Processor 52 may include one or more processing cores. Processor 52 connects to various parts within the terminal device 50 using various interfaces and lines, and performs various functions and processes data of the terminal device 50 by running or executing instructions, programs, code sets, or instruction sets stored in memory 54, and by calling data stored in memory 54. Optionally, processor 52 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). Processor 52 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem handles wireless communication. It is understood that the modem may also not be integrated into processor 52 and may be implemented separately using a communication chip.

[0170] The memory 54 may include random access memory (RAM) or read-only memory (ROM). The memory 54 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 54 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as touch functionality, sound playback functionality, image playback functionality, etc.), and instructions for implementing the various method embodiments described below. The data storage area may also store data created by the terminal device 50 during use.

[0171] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the solution of this application and does not constitute a limitation on the terminal device to which the solution of this application is applied. A specific terminal device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0172] In summary, the terminal device provided in this application embodiment is used to implement the corresponding gene mutation detection method in the foregoing method embodiment, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0173] Please see Figure 6This diagram illustrates a structural block diagram of a computer-readable storage medium provided in an embodiment of this application. The computer-readable storage medium 60 stores program code, which can be called by a processor to execute the methods described in the above-described gene mutation detection method embodiments.

[0174] The computer-readable storage medium 60 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. Optionally, the computer-readable storage medium 60 includes a non-transitory computer-readable storage medium. The computer-readable storage medium 60 has storage space for program code 62 that performs any of the method steps described above. This program code can be read from or written to one or more computer program products. The program code 62 may be compressed, for example, in a suitable form.

[0175] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0176] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting gene mutations, characterized in that, The method includes: Obtain the BAM file; wherein the BAM file is the sequencing file obtained by high-throughput sequencing of the sequencing sample and then aligned with a reference genome. Perform fusion signal detection on the BAM file to output the detection results of split reads and discordant paired reads; Based on the results of the split reads detection and the discordant paired reads detection, split reads and discordant paired reads that correspond to the same gene and have the same exons or introns at the breakpoints are merged to obtain a merged sequence. The BAM file is subjected to structural variation detection using preset detection software, and the variation detection results are annotated to obtain the annotation results; The annotation results and the merged sequence are merged to obtain the structural variation results; Based on the structural variation results, ref construction is performed using the breakpoint locations of the genes to obtain the spliced ​​sequence; The spliced ​​sequence is re-aligned, and the re-alignment result is used to determine whether the spliced ​​sequence is a sequence that supports fusion events; If so, calculate the fusion value of the spliced ​​sequences; The final fusion value of each gene pair is calculated based on the fusion value of the spliced ​​sequence; The final structural variant gene pair is determined based on the final fusion value.

2. The method according to claim 1, characterized in that, The method further includes: Based on a pre-defined database, a blacklist and a whitelist of structural variants are constructed; wherein the blacklist consists of homologous genes or pseudogenes; and the whitelist consists of one or more pre-configured structural variant genes.

3. The method according to claim 2, characterized in that, The determination of the final structural variant gene pair based on the final fusion value includes: Select the gene pair corresponding to the final fusion value that is greater than the preset fusion value, and record it as the initial structural variation gene pair; The initial structural variant gene pairs are screened and filtered using the blacklist and the whitelist to output the final structural variant gene pairs.

4. The method according to any one of claims 1-3, characterized in that, Perform fusion signal detection on the BAM file to output split read detection results and discordant paired read detection results, including: The BAM file is subjected to S-signal detection, and the breakpoints where fusion occurs are calculated based on the alignment information to output splitreads detection results; wherein, the splitreads detection results include information on each gene that has fused and information on the breakpoints where fusion occurs between each gene.

5. The method according to any one of claims 1-3, characterized in that, Perform fusion signal detection on the BAM file to output split read detection results and discordant paired read detection results, including: The inserted segment length is detected in the BAM file. When the inserted segment length is greater than a preset length value, the position is normalized. Clustering is performed on discordant reads whose comparison positions after distance normalization are within a preset range. The median value of the comparison position obtained after clustering is recorded as the breakpoint of fusion; The discrete paired reads detection results are output based on the breakpoints of the fusion; wherein, the discrete paired reads detection results include information on each gene that has fused and information on the breakpoints where the fusion occurs between the genes.

6. The method according to any one of claims 1-3, characterized in that, Perform fusion signal detection on the BAM file to output split read detection results and discordant paired read detection results, including: The inserted fragment length and chromosome corresponding to the paired-end reads were detected in the bam file; When the length of the inserted fragment is 0 and the paired-end reads correspond to different chromosomes, the alignment position is normalized. Clustering is performed on discordant reads whose comparison positions after distance normalization are within a preset range. The median value of the comparison position obtained after clustering is recorded as the breakpoint of fusion; The discrete paired reads detection results are output based on the breakpoints of the fusion; wherein, the discrete paired reads detection results include information on each gene that has fused and information on the breakpoints where the fusion occurs between the genes.

7. The method according to any one of claims 1-3, characterized in that, After obtaining the merged sequence, the process further includes: Calculate the gene fusion frequency, wherein the fusion frequency is calculated using the following formula: = in, Indicates the fusion frequency of gene 1 and gene 2; split reads represent the number of breakpoints where split reads occur in gene 1 and gene 2; discordant paired reads represent the number of breakpoints where discordant paired reads occur in gene 1 and gene 2. Indicates the depth of the breakpoint in the split reads where gene 1 undergoes fusion; Indicates the depth of the breakpoint in the split reads where gene 2 undergoes fusion; Indicates the depth of the breakpoint of gene 1 in discordant paired reads where the fusion occurred; This indicates the depth of the breakpoint in discordant paired reads where gene 2 undergoes fusion.

8. A gene mutation detection device, characterized in that, The device includes: The BAM file acquisition module is used to acquire BAM files; wherein the BAM file is a sequencing file obtained by high-throughput sequencing of sequencing samples and then aligned with a reference genome. The signal detection module is used to perform fusion signal detection on the BAM file to output the detection results of split reads and discordant paired reads. The first merging module is used to merge split reads and discordant paired reads that correspond to the same gene and have the same exons or introns at the breakpoint, based on the split reads detection results and the discordant paired reads detection results, to obtain a merged sequence. The mutation detection module is used to perform structural mutation detection on the BAM file using preset detection software, and to annotate the mutation detection results to obtain annotation results. The second merging module is used to merge the annotation results and the merging sequence to obtain the structural variation results; The Ref construction module is used to construct refs based on the structural variation results and the breakpoint positions of genes to obtain the spliced ​​sequence; The judgment module is used to perform a re-comparison on the spliced ​​sequence and determine whether the spliced ​​sequence is a sequence that supports fusion events based on the re-comparison result; The fusion value calculation module is used to calculate the fusion value of the spliced ​​sequence when the spliced ​​sequence is a sequence that supports fusion events; The final fusion value calculation module is used to calculate the final fusion value of each pair of genes based on the fusion value of the spliced ​​sequence; A variant gene pair determination module is used to determine the final structural variant gene pair based on the final fusion value.

9. A terminal device, characterized in that, include: Memory; One or more processors are coupled to the memory; One or more applications, wherein the one or more applications are stored in memory and configured to be executed by one or more processors, and the one or more applications are configured to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains program code that can be invoked by a processor to execute the method as described in any one of claims 1-7.

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