Chromosome detection method and device, computer equipment and storage medium

Abstract

The embodiment of the invention relates to a chromosome detection method and device, computer equipment and a storage medium. A processor of the computer equipment can execute the following steps: obtaining sequencing data corresponding to a target sample; comparing the sequencing data with reference genome data to obtain a comparison result; annotating the comparison result according to a genome annotation file to obtain chimeric information which comprises chromosome information corresponding to the multiple breakpoints respectively; based on the chromosome information corresponding to each breakpoint, screening the plurality of breakpoints to obtain at least one target breakpoint; the target breakpoint is a breakpoint generated by chromosome connection abnormality; and according to the chromosome information corresponding to the at least one target breakpoint, performing chromosome karyotype analysis on the target sample to obtain a karyotype result corresponding to the target sample. According to the chromosome detection method and device, the computer equipment and the storage medium, the sample sequencing accuracy and analysis efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of data analysis technology, and specifically to a chromosome detection method, apparatus, computer equipment, and storage medium. Background Art

[0002] With the development of high-throughput sequencing technology, bioinformatics analysis of the sequencing data generated by sequencing technologies can provide fundamental insights into genetic variation and genomic structure. Because chromosomes are prone to abnormal connections in many cases, and some abnormal connections can lead to serious diseases, bioinformatics is being used to comprehensively analyze gene expression, splicing variations, and chromosomal rearrangements from massive amounts of sequencing data. However, the use of bioinformatics algorithms on massive amounts of sequencing data from biological genes and chromosomes makes sequencing-based analyses prone to false positives and false negatives, limiting the accuracy and efficiency of the analysis. Summary of the Invention

[0003] The embodiments of the present application disclose a chromosome detection method, apparatus, computer device and storage medium, which can accurately identify target breakpoints in a sample, avoid false positive or false negative results, and thus improve the sequencing accuracy and analysis efficiency of the sample.

[0004] An embodiment of the present application discloses a computer device, including a processor and a memory, wherein the memory stores a computer program. When the computer program is executed by the processor, the processor performs the following steps:

[0005] Obtain sequencing data corresponding to the target sample;

[0006] Comparing the sequencing data with the reference genome data to obtain an alignment result;

[0007] Annotating the alignment result according to the genome annotation file to obtain chimeric information, wherein the chimeric information includes chromosome information corresponding to the multiple breakpoints;

[0008] Based on the chromosome information corresponding to each of the breakpoints, the multiple breakpoints are screened to obtain at least one target breakpoint; the target breakpoint is a breakpoint caused by chromosome connection abnormality;

[0009] According to the chromosome information corresponding to the at least one target breakpoint, a chromosome karyotype analysis is performed on the target sample to obtain a karyotype result corresponding to the target sample.

[0010] As an optional embodiment, the sequencing data includes multiple gene fragments, and each of the gene fragments includes base types and sequencing qualities corresponding to multiple bases; before comparing the sequencing data with the reference genome data to obtain the comparison results, the processor further performs the following steps: removing gene fragments in the sequencing data whose base types corresponding to multiple bases do not meet the base information conditions, and / or gene fragments whose sequencing qualities corresponding to multiple bases do not meet the gene quality conditions; the base information conditions include: the proportion of the number of first bases belonging to the target base type is greater than the first proportion threshold, and the proportion of the number of second bases whose base type cannot be determined is less than the second proportion threshold; the gene quality conditions include: the proportion of the number of bases whose sequencing quality is greater than the target quality threshold is greater than the third proportion threshold.

[0011] As an optional implementation, annotating the alignment result according to the genome annotation file to obtain chimeric information includes: when the alignment result meets the genome alignment condition, annotating the alignment result according to the genome annotation file to obtain chimeric information.

[0012] As an optional embodiment, the comparison results include base sequence comparison results, regional comparison results and ribosomal RNA statistical results; the genome comparison conditions include: the base sequence comparison result is that the comparison rate between the sequencing data and the reference genome data is greater than the comparison threshold; and, the regional comparison result is that the proportion of exon regions in the sequencing data is greater than the regional threshold; and, the rRNA statistical result is that the ratio of rRNA to total RNA in the sequencing data is less than the proportion threshold.

[0013] As an optional embodiment, the multiple breakpoints are screened based on the chromosome information corresponding to each of the breakpoints to obtain at least one target breakpoint, including: determining the first position of the first breakpoint on the first gene segment and the second position of the second breakpoint on the first gene segment based on the chromosome information corresponding to the first breakpoint and the second breakpoint respectively contained in the first gene segment; the first gene segment includes a spliced ​​first chromosome and a second chromosome, and the two ends of the second chromosome are spliced ​​into the first chromosome, and the first breakpoint and the second breakpoint are the breakpoints corresponding to the two ends of the second chromosome respectively; if the first position is within the effective segment interval and the second position is within the effective segment interval, then the first breakpoint and the second breakpoint are used as target breakpoints.

[0014] As an optional embodiment, the sequencing data includes multiple gene fragments; the multiple breakpoints are screened based on the chromosome information corresponding to each of the breakpoints to obtain at least one target breakpoint, including: determining the target chromosome identifier and target breakpoint sequence fragment corresponding to the third breakpoint based on the chromosome information corresponding to the third breakpoint, the target chromosome identifier is used to indicate the spliced ​​chromosome corresponding to the third breakpoint; the third breakpoint is any breakpoint among the multiple breakpoints; the target chromosome identifier and the target breakpoint sequence fragment are compared with each of the gene fragments to determine a first number of gene fragments including the third breakpoint; if the first number is greater than a number threshold, the third breakpoint is used as the target breakpoint.

[0015] As an optional embodiment, the screening of the multiple breakpoints based on the chromosome information corresponding to each of the breakpoints to obtain at least one target breakpoint includes: obtaining chromosome information corresponding to multiple preset breakpoints; the preset breakpoints are breakpoints generated by normal chromosome connection; if there is no preset breakpoint identical to the fourth breakpoint among the multiple preset breakpoints, then using the fourth breakpoint as the target breakpoint; the fourth breakpoint is any breakpoint among the multiple breakpoints.

[0016] The present application embodiment discloses a chromosome detection method, which is applied to a computer device, comprising:

[0017] Obtain sequencing data corresponding to the target sample;

[0018] Comparing the sequencing data with the reference genome data to obtain an alignment result;

[0019] Annotating the alignment result according to the genome annotation file to obtain chimeric information, wherein the chimeric information includes chromosome information corresponding to the multiple breakpoints;

[0020] Based on the chromosome information corresponding to each of the breakpoints, the multiple breakpoints are screened to obtain at least one target breakpoint; the target breakpoint is a breakpoint caused by chromosome connection abnormality;

[0021] According to the chromosome information corresponding to the at least one target breakpoint, a chromosome karyotype analysis is performed on the target sample to obtain a karyotype result corresponding to the target sample.

[0022] The present application discloses a chromosome detection device, which is applied to a computer device and includes:

[0023] An acquisition module is used to obtain sequencing data corresponding to the target sample;

[0024] An alignment module, configured to align the sequencing data with the reference genome data to obtain an alignment result;

[0025] an annotation module, configured to annotate the alignment result according to a genome annotation file to obtain chimeric information, wherein the chimeric information includes chromosome information corresponding to the plurality of breakpoints;

[0026] a screening module, configured to screen the multiple breakpoints based on chromosome information corresponding to each of the breakpoints to obtain at least one target breakpoint; the target breakpoint is a breakpoint caused by abnormal chromosome connection;

[0027] An analysis module is used to perform chromosome karyotype analysis on the target sample according to the chromosome information corresponding to the at least one target breakpoint, so as to obtain a karyotype result corresponding to the target sample.

[0028] An embodiment of the present application discloses a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the method described in any of the above embodiments is implemented.

[0029] The present application discloses a computer program product, including a computer program, and when the computer program is executed by a processor, the method described in any of the above embodiments is implemented.

[0030] The chromosome detection method, apparatus, computer device, and storage medium disclosed in the embodiments of the present application include: a computer device acquiring sequencing data corresponding to a target sample; comparing the sequencing data with reference genome data to obtain a comparison result; annotating the comparison result according to a genome annotation file to obtain chimeric information, wherein the chimeric information includes chromosome information corresponding to multiple breakpoints; screening multiple breakpoints based on the chromosome information corresponding to each breakpoint to obtain at least one target breakpoint; the target breakpoint is a breakpoint caused by a chromosome connection abnormality; and performing a chromosome karyotype analysis on the target sample based on the chromosome information corresponding to the at least one target breakpoint to obtain a karyotype result corresponding to the target sample. In an embodiment of the present application, the computer device can accurately locate sequence fragments in the sequencing data that differ from the reference genome by comparing the sequencing data with the reference genome data, and obtain chimeric information containing breakpoint chromosome information based on the comparison results annotation of the genome annotation file, so that the originally complex and difficult to intuitively understand sequencing data is converted into a description of the breakpoint position and chromosome chimera with clear biological significance, which can effectively eliminate the interference of non-target breakpoints, thereby avoiding false positive results, and ensure that the real target breakpoints are not missed, avoiding false negative results, thereby reducing errors caused by misjudgment or omission in the processing of sequencing data, and improving the sequencing accuracy of the sample. Accurate and efficient target breakpoint identification and analysis also directly improve the overall analysis efficiency, thereby obtaining accurate sample karyotype results, which is conducive to further bioinformatics analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0032] Figure 1 is a structural block diagram of a computer device in one embodiment;

[0033] Figure 2 is a flow chart of a chromosome detection method in one embodiment;

[0034] Figure 3 is a flow chart of a chromosome detection method in another embodiment;

[0035] Figure 4 A flowchart of annotating and obtaining chimeric information in one embodiment;

[0036] Figure 5 A flowchart of screening and obtaining target breakpoints in one embodiment;

[0037] Figure 6 A flowchart of screening and obtaining a target breakpoint in another embodiment;

[0038] Figure 7 A flowchart of screening and obtaining a target breakpoint in another embodiment;

[0039] Figure 8 FIG. 4 is a block diagram of a chromosome detection device in one embodiment. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0041] It should be noted that the terms "including," "having," and any variations thereof in the embodiments and drawings of this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to the process, method, product, or apparatus.

[0042] It is understood that the terms "first," "second," and the like used herein may be used herein to describe various elements, but these elements are not limited by these terms. These terms are used solely to distinguish a first element from another element. For example, a first chromosome may be referred to as a second chromosome, and similarly, a second chromosome may be referred to as a first chromosome, without departing from the scope of this application. Both the first chromosome and the second chromosome are chromosomes contained in the human body, but they are not identical chromosomes.

[0043] The embodiments of the present application disclose a chromosome detection method, apparatus, computer device and storage medium, which can accurately identify target breakpoints in a sample, avoid false positive or false negative results, and thus improve the sequencing accuracy and analysis efficiency of the sample.

[0044] The chromosome detection method provided in this application can be applied to Figure 1 In the computer device 100 shown. Figure 1 FIG1 is a block diagram of a computer device in one embodiment. The computer device 100 may include but is not limited to a mobile phone, a tablet computer, a PC (Personal Computer), a computer, etc. Figure 1 As shown, the computer device 100 may include one or more of the following components: a processor 110, a memory 120 coupled to the processor 110, wherein the memory 120 may store one or more computer programs, and the one or more computer programs may be configured to implement the steps described in the following embodiments when executed by one or more processors 110.

[0045] In some embodiments, a hospital's sample collection personnel collects a sample to be tested from a target user and transports it to a testing facility. The testing facility is responsible for receiving the sample and sequencing it using genetic sequencing technology to obtain sequencing data corresponding to the target user. The testing facility sequences the sample to obtain sequencing data corresponding to the target user, which contains a large amount of DNA or RNA sequence information. The testing facility then sends the sequencing data to the computer device 100 via other electronic devices via email. The computer device 100 then analyzes the sequencing data of the target sample to determine the chromosome karyotype of the target sample.

[0046] In some embodiments, the sequencing technology used by the testing agency to sequence the samples to be tested may include but is not limited to first-generation sequencing (based on Sanger sequencing), second-generation sequencing (high-throughput sequencing, including Illumina's HiSeq, MiSeq series, Thermo Fisher's Ion Torrent series, etc.), third-generation sequencing (long-read sequencing, such as Pacific Biosciences' SMRT technology and Oxford Nanopore's MinION), single-molecule sequencing, etc.

[0047] In the computer device 100, the processor 110 may include one or more processing cores. The processor 110 utilizes various interfaces and circuits to connect various components within the computer device 100. It executes instructions, programs, code sets, or instruction sets stored in the memory 120, as well as accesses data stored in the memory 120, to perform various functions of the computer device 100 and process data. Optionally, the processor 110 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 110 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing display content; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 110 and may be implemented separately via a communication chip.

[0048] In the computer device 100, the memory 120 may include a random access memory (RAM) or a read-only memory (ROM). The memory 120 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. The data storage area may also store data created by the computer device 100 during use.

[0049] It is understandable that the computer device 100 may include more or fewer structural elements than those in the above structural block diagram, for example, including a power supply, input buttons, a camera, a speaker, a screen, an RF (Radio Frequency) circuit, a Wi-Fi (Wireless Fidelity) module, a Bluetooth module, a sensor, etc., and is not limited here.

[0050] like Figure 2 As shown, in one embodiment, a chromosome detection method is provided, which can be applied to the above-mentioned computer device. The processor of the computer device can execute the following steps 210 to 250.

[0051] Step 210: Obtain sequencing data corresponding to the target sample.

[0052] The sequencing data includes multiple gene fragments, and each gene fragment includes base types and sequencing qualities corresponding to multiple bases.

[0053] A gene fragment refers to a continuous sequence of genomic DNA obtained through sequencing technology during the genome sequencing process. A gene fragment is a part of the genome, composed of multiple bases, and represents the information of a specific region in the genome.

[0054] Bases are one of the fundamental units of nucleic acids (DNA and RNA). In DNA, bases are linked together through phosphodiester bonds to form nucleic acid chains. Together with deoxyribose and phosphate, they form the basic structure of DNA. There are four common base types in DNA: adenine (A), thymine (T), guanine (G), and cytosine (C).

[0055] During the sequencing process, the base type corresponding to the base whose base type cannot be determined is set to N.

[0056] Sequencing quality refers to an evaluation index of the accuracy of sequencing each base during the sequencing process, which reflects the reliability of the sequencing equipment in judging the type of the base. The higher the sequencing quality, the more accurate the sequencing equipment is in judging the type of the base; the lower the sequencing quality, the lower the reliability of the judgment. Optionally, sequencing quality is generally expressed as a Phred quality score (ASCII code, Q value), and the relationship between the Q value and the probability of sequencing error (P) is: Q = -10×log 10 P.

[0057] In some embodiments, the sequencing device outputs a fastq-formatted file for the target sample during ranging analysis. The computer receives the fastq-formatted file, which contains sequencing data, from another electronic device. Each gene fragment in the fastq-formatted file typically contains four types of information: the name of the gene fragment, the base type corresponding to each base, a "+" separator, and the sequencing quality corresponding to each base.

[0058] For example, the read length of the first gene fragment is 150bp (base pair), that is, the first gene fragment contains 300 bases (one base pair contains 2 corresponding bases). In the fastq format file, the base type corresponding to the first base in the first gene fragment is A, and the corresponding sequencing quality is F. According to the encoding rules (Phred+33, then converted to ASCII encoding), the symbol F (ASCII 70) corresponds to Q=37 (error rate P=0.02%).

[0059] Step 220 , aligning the sequencing data with the reference genome data to obtain an alignment result.

[0060] Reference genome data refers to the complete sequence information of a species' genome, which has been sequenced, assembled, and annotated. Reference genome data contains the precise location and sequence content of all genes, regulatory elements, and other genetic information in the species' genome. For example, the human reference genome data (such as the GRCh38 version) details the order of approximately 3 billion base pairs in the human genome, as well as the location, structure, and functional annotations of each gene.

[0061] Alternatively, the computer device can obtain reference genome data through public databases or research institutions.

[0062] The alignment results contain a collection of information about how the sequencing data matches the reference genome. Specifically, the alignment results may include base sequence alignment results, region alignment results, and ribosomal RNA statistics.

[0063] The base sequence alignment results include the matching of each base in the gene fragment in the sequencing data with the base at the corresponding position in the reference genome.

[0064] Regional alignment results focus on the alignment of sequenced fragments to different functional regions or specific regions of the reference genome. Regional alignment results can include statistics on the alignment of sequenced fragments to gene regions, such as the number and proportion of fragments aligned to gene coding regions (exons), non-coding regions (introns), and upstream and downstream regulatory regions of the gene. For example, in the sequencing data of a certain sample, 60% of the fragments aligned to exons, 30% aligned to introns, and 10% aligned to upstream and downstream regulatory regions of the gene.

[0065] Ribosomal RNA statistics can include the ratio of the number of fragments in the sequencing data that mapped to rRNA sequences to the total number of sequences. For example, in a certain sequencing data set, 25% of the fragments mapped to rRNA sequences.

[0066] Since sequencing data is usually composed of a large number of shorter gene fragments, these gene fragments come from the genome of the target sample. By comparing the sequencing data with the reference genome data, these gene fragments can be accurately located to the corresponding positions on the reference genome, thereby understanding the genetic information judged by each gene in the target sample; it is also possible to discover abnormalities such as single nucleotide polymorphisms (SNPs), insertions and deletions (InDels), structural variations (such as chromosome variations, inversions, translocations, splicing, etc.) in the target sample by obtaining the differences between the sequencing data and the reference genome data.

[0067] Step 230: annotate the comparison result according to the genome annotation file to obtain chimera information.

[0068] A genome annotation file refers to a text file that describes the functional elements of a genome. The genome annotation file records the location and functional information of features such as genes, exons, introns, non-coding RNAs, and repetitive sequences.

[0069] In some embodiments, the computer device may annotate the results of the genome annotation file comparison to obtain an annotation result, and then integrate the content contained in the annotation result to obtain mosaic information. The mosaic information refers to the abnormal chromosome connection event formed by abnormal splicing of sequence fragments from different chromosomes or different regions of the same chromosome after annotation.

[0070] Optionally, the chimeric information includes chromosome information corresponding to multiple breakpoints, wherein a breakpoint refers to a location in the genome sequence where an abnormal splicing occurs, i.e., where two different fragments are connected.

[0071] The chromosome information of the breakpoint may include the chromosome identifiers of the two gene sequences forming the breakpoint (the first chromosome and the second chromosome), the specific positions of the breakpoints on the chromosomes (usually expressed as base coordinates, for example, the base position on one side of the breakpoint may be located at the 1,000,000 base position of human chromosome 1, and the base position on the other side may be located at the 5,000,000 base position of chromosome 2), the identifier of the gene fragment of the breakpoint in the sequencing data, the name of the gene to which the breakpoint belongs, the position of the breakpoint in the gene fragment in the sequencing data, etc.

[0072] Optionally, the first chromosome and the second chromosome may be the same chromosome or different chromosomes.

[0073] Breakpoints can occur due to chromosomal structural variations (e.g., chromosomal translocations, inversions, insertions, etc.), abnormal splicing during transcription, or viral integration. Therefore, obtaining chromosome information corresponding to multiple breakpoints can accurately locate the specific location of abnormal connections in the genome, thereby determining whether the breakpoint is caused by abnormal chromosome connections.

[0074] Step 240 : Screen multiple breakpoints based on the chromosome information corresponding to each breakpoint to obtain at least one target breakpoint.

[0075] The target breakpoint is a breakpoint caused by a chromosomal junction abnormality. A chromosomal junction abnormality refers to a situation in which the chromosome structure does not conform to the normal connection pattern. Under normal circumstances, chromosomes have a specific structure and sequence arrangement, and different regions are connected together according to certain rules. However, a chromosomal junction abnormality disrupts this normal connection pattern, resulting in abnormal splicing between chromosome segments.

[0076] For example, the Philadelphia chromosome, which is common in chronic myeloid leukemia, is a reciprocal translocation between the 34th region of the long arm of human chromosome 9 (9q34) and the 11th region of the long arm of chromosome 22 (22q11), forming an abnormal chromosome structure of t(9;22)(q34;q11).

[0077] In some embodiments, since only 46 human chromosomes are studied in biological research, the computer device can screen each breakpoint according to the chromosome identifier of the two gene sequences forming the breakpoint, and only retain the breakpoints whose chromosome identifiers are normal chromosomes and sex chromosomes, to avoid false positive results due to non-standard chromosomes (such as unassembled fragments "chrUn_*") or contaminated data (such as bacterial DNA).

[0078] During genome sequencing and analysis, a large number of breakpoints may be detected. However, many of these breakpoints may be caused by non-critical factors such as sequencing errors and random breaks. Some breakpoints may even be normal human genetic variation. Through screening, these interfering factors can be eliminated, focusing on the target breakpoints that are truly caused by abnormal chromosome connection.

[0079] Step 250 : performing chromosome karyotype analysis on the target sample based on the chromosome information corresponding to the at least one target breakpoint, and obtaining a karyotype result corresponding to the target sample.

[0080] Chromosome karyotype analysis refers to the process of pairing, numbering, grouping, and performing morphological analysis on the chromosomes of the cells to be tested according to the inherent chromosome morphological and structural characteristics of the organism. The karyotype result is a summary and description of the chromosome karyotype analysis. The karyotype results may include the number, morphology, and structural characteristics of chromosomes. For example, a normal karyotype can be described as 46, XX (female) or 46, XY (male), where "46" indicates the number of chromosomes and "XX" or "XY" indicates the sex chromosome composition. For example, 47, XX, +21 indicates that the target sample is female and has one more chromosome 21 than normal.

[0081] Chromosome karyotype analysis helps to gain a deeper understanding of the structural composition of chromosomes, gene location, and the relationship between chromosome structural variation, gene expression, and disease development. For example, it can study how chromosome translocations lead to gene fusions and abnormal protein expression.

[0082] In an embodiment of the present application, the computer device can accurately locate sequence fragments in the sequencing data that differ from the reference genome by comparing the sequencing data with the reference genome data, and obtain chimeric information containing breakpoint chromosome information based on the comparison results annotation of the genome annotation file, so that the originally complex and difficult to intuitively understand sequencing data is converted into a description of the breakpoint position and chromosome chimera with clear biological significance, which can effectively eliminate the interference of non-target breakpoints, thereby avoiding false positive results, and ensure that the real target breakpoints are not missed, avoiding false negative results, thereby reducing errors caused by misjudgment or omission in the processing of sequencing data, and improving the sequencing accuracy of the sample. Accurate and efficient target breakpoint identification and analysis also directly improve the overall analysis efficiency, thereby obtaining accurate sample karyotype results, which is conducive to further bioinformatics analysis.

[0083] like Figure 3 As shown, in one embodiment, a chromosome detection method is provided, which can be applied to the above-mentioned computer device. The processor of the computer device can execute the following steps 302 to 312.

[0084] Step 302: Obtain sequencing data corresponding to the target sample.

[0085] For the description of step 302 , reference may be made to the description of step 210 in the above embodiment, which will not be repeated here.

[0086] Step 304 : removing gene segments in the sequencing data whose base types corresponding to the multiple bases do not meet the base information conditions, and / or whose sequencing qualities corresponding to the multiple bases do not meet the gene quality conditions.

[0087] The base information conditions include: the proportion of the number of first bases belonging to the target base type is greater than a first ratio threshold, and the proportion of the number of second bases whose base type cannot be determined is less than a second ratio threshold.

[0088] If the percentage of the first bases of the target base type in a gene fragment does not meet the set base information conditions, it indicates that the gene fragment may contain a large number of sequencing errors or abnormal bases. For example, if the target base types are G and C, under normal circumstances, the content of G and C in a gene fragment should be within a reasonable range. If the corresponding first base ratio is not within a reasonable range, it may mean that the sequencing results of the gene fragment are unreliable. Removing such gene fragments can prevent erroneous data from interfering with subsequent analysis (such as gene expression analysis, variant detection, etc.), ensuring the accuracy of the final analysis results.

[0089] Optionally, the target base type may be at least one of ATCGN.

[0090] Specifically, assuming that the target base types are G and C, the computer device will traverse each gene fragment and count the number of first bases whose base type is G or C, and the number of second bases whose base type is N. Then, the proportion of the number of first bases to the total number of bases in the gene fragment (the first base number ratio) and the proportion of the number of second bases to the total number of bases in the gene fragment (the second base number ratio) are calculated respectively. The computer device can determine the gene fragments whose first base number ratio is between 40% and 60%, or whose second base number ratio is greater than the second ratio threshold of 5%, and delete these gene fragments from the sequencing data.

[0091] For example, consider a gene fragment with a total of 100 bases, of which 30 are G, 25 are C, and 8 are N. The first base count is 30 + 25 = 55, and the first base count accounts for 55 / 100 = 55%, which is between 40% and 60%. The second base count is 8, and the second base count accounts for 8 / 100 = 8%, which is greater than 5%. Based on the set conditions, this indicates that the base types corresponding to multiple bases contained in this gene fragment do not meet the base information requirements and will be deleted from the sequencing data by the computer.

[0092] The gene quality conditions include: the proportion of bases with sequencing quality greater than the target quality threshold is greater than the third ratio threshold.

[0093] Low-quality bases may be caused by factors such as sequencing instrument errors, sample quality issues (such as DNA degradation and low concentration), or interference from the sequencing environment (such as unstable temperature and humidity). If the proportion of bases in a gene fragment with sequencing quality less than or equal to the target quality threshold is too high, it indicates that the fragment contains a large amount of unreliable base information. Removing these gene fragments that do not meet the gene quality requirements can ensure the high reliability of the data used in subsequent analysis and reduce erroneous conclusions due to data quality issues.

[0094] Specifically, assuming that the target quality threshold is 10, the computer device can count the number of bases with a base quality Q value less than or equal to 10 for each gene fragment, and then calculate the proportion of these low-quality bases to the total number of bases in the gene fragment; the computer device can determine the gene fragments whose proportion is less than 20% of the third proportion threshold, and delete these gene fragments from the sequencing data.

[0095] Optionally, the gene quality condition may further include: the proportion of the number of bases with sequencing quality greater than or equal to the target quality threshold is greater than a fourth ratio threshold.

[0096] Exemplarily, the computer device may detect each gene fragment, and if it is detected that the number of bases with a base quality Q value greater than or equal to 20 in a certain gene fragment accounts for a ratio Q20 ≥ 90% of each gene fragment, and / or the number of bases with a base quality Q value greater than or equal to 30 accounts for a ratio Q30 ≥ 80% of each gene fragment, the gene fragment is retained.

[0097] In some embodiments, due to the adapter sequences introduced during the sequencing process, these adapter sequences are not from the gene fragments of the target sample itself and will be included in the fastq format file, which will interfere with subsequent gene analysis. Therefore, after obtaining the sequencing data corresponding to the target sample, the computer device can also compare the base sequence of each gene fragment with the sequence in the adapter sequence library; if a sequence matching the adapter sequence library is found in the base sequence of the gene fragment, it is determined that the gene fragment contains an adapter, and the computer device removes the gene fragment containing the adapter from the sequencing data. For example, gene fragments with adapters such as polyA (consecutive A bases) and polyG (consecutive G bases) are removed.

[0098] Step 306: align the sequencing data with the reference genome data to obtain an alignment result.

[0099] Step 308: Annotate the comparison results according to the genome annotation file to obtain chimera information.

[0100] Step 310 : Screen multiple breakpoints based on the chromosome information corresponding to each breakpoint to obtain at least one target breakpoint.

[0101] Step 312: Perform chromosome karyotype analysis on the target sample based on the chromosome information corresponding to the at least one target breakpoint to obtain a karyotype result corresponding to the target sample.

[0102] For the description of steps 306 to 312 , reference may be made to the description of steps 220 to 250 in the above embodiment, which will not be repeated here.

[0103] In the embodiment of the present application, the computer equipment effectively eliminates erroneous data, low-quality data and impurity information introduced during the sequencing process due to instrument errors, sample problems, environmental interference, etc. by removing base types that do not meet the base information conditions, sequencing quality that does not meet the gene quality conditions, and gene fragments containing connectors. This greatly improves the quality and reliability of the sequencing data, avoids interference of these bad data in subsequent analysis, provides a high-quality data foundation for subsequent gene alignment, annotation and other steps, and ensures the accuracy of the final analysis results.

[0104] In one embodiment, Figure 4 As shown, the processor of the computer device may execute the following steps 402 to 406 to annotate the comparison result according to the genome annotation file to obtain chimera information.

[0105] Step 402 , determine whether the comparison result meets the genome comparison conditions; if so, execute step 404 ; if not, execute step 406 .

[0106] The genome alignment conditions may include: the base sequence alignment result is that the alignment rate between the sequencing data and the reference genome data is greater than the alignment threshold; and the regional alignment result is that the proportion of exon regions in the sequencing data is greater than the regional threshold; and the rRNA statistical result is that the ratio of rRNA to total RNA in the sequencing data is less than the proportion threshold.

[0107] A high alignment rate indicates that most gene fragments in the sequencing data can be correctly matched with the reference genome, indicating that the sequencing process is relatively accurate and the data quality is high. By removing gene sequences with a alignment ratio less than or equal to the alignment threshold, computing resources and time are avoided from being wasted on low-quality sequencing data.

[0108] If the proportion of exon regions in the sequencing data is too low, it may mean that the sequencing data is mainly concentrated in introns or non-coding regions. Although these regions have research value, they are usually not the focus. By screening sequencing data with a high proportion of exon regions, the analysis burden of non-critical regions can be reduced, computing efficiency can be improved, and the analysis focus can be ensured to be focused on regions with biological functions (exon regions).

[0109] A high ratio of rRNA to total RNA may indicate rRNA contamination during sample extraction, storage, or sequencing. For example, if laboratory equipment or reagents are contaminated with rRNA from the environment during RNA extraction, or if an inappropriate RNA extraction method is used, this can result in excessive rRNA content in the sequencing data, affecting the analysis of other RNAs (such as mRNA and lncRNA). Therefore, it is necessary to ensure that the ratio of rRNA to total RNA in the sequencing data is less than a threshold ratio.

[0110] Illustratively, the computer device may determine, based on the comparison results, whether the comparison rate between the sequencing data and the reference genome data is greater than 80%, the proportion of exon regions in the sequencing data is greater than 40%, and the ratio of rRNA to total RNA in the sequencing data is less than 10%; if all of the above are true, execute step 404; if any of the above is not satisfied, execute step 406.

[0111] Step 404: annotate the comparison result according to the genome annotation file to obtain chimera information.

[0112] In some embodiments, when the alignment result satisfies the genome alignment conditions, the computer device annotates the alignment result according to the genome annotation file to obtain chimera information.

[0113] The alignment result meets the genome alignment conditions, indicating that the alignment rate between the sequencing data and the reference genome data is greater than the alignment threshold, the proportion of exon regions in the sequencing data is greater than the region threshold, and the ratio of rRNA to total RNA in the sequencing data is less than the proportion threshold, which means that the sequencing data corresponding to the target sample is high-quality, low-contamination, and focused on biological functional areas. The computer device can then annotate the alignment results based on the genome annotation file to obtain chimeric information.

[0114] Step 406: Output an alignment error prompt, indicating that the alignment result of the sequencing data does not meet the genome alignment conditions.

[0115] In some embodiments, when the alignment result does not meet the genome alignment condition, the computer may determine a target condition that the alignment result does not meet from multiple conditions included in the genome alignment condition; and generate a corresponding alignment error prompt based on the target condition to remind the user that the target sample has a problem with the sequencing data due to a failure in the sequencing process.

[0116] In the embodiment of the present application, the computer equipment can effectively screen out high-quality, low-contamination sequencing data focused on biological functional areas by setting genome comparison conditions, avoiding wasting computing resources and time on low-quality data, providing a strong basis for subsequent experimental adjustments and data processing, and overall ensuring the accuracy and reliability of chromosome detection and analysis results.

[0117] In one embodiment, Figure 5 As shown, the processor of the computer device may execute the following steps 502 to 508 to screen multiple breakpoints based on the chromosome information corresponding to each breakpoint to obtain at least one target breakpoint.

[0118] Step 502 : Determine a first position of the first breakpoint on the first gene segment and a second position of the second breakpoint on the first gene segment based on chromosome information corresponding to the first breakpoint and the second breakpoint included in the first gene segment.

[0119] In some embodiments, the abnormal chromosome connection involves a chromosomal translocation, resulting in a gene segment on one chromosome appearing within another chromosome. The first gene segment comprises a spliced ​​first chromosome and a second chromosome, with both ends of the second chromosome spliced ​​into the first chromosome, and the first breakpoint and the second breakpoint are the corresponding breakpoints at both ends of the second chromosome, respectively.

[0120] For example, assuming the first chromosome is chr1 and the second chromosome is chr2, and a segment of the second chromosome is inserted into the first chromosome and replaces the first chromosome, the inserted segment ranges from chr2: 5000-6000, the replaced segment ranges from chr1: 1000-2000, and the first gene segment in the sequencing data ranges from chr1: 500-2500. Then, the first breakpoint on the first gene segment is chr1: 1000, and the second breakpoint on the first gene segment is chr1: 2000.

[0121] Alternatively, the first chromosome and the second chromosome may be the same chromosome. In the case where the first chromosome and the second chromosome are the same chromosome,

[0122] Optionally, the first breakpoint can also be referred to as a donor breakpoint and an acceptor breakpoint at the same time. The donor breakpoint and the acceptor breakpoint refer to the same breakpoint. The breakpoint on the first chromosome can be referred to as a donor breakpoint, and the same breakpoint on the second chromosome can be referred to as an acceptor breakpoint.

[0123] It is important to note that the concepts of donor breakpoints and acceptor breakpoints are relative. For example, when splicing 9q34 and 22q11, the breakpoint in band 34 of the long arm of chromosome 9 can be used as the donor breakpoint, and the corresponding breakpoint in band 11 of the long arm of chromosome 22 can be used as the acceptor breakpoint; alternatively, the breakpoint in band 11 of the long arm of chromosome 22 can be used as the donor breakpoint, and the corresponding breakpoint in band 34 of the long arm of chromosome 9 can be used as the acceptor breakpoint.

[0124] Step 504 , determining whether the first position is within a valid segment interval and whether the second position is within a valid segment interval; if so, executing step 506 ; if not, executing step 508 .

[0125] Alternatively, there may be low-quality regions at either end of the gene fragment in the sequencing data (e.g., errors caused by sequencer signal attenuation or residual adapters during the sequencing process). If any breakpoint is located in this low-quality region, it is likely that the target breakpoint will be judged as a false positive due to low base quality or alignment bias.

[0126] In some embodiments, the effective segment region may be the position of 20% to 80% of the first gene segment. If either the first breakpoint or the second breakpoint is not in the effective segment region, then both the first breakpoint and the second breakpoint are considered invalid.

[0127] Step 506: Set the first breakpoint and the second breakpoint as target breakpoints.

[0128] In some embodiments, the first breakpoint at a first position on the first gene segment is located within the effective segment interval, and the second breakpoint at a second position on the first gene segment is located within the effective segment interval, indicating that the first breakpoint and the second breakpoint are generated by chromosome connection rather than an abnormality during the sequencing process. In this case, the computer device may use the first breakpoint and the second breakpoint as target breakpoints.

[0129] For example, assuming that the inserted fragment range is chr2:5000-6000, the replaced fragment is chr1:1000-2000, and the first gene fragment in the sequencing data is chr1:500-2500, then the effective fragment area of ​​the first gene fragment is 9000:2100, then the first position of chr1:1000 and the second position of chr1:2000 are both located within the effective fragment interval, then the computer device uses the first breakpoint and the second breakpoint as target breakpoints.

[0130] Step 508: Delete the first breakpoint and the second breakpoint.

[0131] In some embodiments, if the first position of the first breakpoint on the first gene segment is not within the effective segment interval, and / or the second position of the second breakpoint on the first gene segment is not within the effective segment interval, it indicates that the first breakpoint and / or the second breakpoint may be caused by sequencing errors, experimental problems or other noise factors, and the computer device may delete the first breakpoint and the second breakpoint.

[0132] In the present application, the computer device can accurately identify target breakpoints that meet the characteristics of chromosome structural variation by screening multiple breakpoints based on chromosome information and valid fragment intervals. False positive breakpoints caused by sequencing errors, experimental problems, or other noise factors are eliminated, improving the accuracy and reliability of breakpoint detection. At the same time, by setting the valid fragment interval, breakpoint judgment is avoided in low-quality regions at both ends of the sequencing data, further reducing the occurrence of false positive results.

[0133] In one embodiment, Figure 6 As shown, the processor of the computer device may execute the following steps 602 to 610 to screen multiple breakpoints based on the chromosome information corresponding to each breakpoint to obtain at least one target breakpoint.

[0134] Step 602: Determine the target chromosome identifier and target breakpoint sequence fragment corresponding to the third breakpoint based on the chromosome information corresponding to the third breakpoint.

[0135] The target chromosome identifier is used to indicate the spliced ​​chromosome corresponding to the third breakpoint. The third breakpoint is any breakpoint among multiple breakpoints. For example, if chr2 and chr5 are spliced ​​together to form the third breakpoint, the target chromosome identifier corresponding to the third breakpoint includes chr2 and chr5.

[0136] The target breakpoint sequence fragment refers to the bases near the breakpoint position on the spliced ​​chromosome corresponding to the third breakpoint. For example, if "ATCTATATAA" in chr2 is spliced ​​with "TCGGCCGAT" in chr5, the target breakpoint sequence fragment for the third breakpoint will include "ATCTATATAA" in chr2 and "TCGGCCGAT" in chr5.

[0137] Optionally, the number of bases contained in the target breakpoint sequence fragment is not limited and can be 10 or 30.

[0138] Step 604 : Compare the target chromosome identifier and the target breakpoint sequence fragment with each gene fragment to determine a first number of gene fragments including the third breakpoint.

[0139] The target chromosome identifier and the target breakpoint sequence fragment are compared with each gene fragment, so that the target gene fragment containing the third breakpoint can be found among the multiple gene fragments included in the sequencing data, and the number of the target gene fragments is counted to obtain a first number.

[0140] Step 606 , determining whether the first quantity is greater than a quantity threshold; if so, executing step 608 ; if not, executing step 610 .

[0141] The first number corresponding to the third breakpoint can be used to assess whether the third breakpoint actually exists and has biological significance. A larger first number indicates a higher concentration of the third breakpoint in the sequencing data, a lower probability that the third breakpoint occurred by chance, and a higher probability that the third breakpoint is the target breakpoint.

[0142] Step 608: Set the third breakpoint as the target breakpoint.

[0143] When the first number of gene fragments including the third breakpoint is greater than the quantity threshold, it indicates that there are more gene fragments supporting the third breakpoint in the sequencing data, and the third breakpoint is not a false positive result caused by sequencing errors, experimental problems or other random noise factors, but may truly reflect the situation of chromosome structural variation. In this case, the computer device can use the third breakpoint as the target breakpoint.

[0144] Step 610: Delete the third breakpoint.

[0145] The first number of gene fragments containing the third breakpoint is less than the data threshold, indicating that there are fewer gene fragments supporting the third breakpoint in the sequencing data, and the third breakpoint may be a false positive result generated accidentally, so the computer device deeply detects the third breakpoint.

[0146] In the embodiment of the present application, the computer device determines the target chromosome identifier and target breakpoint sequence fragment of the third breakpoint and compares them with each gene fragment. The computer device can count the number of gene fragments containing the third breakpoint, and then evaluate the authenticity of the third breakpoint. It can eliminate false positive breakpoints caused by sequencing errors, experimental problems or other random noise factors, improve the accuracy and reliability of breakpoint detection, and thus identify target breakpoints that really exist and have biological significance.

[0147] In one embodiment, Figure 7 As shown, the processor of the computer device may execute the following steps 702 to 708 to screen multiple breakpoints based on the chromosome information corresponding to each breakpoint to obtain at least one target breakpoint.

[0148] Step 702: Obtain chromosome information corresponding to multiple preset breakpoints.

[0149] The preset breakpoints are the breakpoints that occur normally when chromosomes are joined.

[0150] In some embodiments, a computer device may obtain normal sequencing data corresponding to multiple normal samples, compare the normal sequencing data corresponding to each normal sample with the reference genome data to obtain a normal comparison result; annotate the normal comparison result based on the genome annotation file to obtain normal mosaic information, which includes chromosome information corresponding to each of the multiple breakpoints; based on the chromosome information corresponding to each breakpoint, the computer device screens the multiple breakpoints to obtain at least one normal breakpoint; and construct a normal breakpoint database based on the at least one normal breakpoint corresponding to the multiple normal samples. The normal breakpoint database contains breakpoints that normally occur in humans and their corresponding chromosome information.

[0151] Optionally, compared to the existing database (which only contains breakpoints that are commonly found in the vast majority of people under normal circumstances), the normal breakpoint database constructed by a computer device using normal sequencing data corresponding to multiple normal samples can include not only breakpoints that are commonly found in the vast majority of people under normal circumstances, but also special breakpoints that only some humans have under normal circumstances; that is, obtaining chromosome information corresponding to multiple preset breakpoints in the constructed normal breakpoint database can more comprehensively reflect the normal variation of the human genome.

[0152] Step 704 , determining whether there is a preset breakpoint identical to the fourth breakpoint among the plurality of preset breakpoints; if not, proceed to step 706 ; if so, proceed to step 708 .

[0153] The fourth breakpoint is any breakpoint among the multiple breakpoints.

[0154] Step 706: Set the fourth breakpoint as the target breakpoint.

[0155] If there is no preset breakpoint identical to the fourth breakpoint among the multiple preset breakpoints, it means that the fourth breakpoint has not been recorded in the normal breakpoint database and is very likely a breakpoint caused by abnormal chromosome connection. In this case, the computer device can use the fourth breakpoint as a target breakpoint.

[0156] Step 708: Delete the fourth breakpoint.

[0157] If there is a preset breakpoint identical to the fourth breakpoint among the multiple preset breakpoints, it means that the fourth breakpoint is a breakpoint that also exists in the normal population, and the computer device can delete the fourth breakpoint.

[0158] In an embodiment of the present application, a computer device constructs a normal breakpoint database containing breakpoints that normally occur in humans, and screens multiple breakpoints based on the database. This allows the computer device to accurately distinguish normal breakpoints from breakpoints that may be caused by abnormal chromosomal connections, and to exclude breakpoints that exist in normal humans, making the screened target breakpoints more likely to be breakpoints caused by abnormal chromosomal connections. Moreover, compared with existing databases, the normal breakpoint database constructed by the computer device is more comprehensive and can better reflect the normal variation of the human genome.

[0159] like Figure 8 As shown, in one embodiment, a chromosome detection device 800 is provided, which can be applied to the above-mentioned computer device. The chromosome detection device 800 can include an acquisition module 810, an alignment module 820, an annotation module 830, a screening module 840 and an analysis module 850.

[0160] The acquisition module 810 is used to obtain sequencing data corresponding to the target sample.

[0161] The comparison module 820 is used to compare the sequencing data with the reference genome data to obtain a comparison result.

[0162] The annotation module 830 is used to annotate the comparison results according to the genome annotation file to obtain mosaic information, which includes chromosome information corresponding to multiple breakpoints.

[0163] The screening module 840 is configured to screen multiple breakpoints based on the chromosome information corresponding to each breakpoint to obtain at least one target breakpoint; the target breakpoint is a breakpoint caused by abnormal chromosome connection.

[0164] The analysis module 850 is configured to perform chromosome karyotype analysis on the target sample based on the chromosome information corresponding to at least one target breakpoint, and obtain a karyotype result corresponding to the target sample.

[0165] Optionally, the sequencing data includes multiple gene fragments, and each gene fragment includes base types and sequencing qualities corresponding to multiple bases.

[0166] In some embodiments, the screening module 840 is further used to remove gene fragments in the sequencing data whose base types corresponding to multiple bases do not meet the base information conditions, and / or gene fragments whose sequencing qualities corresponding to multiple bases do not meet the gene quality conditions; the base information conditions include: the proportion of the number of first bases belonging to the target base type is greater than a first proportion threshold, and the proportion of the number of second bases whose base type cannot be determined is less than a second proportion threshold; the gene quality conditions include: the proportion of the number of bases whose sequencing quality is greater than the target quality threshold is greater than a third proportion threshold.

[0167] In some embodiments, the annotation module 830 is further configured to annotate the alignment result according to the genome annotation file to obtain chimera information when the alignment result satisfies the genome alignment condition.

[0168] Optionally, the alignment results include base sequence alignment results, regional alignment results, and ribosomal RNA statistics. Genome alignment conditions include: base sequence alignment results indicating that the alignment ratio between the sequencing data and the reference genome data is greater than an alignment threshold; regional alignment results indicating that the proportion of exon regions in the sequencing data is greater than a regional threshold; and rRNA statistics results indicating that the ratio of rRNA to total RNA in the sequencing data is less than a ratio threshold.

[0169] In some embodiments, the screening module 840 is further used to determine a first position of the first breakpoint on the first gene segment and a second position of the second breakpoint on the first gene segment based on chromosome information corresponding to the first breakpoint and the second breakpoint contained in the first gene segment; the first gene segment includes a spliced ​​first chromosome and a second chromosome, and both ends of the second chromosome are spliced ​​into the first chromosome, and the first breakpoint and the second breakpoint are the breakpoints corresponding to the two ends of the second chromosome respectively; if the first position is within the valid segment interval and the second position is within the valid segment interval, the first breakpoint and the second breakpoint are used as target breakpoints.

[0170] In some embodiments, the screening module 840 is further configured to determine a target chromosome identifier and a target breakpoint sequence fragment corresponding to the third breakpoint based on the chromosome information corresponding to the third breakpoint, where the target chromosome identifier is used to indicate the spliced ​​chromosome corresponding to the third breakpoint; the third breakpoint is any breakpoint among a plurality of breakpoints; the target chromosome identifier and the target breakpoint sequence fragment are compared with each gene fragment to determine a first number of gene fragments including the third breakpoint; and if the first number is greater than a number threshold, the third breakpoint is selected as the target breakpoint.

[0171] In some embodiments, the screening module 840 is further used to obtain chromosome information corresponding to multiple preset breakpoints; the preset breakpoints are breakpoints generated normally by chromosome connection; if there is no preset breakpoint identical to the fourth breakpoint among the multiple preset breakpoints, the fourth breakpoint is used as the target breakpoint; the fourth breakpoint is any breakpoint among the multiple breakpoints.

[0172] In an embodiment of the present application, the computer device can accurately locate sequence fragments in the sequencing data that differ from the reference genome by comparing the sequencing data with the reference genome data, and obtain chimeric information containing breakpoint chromosome information based on the comparison results annotation of the genome annotation file, so that the originally complex and difficult to intuitively understand sequencing data is converted into a description of the breakpoint position and chromosome chimera with clear biological significance, which can effectively eliminate the interference of non-target breakpoints, thereby avoiding false positive results, and ensure that the real target breakpoints are not missed, avoiding false negative results, thereby reducing errors caused by misjudgment or omission in the processing of sequencing data, and improving the sequencing accuracy of the sample. Accurate and efficient target breakpoint identification and analysis also directly improve the overall analysis efficiency, thereby obtaining accurate sample karyotype results, which is conducive to further bioinformatics analysis.

[0173] An embodiment of the present application discloses a computer-readable storage medium storing a computer program, wherein the computer program implements the methods described in the above embodiments when executed by a processor.

[0174] The embodiments of the present application disclose a computer program product, including a computer program, and the computer program can be executed by a processor to implement the methods described in the above embodiments.

[0175] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When executed, the program can include the processes in the above-described method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or the like.

[0176] As used herein, any reference to memory, storage, database, or other medium may include nonvolatile and / or volatile memory. Suitable nonvolatile memory may include ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which serves as an external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus DRAM (RDRAM), and direct Rambus DRAM (DRDRAM).

[0177] It should be understood that the references to "one embodiment" or "an embodiment" throughout the specification mean that the specific features, structures, or characteristics associated with the embodiment are included in at least one embodiment of the present application. Therefore, the references to "in one embodiment" or "in an embodiment" throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. Those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required for the present application.

[0178] In the various embodiments of the present application, it should be understood that the size of the serial numbers of the above-mentioned processes does not necessarily mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0179] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0180] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of these units may be selected based on actual needs to achieve the objectives of this embodiment.

[0181] In addition, the functional units in the embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0182] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-accessible memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a memory and includes several requests for a computer device (which can be a personal computer, server or network device, etc., specifically a processor in a computer device) to execute some or all of the steps of the above-mentioned methods of various embodiments of the present application.

[0183] The above describes in detail the chromosome detection method, apparatus, computer device, and storage medium disclosed in the embodiments of this application. Specific examples are used herein to illustrate the principles and implementation methods of this application. The description of the above embodiments is intended only to facilitate understanding of the method and core concepts of this application. Furthermore, those skilled in the art will appreciate that variations in the specific implementation methods and scope of application may occur based on the concepts of this application. In summary, this specification should not be construed as limiting this application.

Claims

1. A computer device, characterized in that: The system comprises a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the following steps: Obtain sequencing data corresponding to the target sample; Comparing the sequencing data with the reference genome data to obtain an alignment result; Annotating the alignment result according to the genome annotation file to obtain chimeric information, wherein the chimeric information includes chromosome information corresponding to the multiple breakpoints; screening the multiple breakpoints based on chromosome information corresponding to each of the breakpoints to obtain at least one target breakpoint; The target breakpoint is a breakpoint caused by abnormal chromosome connection; According to the chromosome information corresponding to the at least one target breakpoint, a chromosome karyotype analysis is performed on the target sample to obtain a karyotype result corresponding to the target sample.

2. The computer device according to claim 1, wherein: The sequencing data includes a plurality of gene fragments, each of the gene fragments includes a base type and sequencing quality corresponding to a plurality of bases; before comparing the sequencing data with the reference genome data to obtain the comparison result, the processor further performs the following steps: Removing gene fragments in the sequencing data whose base types corresponding to the multiple bases do not meet the base information conditions, and / or whose sequencing qualities corresponding to the multiple bases do not meet the gene quality conditions; The base information condition includes: the proportion of the number of first bases belonging to the target base type is greater than a first ratio threshold, and the proportion of the number of second bases whose base type cannot be determined is less than a second ratio threshold; The gene quality condition includes: the proportion of bases with sequencing quality greater than the target quality threshold is greater than a third ratio threshold.

3. The computer device according to claim 1, wherein: The step of annotating the alignment result according to the genome annotation file to obtain chimeric information includes: When the alignment result meets the genome alignment conditions, the alignment result is annotated according to the genome annotation file to obtain chimera information.

4. The computer device according to claim 3, wherein: The comparison results include base sequence comparison results, regional comparison results and ribosomal RNA statistical results; the genome comparison conditions include: The base sequence alignment result is that the alignment rate between the sequencing data and the reference genome data is greater than an alignment threshold; and, The regional comparison result is that the proportion of exon regions in the sequencing data is greater than the regional threshold; and, The rRNA statistical result is that the ratio of rRNA to total RNA in the sequencing data is less than a ratio threshold.

5. The computer device according to claim 1, wherein: The step of screening the multiple breakpoints based on the chromosome information corresponding to each breakpoint to obtain at least one target breakpoint includes: determining a first position of the first breakpoint on the first gene segment and a second position of the second breakpoint on the first gene segment based on chromosome information corresponding to a first breakpoint and a second breakpoint contained in the first gene segment; the first gene segment includes a spliced ​​first chromosome and a second chromosome, and both ends of the second chromosome are spliced ​​into the first chromosome, and the first breakpoint and the second breakpoint are breakpoints corresponding to both ends of the second chromosome, respectively; If the first position is within a valid segment interval and the second position is within the valid segment interval, the first breakpoint and the second breakpoint are used as target breakpoints.

6. The computer device according to claim 1, wherein: The sequencing data includes a plurality of gene fragments; and the plurality of breakpoints are screened based on chromosome information corresponding to each of the breakpoints to obtain at least one target breakpoint, comprising: determining, based on chromosome information corresponding to a third breakpoint, a target chromosome identifier and a target breakpoint sequence fragment corresponding to the third breakpoint, wherein the target chromosome identifier is used to indicate a spliced ​​chromosome corresponding to the third breakpoint; the third breakpoint being any breakpoint among the multiple breakpoints; Comparing the target chromosome identifier and the target breakpoint sequence fragment with each of the gene fragments to determine a first number of gene fragments including the third breakpoint; If the first number is greater than a number threshold, the third breakpoint is used as a target breakpoint.

7. The computer device according to claim 1, wherein: The step of screening the multiple breakpoints based on the chromosome information corresponding to each breakpoint to obtain at least one target breakpoint includes: Obtaining chromosome information corresponding to a plurality of preset breakpoints; the preset breakpoints are breakpoints generated by normal chromosome connection; If there is no preset breakpoint identical to the fourth breakpoint among the plurality of preset breakpoints, the fourth breakpoint is used as the target breakpoint; the fourth breakpoint is any breakpoint among the plurality of breakpoints.

8. A chromosome detection method, characterized in that: Applied to a computer device, the method comprises: Obtain sequencing data corresponding to the target sample; Comparing the sequencing data with the reference genome data to obtain an alignment result; Annotating the alignment result according to the genome annotation file to obtain chimeric information, wherein the chimeric information includes chromosome information corresponding to the multiple breakpoints; Based on the chromosome information corresponding to each of the breakpoints, the multiple breakpoints are screened to obtain at least one target breakpoint; the target breakpoint is a breakpoint caused by chromosome connection abnormality; According to the chromosome information corresponding to the at least one target breakpoint, a chromosome karyotype analysis is performed on the target sample to obtain a karyotype result corresponding to the target sample.

9. A chromosome detection device, characterized in that: Applied to computer equipment, the device comprises: An acquisition module is used to obtain sequencing data corresponding to the target sample; An alignment module, configured to align the sequencing data with the reference genome data to obtain an alignment result; an annotation module, configured to annotate the alignment result according to a genome annotation file to obtain chimeric information, wherein the chimeric information includes chromosome information corresponding to the plurality of breakpoints; a screening module, configured to screen the multiple breakpoints based on chromosome information corresponding to each of the breakpoints to obtain at least one target breakpoint; the target breakpoint is a breakpoint caused by abnormal chromosome connection; An analysis module is used to perform chromosome karyotype analysis on the target sample according to the chromosome information corresponding to the at least one target breakpoint, so as to obtain a karyotype result corresponding to the target sample.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to perform the steps according to any one of claims 1 to 7.

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