Cloning identification method for immune repertoire gene rearrangement and electronic equipment

Abstract

The invention discloses a clone identification method for immune repertoire gene rearrangement and electronic equipment, which are used for correcting sequencing errors and correcting PCR (Polymerase Chain Reaction) amplification deviation bias to ensure that the number of the clone rearrangement is close to that of clone rearrangement in original DNA (Deoxyribose Nucleic Acid). The method comprises the steps that nucleic acid sequencing data are obtained, the nucleic acid sequencing data are generated based on nucleic acid samples and tag sequences, and the tag sequences are used for distinguishing different types of nucleic acid samples; clustering the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data; correcting the base of each site in the nucleic acid sequencing data contained in each nucleic acid cluster according to the consistency of the base quality to obtain a corrected nucleic acid cluster; and determining corrected sequencing data according to the corrected nucleic acid cluster, and performing clone identification on the corrected sequencing data to obtain a clone identification result of the nucleic acid sequencing data.

Description

Technical Field

[0001] The present invention relates to the field of biotechnology, and in particular to a cloning identification method and electronic equipment for immune repertoire gene rearrangement. Background Art

[0002] In the immune system, T lymphocytes and B lymphocytes recognize and bind to specific antigens through their surface cell receptors (TCR or BCR), respectively, to specifically eliminate pathogens or tumor cells. Functional TR genes include 43-45 TRAVs, 50 TRAJs, 40-48 TRBVs, 2 TRBDs, 12-13 TRBJs, 4-6 TRGVs, 5 TRGJs, 3 TRDVs, 3 TRDDs, 4 TRDJs, and TCRs; functional IG genes include 38-46 IGHVs, 23 IGHDs, 6 IGHJs, 34-38 IGKVs, 5 IGKJs, 29-33 IGLVs, and 4-6 IGLJs. Through the rearrangement and combination of the V(D)J gene segments of the TR (TRA, TRB, TRG, TRD) and IG (IGH, IGK, IGL) genes, abundant antibodies will be produced. Under normal circumstances, TR and IG gene rearrangements are random, and T lymphocytes and B lymphocytes are polyclonal, with the potential to exert various cellular immune effects. During the occurrence of lymphoma, lymphocytes are transformed in one or several specific TR or IG gene rearranged cells, resulting in monoclonal expression of TR or IG genes, causing lymphocytes to show clonal proliferation, resulting in the appearance of one or two major lymphocyte clones in lymph nodes, peripheral blood or bone marrow cells, which are monoclonal. The clonal rearrangement of the TR or IG gene family is an important feature of lymphoma cell populations. Therefore, NGS technology can be used to sequence BCR and TCR genes to obtain gene rearrangement results, thereby achieving auxiliary diagnosis and differential diagnosis of the disease, monitoring of minimal residual disease (MRD) after treatment, etc.

[0003] However, the NGS gene sequencing process will have sequencing data quality problems, mainly from two aspects: library construction process and sequencing process. For example, contamination in the library construction process will introduce non-sample sequences, unbalanced PCR (Polymerase Chain Reaction) primer concentration will cause some sequences to be over-amplified while some sequences are not amplified, and sequencing errors caused by uneven base quality during sequencing. These problems make the final identification of clonal gene rearrangements inaccurate.

[0004] Existing clonal rearrangement identification tools such as mixcr and igblastn are commonly used in non-molecular marker immune group gene rearrangement sequencing data, but they do not correct PCR bias errors and sequencing errors, resulting in certain deviations in the analyzed clonal results. Megic is a method that uses UMI (Unique Molecular Identifier) ​​technology for correction, but it targets a narrow range of experimental types, has poor generalization, and has certain deviations in the results. Summary of the invention

[0005] The present invention provides a clone identification method and electronic equipment for immune repertoire gene rearrangement, which are used to correct sequencing errors and PCR amplification bias to ensure that the clone rearrangement number is close to that in the original DNA.

[0006] In a first aspect, an embodiment of the present invention provides a method for cloning and identifying immune repertoire gene rearrangements, the method comprising:

[0007] Acquiring nucleic acid sequencing data, wherein the nucleic acid sequencing data is generated based on the nucleic acid sample and a tag sequence, wherein the tag sequence is used to distinguish different types of nucleic acid samples;

[0008] Clustering nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data;

[0009] According to the consistency of base quality, the bases at each site in the nucleic acid sequencing data contained in each nucleic acid cluster are corrected to obtain a corrected nucleic acid cluster;

[0010] Corrected sequencing data is determined according to the corrected nucleic acid clusters, and clone identification is performed on the corrected sequencing data to obtain clone identification results of the nucleic acid sequencing data.

[0011] As an optional implementation, obtaining nucleic acid sequencing data includes:

[0012] Obtaining a nucleic acid sample, and adding a tag sequence to the primer end of the nucleic acid sample, wherein the tag sequence is determined according to a randomly generated base sequence;

[0013] The base sequence of the nucleic acid sample with the added tag sequence is amplified to obtain the nucleic acid sequencing data.

[0014] As an optional implementation, after acquiring the nucleic acid sequencing data and before clustering the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data, the method further includes:

[0015] removing bases whose base quality is lower than a first threshold; and / or,

[0016] The nucleic acid sequencing data and the sequencing adapter sequences of the nucleic acid sequencing data whose average base quality is lower than a second threshold are removed.

[0017] As an optional implementation, after acquiring the nucleic acid sequencing data and before clustering the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data, the method further includes:

[0018] Remove nucleic acid sequencing data that does not contain primers and / or tag sequences.

[0019] As an optional implementation, after clustering the nucleic acid sequencing data of the same tag sequence into one nucleic acid cluster and before obtaining the corrected nucleic acid cluster, the method further includes:

[0020] The sequence numbers of the nucleic acid sequencing data in the nucleic acid clusters are sorted, and nucleic acid clusters whose sequence numbers are less than the lower quartile are removed.

[0021] As an optional implementation, the bases at each site in the nucleic acid sequencing data contained in each nucleic acid cluster are corrected according to the consistency of the base quality to obtain a corrected nucleic acid cluster, including:

[0022] For the base at each site of the nucleic acid cluster, determining the base quality of the base at the site in the nucleic acid sequencing data contained in the nucleic acid cluster;

[0023] If the consistency of the base quality of the base at the site is greater than a threshold, the base at the site is corrected to a consistent base, where the consistent base represents a base whose consistency of the base quality is greater than the threshold;

[0024] The corrected nucleic acid cluster is determined based on the bases of each corrected site.

[0025] As an optional implementation, it also includes:

[0026] If the consistency of the base quality of the base at the site is less than or equal to the threshold, the base at the site is removed;

[0027] Based on the consistency of the base quality of the bases at other sites after excision, the bases at other sites continue to be corrected.

[0028] As an optional embodiment, after obtaining the corrected nucleic acid clusters and before determining the corrected sequencing data according to the corrected nucleic acid clusters, the method further includes:

[0029] Calculating the similarity between the corrected nucleic acid clusters corresponding to different tag sequences;

[0030] When the similarity is greater than a similarity threshold, the corrected nucleic acid clusters corresponding to the different tag sequences are merged to obtain a merged nucleic acid cluster.

[0031] As an optional implementation, the performing clone identification on the corrected sequencing data includes:

[0032] The corrected sequencing data are spliced ​​to obtain spliced ​​sequencing data, the spliced ​​sequencing data are compared with the immune data in a preset immune group database, and clone identification is performed on the corrected sequencing data according to the comparison result.

[0033] In a second aspect, an embodiment of the present invention provides an electronic device, including a processor and a memory, wherein the memory is used to store a program executable by the processor, and the processor is used to read the program in the memory and perform the following steps:

[0034] Acquiring nucleic acid sequencing data, wherein the nucleic acid sequencing data is generated based on the nucleic acid sample and a tag sequence, wherein the tag sequence is used to distinguish different types of nucleic acid samples;

[0035] Clustering nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data;

[0036] According to the consistency of base quality, the bases at each site in the nucleic acid sequencing data contained in each nucleic acid cluster are corrected to obtain a corrected nucleic acid cluster;

[0037] Corrected sequencing data is determined according to the corrected nucleic acid clusters, and clone identification is performed on the corrected sequencing data to obtain clone identification results of the nucleic acid sequencing data.

[0038] As an optional implementation, the processor is specifically configured to execute:

[0039] Obtaining a nucleic acid sample, and adding a tag sequence to the primer end of the nucleic acid sample, wherein the tag sequence is determined according to a randomly generated base sequence;

[0040] The base sequence of the nucleic acid sample with the added tag sequence is amplified to obtain the nucleic acid sequencing data.

[0041] As an optional implementation, after acquiring the nucleic acid sequencing data and before clustering the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data, the processor is further configured to execute:

[0042] removing bases whose base quality is lower than a first threshold; and / or,

[0043] The nucleic acid sequencing data and the sequencing adapter sequences of the nucleic acid sequencing data whose average base quality is lower than a second threshold are removed.

[0044] As an optional implementation, after acquiring the nucleic acid sequencing data and before clustering the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data, the processor is further configured to execute:

[0045] Remove nucleic acid sequencing data that does not contain primers and / or tag sequences.

[0046] As an optional implementation, after clustering the nucleic acid sequencing data of the same tag sequence into one nucleic acid cluster and before obtaining the corrected nucleic acid cluster, the processor is further configured to execute:

[0047] The sequence numbers of the nucleic acid sequencing data in the nucleic acid clusters are sorted, and nucleic acid clusters whose sequence numbers are less than the lower quartile are removed.

[0048] As an optional implementation, the processor is specifically configured to execute:

[0049] For the base at each site of the nucleic acid cluster, determining the base quality of the base at the site in the nucleic acid sequencing data contained in the nucleic acid cluster;

[0050] If the consistency of the base quality of the base at the site is greater than a threshold, the base at the site is corrected to a consistent base, where the consistent base represents a base whose consistency of the base quality is greater than the threshold;

[0051] The corrected nucleic acid cluster is determined based on the bases of each corrected site.

[0052] As an optional implementation, the processor is further configured to execute:

[0053] If the consistency of the base quality of the base at the site is less than or equal to the threshold, the base at the site is removed;

[0054] Based on the consistency of the base quality of the bases at other sites after excision, the bases at other sites continue to be corrected.

[0055] As an optional implementation, after obtaining the corrected nucleic acid clusters and before determining the corrected sequencing data according to the corrected nucleic acid clusters, the processor is further configured to execute:

[0056] Calculating the similarity between the corrected nucleic acid clusters corresponding to different tag sequences;

[0057] When the similarity is greater than a similarity threshold, the corrected nucleic acid clusters corresponding to the different tag sequences are merged to obtain a merged nucleic acid cluster.

[0058] As an optional implementation, the processor is specifically configured to execute:

[0059] The corrected sequencing data are spliced ​​to obtain spliced ​​sequencing data, the spliced ​​sequencing data are compared with the immune data in a preset immune group database, and clone identification is performed on the corrected sequencing data according to the comparison result.

[0060] In a third aspect, an embodiment of the present invention provides a clonal identification device for immune repertoire gene rearrangement, the device comprising:

[0061] An acquisition sequencing data unit is used to acquire nucleic acid sequencing data, wherein the nucleic acid sequencing data is generated based on a nucleic acid sample and a label sequence, wherein the label sequence is used to distinguish different types of nucleic acid samples;

[0062] A clustering unit, used for clustering nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data;

[0063] A quality correction unit, used to correct the bases at each site in the nucleic acid sequencing data contained in each nucleic acid cluster according to the consistency of the base quality, so as to obtain a corrected nucleic acid cluster;

[0064] The clone identification unit is used to determine the corrected sequencing data according to the corrected nucleic acid cluster, perform clone identification on the corrected sequencing data, and obtain the clone identification result of the nucleic acid sequencing data.

[0065] As an optional implementation manner, the unit for obtaining sequencing data is specifically used for:

[0066] Obtaining a nucleic acid sample, and adding a tag sequence to the primer end of the nucleic acid sample, wherein the tag sequence is determined according to a randomly generated base sequence;

[0067] The base sequence of the nucleic acid sample with the added tag sequence is amplified to obtain the nucleic acid sequencing data.

[0068] As an optional implementation, the device further includes a first removal unit, specifically configured to:

[0069] removing bases whose base quality is lower than a first threshold; and / or,

[0070] The nucleic acid sequencing data and the sequencing adapter sequences of the nucleic acid sequencing data whose average base quality is lower than a second threshold are removed.

[0071] As an optional implementation, the device further includes a second removal unit, specifically configured to:

[0072] Remove nucleic acid sequencing data that does not contain primers and / or tag sequences.

[0073] As an optional implementation, the device further includes a third removal unit, specifically configured to:

[0074] The sequence numbers of the nucleic acid sequencing data in the nucleic acid clusters are sorted, and nucleic acid clusters whose sequence numbers are less than the lower quartile are removed.

[0075] As an optional implementation manner, the mass correction unit is specifically used for:

[0076] For the base at each site of the nucleic acid cluster, determining the base quality of the base at the site in the nucleic acid sequencing data contained in the nucleic acid cluster;

[0077] If the consistency of the base quality of the base at the site is greater than a threshold, the base at the site is corrected to a consistent base, where the consistent base represents a base whose consistency of the base quality is greater than the threshold;

[0078] The corrected nucleic acid cluster is determined based on the bases of each corrected site.

[0079] As an optional implementation, the device further includes a cutting correction unit, which is specifically configured to:

[0080] If the consistency of the base quality of the base at the site is less than or equal to the threshold, the base at the site is removed;

[0081] Based on the consistency of the base quality of the bases at other sites after excision, the bases at other sites continue to be corrected.

[0082] As an optional implementation manner, the device further includes a merging unit, specifically configured to:

[0083] Calculating the similarity between the corrected nucleic acid clusters corresponding to different tag sequences;

[0084] When the similarity is greater than a similarity threshold, the corrected nucleic acid clusters corresponding to the different tag sequences are merged to obtain a merged nucleic acid cluster.

[0085] As an optional implementation, the clone identification unit is specifically used for:

[0086] The corrected sequencing data are spliced ​​to obtain spliced ​​sequencing data, the spliced ​​sequencing data are compared with the immune data in a preset immune group database, and clone identification is performed on the corrected sequencing data according to the comparison result.

[0087] In a fourth aspect, an embodiment of the present invention further provides a computer storage medium on which a computer program is stored, and when the program is executed by a processor, it is used to implement the steps of the method described in the first aspect above.

[0088] These and other aspects of the present application will be more clearly understood in the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0090] Figure 1 A flowchart of an implementation method of a clone identification method of immune repertoire gene rearrangement provided in an embodiment of the present invention;

[0091] Figures 2A-2C A schematic diagram of clone identification and analysis results of different nucleic acid samples provided by an embodiment of the present invention;

[0092] Figures 3A-3C A schematic diagram of clone identification analysis results of a nucleic acid sample not based on UMI clustering provided in an embodiment of the present invention;

[0093] Figure 4 A specific implementation flow chart of a method for cloning and identifying immune repertoire gene rearrangements provided in an embodiment of the present invention;

[0094] Figure 5 A schematic diagram of an electronic device provided by an embodiment of the present invention;

[0095] Figure 6 A schematic diagram of a clonal identification device for immune repertoire gene rearrangement provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0096] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0097] In the embodiments of the present invention, the term "and / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0098] The application scenarios described in the embodiments of the present invention are intended to more clearly illustrate the technical solutions of the embodiments of the present invention, and do not constitute a limitation on the technical solutions provided by the embodiments of the present invention. It is known to those skilled in the art that with the emergence of new application scenarios, the technical solutions provided by the embodiments of the present invention are also applicable to similar technical problems. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0099] High-throughput sequencing technology, also known as the second-generation sequencing technology (NGS), refers to the technology of sequencing hundreds of thousands to millions of DNA (Deoxyribonucleic Acid) or RNA (Ribonucleic Acid) molecules in parallel at one time. High-throughput sequencing mainly includes the following processes: sample collection and nucleic acid extraction, targeted sequence enrichment and sequencing library construction, sequencing and result analysis.

[0100] In the immune system, T lymphocytes and B lymphocytes recognize and bind to specific antigens through their surface cell receptors (TCR or BCR), respectively, to specifically eliminate pathogens or tumor cells. Functional TR genes include 43-45 TRAVs, 50 TRAJs, 40-48 TRBVs, 2 TRBDs, 12-13 TRBJs, 4-6 TRGVs, 5 TRGJs, 3 TRDVs, 3 TRDDs, 4 TRDJs, and TCRs; functional IG genes include 38-46 IGHVs, 23 IGHDs, 6 IGHJs, 34-38 IGKVs, 5 IGKJs, 29-33 IGLVs, and 4-6 IGLJs. Through the rearrangement and combination of the V(D)J gene segments of the TR (TRA, TRB, TRG, TRD) and IG (IGH, IGK, IGL) genes, abundant antibodies will be produced. Under normal circumstances, TR and IG gene rearrangements are random, and T lymphocytes and B lymphocytes are polyclonal, with the potential to exert various cellular immune effects. During the occurrence of lymphoma, lymphocytes are transformed in one or several specific TR or IG gene rearranged cells, resulting in monoclonal expression of TR or IG genes, causing lymphocytes to show clonal proliferation, resulting in the appearance of one or two major lymphocyte clones in lymph nodes, peripheral blood or bone marrow cells, which are monoclonal. The clonal rearrangement of the TR or IG gene family is an important feature of lymphoma cell populations. Therefore, NGS technology can be used to sequence BCR and TCR genes to obtain gene rearrangement results, thereby achieving auxiliary diagnosis and differential diagnosis of the disease, monitoring of minimal residual disease (MRD) after treatment, etc.

[0101] However, the quality of sequencing data will be problematic in the NGS gene sequencing process, mainly from two aspects: library construction and sequencing. For example, contamination during library construction will introduce non-sample sequences, unbalanced PCR primer concentration will cause some sequences to be over-amplified while some sequences will not be amplified, and sequencing errors caused by uneven base quality during sequencing. These problems make the final identification of clonal gene rearrangements inaccurate. Existing clonal rearrangement identification tools such as mixcr and igblastn are commonly used in non-molecular marker immune gene rearrangement sequencing data, but they do not correct PCR bias errors and sequencing errors, resulting in a certain deviation in the analyzed cloning results. Megic is a method that uses UMI tags for correction, but it targets a narrow range of experimental types, has poor generalization, and has certain deviations in the results. Although there are also methods that cluster two UMIs into a cluster based on the Hamming distance between different UMI tags being less than 1 and the number of immune gene sequences contained being similar, and find consistent immune gene sequences, although it can reduce the impact of UMI sequence errors in the PCR process on the accuracy of immune gene sequencing, it cannot guarantee the consistency of the immune gene sequences in the two clusters.

[0102] It should be noted that the experimental methods used in this example are conventional methods unless otherwise specified. The materials, reagents, etc. used in this example can be obtained from commercial sources unless otherwise specified.

[0103] The present embodiment provides a method for clonal identification of immune repertoire gene rearrangement, which clusters nucleic acid sequencing data based on tag sequences, and for a nucleic acid cluster of the same category, corrects the bases at each site in the nucleic acid sequencing data within the nucleic acid cluster according to the consistency of the base quality to obtain corrected sequencing data, and performs clonal identification on the corrected sequencing data, and traces back to the original DNA according to the tag sequence and the comparison position, and compares the consensus sequences (consensus) of multiple sequences derived from the same DNA to identify whether the mutation is real or introduced by random errors. Not only can sequencing errors be corrected, but PCR amplification bias can also be corrected to ensure that the number of clonal rearrangements is close to that in the original DNA.

[0104] like Figure 1 As shown, the implementation process of a clone identification method for immune repertoire gene rearrangement provided in this embodiment is as follows:

[0105] Step 100: Acquire nucleic acid sequencing data, where the nucleic acid sequencing data is generated based on a nucleic acid sample and a tag sequence, where the tag sequence is used to distinguish different types of nucleic acid samples;

[0106] In some embodiments, nucleic acid sequencing data is obtained by:

[0107] A nucleic acid sample is obtained, and a label sequence is added to the primer end of the nucleic acid sample, wherein the label sequence is determined according to a randomly generated base sequence; and the base sequence of the nucleic acid sample with the label sequence added is amplified to obtain the nucleic acid sequencing data.

[0108] Optionally, the nucleic acid samples in this embodiment include but are not limited to DNA fragments. For example, 58 plasmids and raji samples are used as nucleic acid samples to clone and identify the IGK gene. In implementation, a label sequence can be added to the primer end of the nucleic acid sample, a label sequence can be added to the reverse primer end, or a label sequence can be added to the forward primer end. It should be noted that the reverse primer end is the 3' end, because when multiple primers are amplified, for example, for the design of IGKV family genes, the forward primer end may require 20 to include the alleles of this family, while the reverse primer end only requires 5. Therefore, for the IGKV family genes, it is more appropriate to add UMI to the reverse primer. The end at which the label sequence is added can be selected according to actual needs, and this embodiment does not impose too many restrictions on this.

[0109] Optionally, the tag sequence in this embodiment includes but is not limited to a single molecule tag (Unique Molecular Identifier, UMI) sequence, wherein the UMI technology adds a unique short tag sequence to each original DNA before PCR amplification. After library construction and sequencing are completed, the original DNA can be traced back according to the UMI tag sequence and the alignment position, and the consensus sequence (consensus) of multiple sequences derived from the same DNA can be compared to identify whether the mutation is real or introduced by random errors. Not only can sequencing errors be corrected, but PCR amplification bias can also be corrected to ensure that the number of clonal rearrangements is close to that in the original DNA.

[0110] The consensus sequence refers to the nucleotide or amino acid sequence that appears most frequently at each position in a set of sequence alignment results.

[0111] Assuming that the length of UMI is 8 bases, there are 65,536 kinds of UMI molecules connected to the reverse primer. Therefore, the sequences belonging to the same UMI must come from the same original DNA template. By comparing the consistency of these sequences, the random errors introduced by the amplification process can be corrected. The obtained consistent sequence is compared with the genome to determine whether there is a mutation.

[0112] For example, in this embodiment, a UMI tag of 8 random bases can be introduced at the reverse primer end, and no UMI tag is added to the forward primer end to amplify the base sequence and obtain the nucleic acid sequencing data.

[0113] In some embodiments, after obtaining nucleic acid sequencing data, any one or more of the following may also be performed:

[0114] Method 1: remove bases whose base quality is lower than the first threshold.

[0115] Method 2: removing nucleic acid sequencing data with an average base quality lower than a second threshold and sequencing adapter sequences of the nucleic acid sequencing data.

[0116] Method 3: removing bases whose base quality is lower than a first threshold, and removing nucleic acid sequencing data whose average base quality is lower than a second threshold and sequencing adapter sequences of the nucleic acid sequencing data.

[0117] Optionally, the first threshold and the second threshold in this embodiment may be the same or different, and this embodiment does not impose too many restrictions on this.

[0118] In practice, after obtaining the nucleic acid sequencing data, the nucleic acid sequencing data is quality controlled, such as removing bases with a base quality lower than 20 and sequences with an average base quality lower than 20, and cutting out the sequencing adapter sequence. The quality in the base quality of this embodiment is not the "quality" in physics. The base quality value (quality score, Q-score) is an integer mapping of the probability of base recognition error in biophysics, Q = -10*lgP, where P is the probability of base recognition error. Simply put, each base in each sequence in the offline data has a quality value information, and by identifying this quality value information, you can understand the probability of this base being recognized incorrectly.

[0119] As shown in the following table, the comparison of the number of sequences and the number of bases in the nucleic acid sequencing data provided in this embodiment and the quality control nucleic acid sequencing data obtained by screening according to the base quality, as well as the ratio of the number of sequences remaining after screening.

[0120] Table 1 Comparison of nucleic acid sequencing data and quality control nucleic acid sequencing data

[0121]

[0122] In practice, quality control can be used to remove bases with low base quality, nucleic acid sequencing data with low average base quality, and sequencing adapter sequences. Quality control can be used to obtain sequencing data with higher quality, making downstream data analysis more reliable.

[0123] In some embodiments, after acquiring the nucleic acid sequencing data, and before clustering the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data, the following steps may be further performed:

[0124] Remove nucleic acid sequencing data that does not contain primers and / or tag sequences.

[0125] During implementation, the nucleic acid sequencing data after quality control can be screened again. Retain the nucleic acid sequencing data containing primers and UMI, and remove the nucleic acid sequencing data without primers and UMI.

[0126] Step 101: Cluster the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data;

[0127] During implementation, one nucleic acid sequencing data corresponds to one tag sequence. Different tag sequences are used to distinguish different categories of nucleic acid sequencing data. Therefore, nucleic acid sequencing data of the same category can be clustered into one category based on the tag sequence to form a nucleic acid cluster.

[0128] In some embodiments, after obtaining nucleic acid clusters corresponding to different UMIs through the above steps, the following steps are further performed:

[0129] Sort the number of sequences of the nucleic acid sequencing data in the nucleic acid cluster, and remove the nucleic acid clusters with the number of sequences less than the lower quartile.

[0130] During implementation, after obtaining the nucleic acid clusters, filter the nucleic acid sequencing data in the nucleic acid clusters, calculate the number of the number of sequences of the nucleic acid sequencing data contained in all nucleic acid clusters, and sort the number of sequences of the contained nucleic acid sequencing data. The sorting can be performed in ascending or descending order of the number of sequences. For example, after sorting in ascending order of the number of sequences, take the value at the lower quartile. This value is used as the threshold rho for filtering nucleic acid clusters. For example, when the number of the number of sequences of the nucleic acid sequencing data in a nucleic acid cluster < rho, discard the nucleic acid cluster and the nucleic acid sequencing data it contains. Take the number of types of the filtered nucleic acid clusters as the number of types of the preliminary gene rearrangement sequences. That is, initially, it is considered that the nucleic acid clusters corresponding to these UMIs amplify from different DNA template sequences (gene rearrangement sequences), and these DNA templates are composed of immune gene rearrangements. Such as IGKV family gene + IGKJ family gene; for example, a gene rearrangement sequence = IGKV2 + IGKJ4.

[0131] Among them, the lower quartile refers to "the value at the 25% position after sorting the array composed of the number of sequences contained in each nucleic acid cluster corresponding to all UMIs from small to large". This value is used as the threshold rho for filtering UMI clusters. For example, when the number of sequences in a nucleic acid cluster corresponding to a UMI < rho, discard the nucleic acid cluster corresponding to the UMI and the sequences it contains.

[0132] Step 102: Correct the bases at each site in the nucleic acid sequencing data contained in each nucleic acid cluster according to the consistency of base quality to obtain a corrected nucleic acid cluster;

[0133] During implementation, by controlling the base quality, the bases at the sites whose base quality does not meet the requirements in each nucleic acid cluster or the nucleic acid sequencing data containing the bases are removed to filter the nucleic acid sequencing data in the nucleic acid cluster to obtain nucleic acid sequencing data of better quality.

[0134] In some embodiments, quality control is performed by:

[0135] Step 1a) determining, for the base at each site of the nucleic acid cluster, the base quality of the base at the site in the nucleic acid sequencing data contained in the nucleic acid cluster;

[0136] During implementation, for each nucleic acid cluster, all nucleic acid sequencing data contained in the nucleic acid cluster are filtered, wherein, for each site of the nucleic acid sequencing data, the base masses of the bases at the site of each nucleic acid sequencing data are counted, the consistency of the base masses at the site is calculated, and the ratio of the base masses of the same base at the site to the base masses of all bases is recorded.

[0137] Step 1b) if the consistency of the base quality of the base at the site is greater than a threshold, the base at the site is corrected to a consistent base, where the consistent base represents a base whose consistency of the base quality is greater than the threshold;

[0138] In implementation, when the consistency of the base quality of each nucleic acid sequencing data at each site in the nucleic acid cluster is greater than a threshold, the base at the site is corrected to a consistent base. For example, at site 1, the consistency of the base quality of base A at site 1 of each nucleic acid sequencing data in the nucleic acid cluster is greater than a threshold, then the bases at site 1 of each nucleic acid sequencing data in the nucleic acid cluster are corrected to base A. For another example, at site 2, each nucleic acid sequencing data in the nucleic acid cluster is base B at site 2, then the consistent base is base B.

[0139] In some embodiments, if the consistency of the base quality of the base at the site is less than or equal to a threshold, the base at the site is excised; and based on the consistency of the base quality of the bases at other sites after excision, the bases at other sites continue to be corrected.

[0140] Step 1c) Determine the corrected nucleic acid cluster according to the corrected bases at each site.

[0141] Through the above steps, the base of each site of each nucleic acid sequencing data in each nucleic acid cluster is corrected to obtain a corrected nucleic acid cluster. After each nucleic acid cluster is corrected, the corrected sequencing data is obtained.

[0142] In the implementation, for the sequence of nucleic acid sequencing data in the nucleic acid cluster corresponding to each UMI, the mafft software is used to perform multiple sequence alignment, and the base quality value of each site is weighted. If the base consistency of the site is greater than 70%, the base of the site is corrected to a consistent base. As shown in Table 2, a multiple sequence comparison within a nucleic acid cluster corresponding to a UMI is provided.

[0143]

[0144] In some embodiments, after filtering the nucleic acid clusters through the above steps and obtaining the corrected nucleic acid clusters, the following steps are further performed:

[0145] Step 2a) calculating the similarity between the corrected nucleic acid clusters corresponding to different tag sequences;

[0146] Step 2b) when the similarity is greater than a similarity threshold, merging the corrected nucleic acid clusters corresponding to the different tag sequences to obtain a merged nucleic acid cluster; used to determine the corrected sequencing data based on the merged nucleic acid cluster.

[0147] In some embodiments, after obtaining the merged nucleic acid clusters, the following steps may be further performed:

[0148] The sequence numbers of the nucleic acid sequencing data in the merged nucleic acid clusters are sorted, and nucleic acid clusters with sequence numbers less than the lower quartile in the merged nucleic acid clusters are removed; and the correction sequencing data are determined based on the remaining nucleic acid clusters.

[0149] In implementation, the similarity of nucleic acid sequencing data in nucleic acid clusters corresponding to different UMIs can be calculated. If they are completely consistent or the similarity is greater than a similarity threshold, the two nucleic acid clusters are merged, and the number of sequences of the nucleic acid sequencing data contained in the two nucleic acid clusters is added. At the same time, the nucleic acid clusters whose sequence number in the merged nucleic acid cluster is less than the lower quartile are removed.

[0150] Step 103: determine the corrected sequencing data according to the corrected nucleic acid cluster, perform clone identification on the corrected sequencing data, and obtain clone identification results of the nucleic acid sequencing data.

[0151] In practice, after each nucleic acid cluster is corrected, each corrected nucleic acid cluster is obtained, and the corrected sequencing data is composed of each corrected nucleic acid cluster, and clone identification is performed on it.

[0152] In some embodiments, clone identification is performed on the corrected sequencing data by the following steps:

[0153] The corrected sequencing data are spliced ​​to obtain spliced ​​sequencing data, the spliced ​​sequencing data are compared with the immune data in a preset immune group database, and clone identification is performed on the corrected sequencing data according to the comparison result.

[0154] In implementation, since the correction sequencing data are all DNA fragments, it is necessary to splice the individual correction sequencing data to obtain the spliced ​​sequencing data, and then compare and annotate the spliced ​​sequencing data with the IMGT immune group database to screen out the matching correction sequencing data, and then perform clone identification analysis on the screened correction sequencing data.

[0155] It should be noted that the sequencing in this embodiment adopts double-end sequencing, that is, the result of sequencing a PCR-amplified DNA fragment, that is, the sequencing result of the nucleic acid sequencing data in this embodiment includes the double-end results of R1 (3' end) and R2 (5' end). When correcting the nucleic acid cluster, both R1 and R2 need to be corrected.

[0156] like Figures 2A-2C As shown, this embodiment provides a schematic diagram of clone identification analysis results of different nucleic acid samples, where the horizontal axis represents the nucleic acid sample and the vertical axis represents the sequence number of nucleic acid sequencing data. Figures 3A-3C As shown, this embodiment also provides a clone identification analysis result of a nucleic acid sample not based on UMI clustering. The horizontal axis represents the sample, the vertical axis represents the sequence number, and the analysis is performed using the mixcr software. The results are as follows:

[0157]

[0158] It should be noted that the nucleic acid sequencing data in this embodiment includes but is not limited to Wes-seq, RNA-seq and other experimental types carrying UMI molecular tags, which can remove PCR amplification preferences and correct random errors introduced by PCR. When performing clonal analysis, it is only necessary to replace the preset immune group database with the required rearranged gene database to perform sequence type / sequence rearrangement identification.

[0159] This embodiment traces back to the original DNA based on the tag sequence and the alignment position, and identifies whether the mutation is real or introduced by comparing the consensus sequence (consensus) of multiple nucleic acid sequencing data from the same DNA. It can not only correct sequencing errors, but also correct PCR amplification bias to ensure that the number of clone rearrangements is close to that in the original DNA. The UMI correction method used is used to correct the sequencing data to obtain more reliable gene rearrangement sequencing data. By clustering the nucleic acid sequencing data of the same UMI and removing the incomplete nucleic acid sequencing data, the base consistency weighted by the base quality value is first used to obtain the consistency within the nucleic acid cluster corresponding to the UMI, thereby correcting the errors generated in the sequencing process, and using a floating threshold (the lower quartile of the number of sequences within the nucleic acid cluster corresponding to the UMI) to filter and merge the number of UMI types (nucleic acid clusters), correct the deviation generated by PCR, so that the number of gene rearrangements compared is closer to the original test sample, and the false positive of the identified clone results caused by sequencing and PCR deviations is reduced.

[0160] like Figure 4 As shown, this embodiment provides a specific implementation step of a method for cloning and identifying immune repertoire gene rearrangement, as shown below:

[0161] Step 400: Obtain a nucleic acid sample, add a UMI to the primer end of the nucleic acid sample, amplify the base sequence of the nucleic acid sample with the added UMI, and obtain nucleic acid sequencing data;

[0162] Step 401, removing bases whose base quality is lower than a first threshold, and nucleic acid sequencing data whose average base quality is lower than a second threshold and sequencing adapter sequences of the nucleic acid sequencing data;

[0163] Step 402: removing nucleic acid sequencing data that does not contain primer and tag sequences;

[0164] Step 403: clustering nucleic acid sequencing data with the same UMI into a nucleic acid cluster according to the UMI of the nucleic acid sequencing data;

[0165] Step 404, sorting the sequence numbers of the nucleic acid sequencing data in the nucleic acid clusters, and removing nucleic acid clusters with sequence numbers less than the lower quartile;

[0166] Step 405: Correct the bases at each site in the nucleic acid sequencing data contained in each nucleic acid cluster according to the consistency of the base quality to obtain a corrected nucleic acid cluster;

[0167] Step 406, calculating the similarity between the corrected nucleic acid clusters corresponding to different tag sequences, and when the similarity is greater than a similarity threshold, merging the corrected nucleic acid clusters corresponding to different tag sequences to obtain a merged nucleic acid cluster;

[0168] Step 407, sorting the sequence numbers of the nucleic acid sequencing data in the merged nucleic acid clusters, and removing nucleic acid clusters with sequence numbers less than the lower quartile;

[0169] Step 408, determining the corrected sequencing data according to the corrected nucleic acid clusters, and splicing the corrected sequencing data to obtain spliced ​​sequencing data;

[0170] Step 409: compare the spliced ​​sequencing data with the immune data in the preset immune group database, perform clone identification on the corrected sequencing data according to the comparison result, and determine the gene rearrangement result of the nucleic acid sequencing data.

[0171] The present embodiment provides a method for clonal identification of immune repertoire gene rearrangement, which uses data quality control to obtain high-quality data and increase the reliability of downstream analysis. By clustering the nucleic acid sequencing data corresponding to the UMI, after removing the incomplete nucleic acid sequencing data, the consistent nucleic acid sequencing data of the UMI clustering cluster is obtained by using the base consistency weighted by the sequencing quality value, thereby correcting the errors generated in the sequencing process, and using a floating threshold (the lower quartile of the number of sequences in the nucleic acid cluster corresponding to the UMI) to filter and merge the number of UMI types (nucleic acid clusters), correct the deviation generated by PCR, so that the number of gene rearrangements compared is closer to the original test sample, and the false positive of the identified clone results caused by sequencing and PCR deviations is reduced. The method provided in this embodiment is applicable to all combinations of multiple gene rearrangements that may exist in B-lineage or T-lineage immune gene rearrangements, and is applicable to the downstream analysis and identification of minimal residual disease (MRD) and recurrence monitoring of lymphoma, immune repertoire sequencing, etc.

[0172] Based on the same inventive concept, an embodiment of the present invention further provides an electronic device. Since the electronic device is the electronic device in the method in the embodiment of the present invention, and the principle of solving the problem by the electronic device is similar to that of the method, the implementation of the electronic device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0173] like Figure 5 As shown, the electronic device includes a processor 500 and a memory 501, wherein the memory 501 is used to store a program executable by the processor 500, and the processor 500 is used to read the program in the memory 501 and perform the following steps:

[0174] Acquiring nucleic acid sequencing data, wherein the nucleic acid sequencing data is generated based on the nucleic acid sample and a tag sequence, wherein the tag sequence is used to distinguish different types of nucleic acid samples;

[0175] Clustering nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data;

[0176] According to the consistency of base quality, the bases at each site in the nucleic acid sequencing data contained in each nucleic acid cluster are corrected to obtain a corrected nucleic acid cluster;

[0177] Corrected sequencing data is determined according to the corrected nucleic acid clusters, and clone identification is performed on the corrected sequencing data to obtain clone identification results of the nucleic acid sequencing data.

[0178] As an optional implementation manner, the processor 500 is specifically configured to execute:

[0179] Obtaining a nucleic acid sample, and adding a tag sequence to the primer end of the nucleic acid sample, wherein the tag sequence is determined according to a randomly generated base sequence;

[0180] The base sequence of the nucleic acid sample with the added tag sequence is amplified to obtain the nucleic acid sequencing data.

[0181] As an optional implementation, after acquiring the nucleic acid sequencing data and before clustering the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data, the processor 500 is further configured to execute:

[0182] removing bases whose base quality is lower than a first threshold; and / or,

[0183] The nucleic acid sequencing data and the sequencing adapter sequences of the nucleic acid sequencing data whose average base quality is lower than a second threshold are removed.

[0184] As an optional implementation, after acquiring the nucleic acid sequencing data and before clustering the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data, the processor 500 is further configured to execute:

[0185] Remove nucleic acid sequencing data that does not contain primers and / or tag sequences.

[0186] As an optional implementation, after clustering the nucleic acid sequencing data of the same tag sequence into one nucleic acid cluster and before obtaining the corrected nucleic acid cluster, the processor 500 is further configured to execute:

[0187] The sequence numbers of the nucleic acid sequencing data in the nucleic acid clusters are sorted, and nucleic acid clusters whose sequence numbers are less than the lower quartile are removed.

[0188] As an optional implementation manner, the processor 500 is specifically configured to execute:

[0189] For the base at each site of the nucleic acid cluster, determining the base quality of the base at the site in the nucleic acid sequencing data contained in the nucleic acid cluster;

[0190] If the consistency of the base quality of the base at the site is greater than a threshold, the base at the site is corrected to a consistent base, where the consistent base represents a base whose consistency of the base quality is greater than the threshold;

[0191] The corrected nucleic acid cluster is determined based on the bases of each corrected site.

[0192] As an optional implementation manner, the processor 500 is further configured to execute:

[0193] If the consistency of the base quality of the base at the site is less than or equal to the threshold, the base at the site is removed;

[0194] Based on the consistency of the base quality of the bases at other sites after excision, the bases at other sites continue to be corrected.

[0195] As an optional implementation, after obtaining the corrected nucleic acid clusters and before determining the corrected sequencing data according to the corrected nucleic acid clusters, the processor 500 is further configured to execute:

[0196] Calculating the similarity between the corrected nucleic acid clusters corresponding to different tag sequences;

[0197] When the similarity is greater than a similarity threshold, the corrected nucleic acid clusters corresponding to the different tag sequences are merged to obtain a merged nucleic acid cluster.

[0198] As an optional implementation manner, the processor 500 is specifically configured to execute:

[0199] The corrected sequencing data are spliced ​​to obtain spliced ​​sequencing data, the spliced ​​sequencing data are compared with the immune data in a preset immune group database, and clone identification is performed on the corrected sequencing data according to the comparison result.

[0200] Based on the same inventive concept, an embodiment of the present invention also provides a clonal identification device for immune repertoire gene rearrangement. Since the device is the device in the method in the embodiment of the present invention, and the principle of solving the problem by the device is similar to that of the method, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0201] like Figure 6 As shown, the device comprises:

[0202] The sequencing data acquisition unit 600 is used to acquire nucleic acid sequencing data, wherein the nucleic acid sequencing data is generated based on the nucleic acid sample and the label sequence, wherein the label sequence is used to distinguish different types of nucleic acid samples;

[0203] A clustering unit 601 is used to cluster nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data;

[0204] The quality correction unit 602 is used to correct the bases at each site in the nucleic acid sequencing data contained in each nucleic acid cluster according to the consistency of the base quality, so as to obtain a corrected nucleic acid cluster;

[0205] The clone identification unit 603 is used to determine the corrected sequencing data according to the corrected nucleic acid cluster, perform clone identification on the corrected sequencing data, and obtain a clone identification result of the nucleic acid sequencing data.

[0206] As an optional implementation, the sequencing data acquisition unit 600 is specifically used for:

[0207] Obtaining a nucleic acid sample, and adding a tag sequence to the primer end of the nucleic acid sample, wherein the tag sequence is determined according to a randomly generated base sequence;

[0208] The base sequence of the nucleic acid sample with the added tag sequence is amplified to obtain the nucleic acid sequencing data.

[0209] As an optional implementation, the device further includes a first removal unit, specifically configured to:

[0210] removing bases whose base quality is lower than a first threshold; and / or,

[0211] The nucleic acid sequencing data and the sequencing adapter sequences of the nucleic acid sequencing data whose average base quality is lower than a second threshold are removed.

[0212] As an optional implementation, the device further includes a second removal unit, specifically configured to:

[0213] Remove nucleic acid sequencing data that does not contain primers and / or tag sequences.

[0214] As an optional implementation, the device further includes a third removal unit, specifically configured to:

[0215] The sequence numbers of the nucleic acid sequencing data in the nucleic acid clusters are sorted, and nucleic acid clusters whose sequence numbers are less than the lower quartile are removed.

[0216] As an optional implementation manner, the quality correction unit 602 is specifically used for:

[0217] For the base at each site of the nucleic acid cluster, determining the base quality of the base at the site in the nucleic acid sequencing data contained in the nucleic acid cluster;

[0218] If the consistency of the base quality of the base at the site is greater than a threshold, the base at the site is corrected to a consistent base, where the consistent base represents a base whose consistency of the base quality is greater than the threshold;

[0219] The corrected nucleic acid cluster is determined based on the bases of each corrected site.

[0220] As an optional implementation, the device further includes a cutting correction unit, which is specifically configured to:

[0221] If the consistency of the base quality of the base at the site is less than or equal to the threshold, the base at the site is removed;

[0222] Based on the consistency of the base quality of the bases at other sites after excision, the bases at other sites continue to be corrected.

[0223] As an optional implementation manner, the device further includes a merging unit, specifically configured to:

[0224] Calculating the similarity between the corrected nucleic acid clusters corresponding to different tag sequences;

[0225] When the similarity is greater than a similarity threshold, the corrected nucleic acid clusters corresponding to the different tag sequences are merged to obtain a merged nucleic acid cluster.

[0226] As an optional implementation manner, the clone identification unit 603 is specifically used for:

[0227] The corrected sequencing data are spliced ​​to obtain spliced ​​sequencing data, the spliced ​​sequencing data are compared with the immune data in a preset immune group database, and clone identification is performed on the corrected sequencing data according to the comparison result.

[0228] Based on the same inventive concept, the present disclosure provides a computer storage medium, the computer storage medium comprising: a computer program code, when the computer program code is run on a computer, the computer executes any of the above-mentioned methods for cloning and identifying the rearrangement of immune repertoire genes. Since the principle of solving the problem by the above-mentioned computer storage medium is similar to the method for cloning and identifying the rearrangement of immune repertoire genes, the implementation of the above-mentioned computer storage medium can refer to the implementation of the method, and the repetitions will not be repeated.

[0229] In the specific implementation process, the computer storage medium may include: Universal Serial Bus Flash Drive (USB), mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, and other storage media that can store program codes.

[0230] Based on the same inventive concept, the disclosed embodiment also provides a computer program product, which includes: a computer program code, when the computer program code is run on a computer, the computer executes any of the above-mentioned methods for cloning and identifying the rearrangement of the immune repertoire gene. Since the principle of solving the problem by the above-mentioned computer program product is similar to the method for cloning and identifying the rearrangement of the immune repertoire gene, the implementation of the above-mentioned computer program product can refer to the implementation of the method, and the repetitions will not be repeated.

[0231] The computer program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more conductors, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0232] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0233] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that has the functions specified in one or more boxes.

[0234] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0235] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0236] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for cloning and identifying immune repertoire gene rearrangement, characterized in that: The method includes: Acquiring nucleic acid sequencing data, wherein the nucleic acid sequencing data is generated based on the nucleic acid sample and a tag sequence, wherein the tag sequence is used to distinguish different types of nucleic acid samples; Clustering nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data; According to the consistency of base quality, the bases at each site in the nucleic acid sequencing data contained in each nucleic acid cluster are corrected to obtain a corrected nucleic acid cluster; Corrected sequencing data is determined according to the corrected nucleic acid clusters, and clone identification is performed on the corrected sequencing data to obtain clone identification results of the nucleic acid sequencing data.

2. The method according to claim 1, characterized in that Obtain nucleic acid sequencing data, including: Obtaining a nucleic acid sample, and adding a tag sequence to the primer end of the nucleic acid sample, wherein the tag sequence is determined according to a randomly generated base sequence; The base sequence of the nucleic acid sample with the added tag sequence is amplified to obtain the nucleic acid sequencing data.

3. The method according to claim 1, characterized in that After acquiring the nucleic acid sequencing data, and before clustering the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data, the method further includes: removing bases whose base quality is lower than a first threshold; and / or, The nucleic acid sequencing data and the sequencing adapter sequences of the nucleic acid sequencing data whose average base quality is lower than a second threshold are removed.

4. The method according to claim 1, characterized in that: After acquiring the nucleic acid sequencing data, and before clustering the nucleic acid sequencing data with the same tag sequence into a nucleic acid cluster according to the tag sequence of the nucleic acid sequencing data, the method further includes: Remove nucleic acid sequencing data that does not contain primers and / or tag sequences.

5. The method according to claim 1, characterized in that After clustering the nucleic acid sequencing data of the same tag sequence into one nucleic acid cluster and before obtaining the corrected nucleic acid cluster, the method further includes: The sequence numbers of the nucleic acid sequencing data in the nucleic acid clusters are sorted, and nucleic acid clusters whose sequence numbers are less than the lower quartile are removed.

6. The method according to claim 1, characterized in that The method of correcting the bases at each site in the nucleic acid sequencing data contained in each nucleic acid cluster according to the consistency of the base quality to obtain a corrected nucleic acid cluster includes: For the base at each site of the nucleic acid cluster, determining the base quality of the base at the site in the nucleic acid sequencing data contained in the nucleic acid cluster; If the consistency of the base quality of the base at the site is greater than a threshold, the base at the site is corrected to a consistent base, where the consistent base represents a base whose consistency of the base quality is greater than a threshold; The corrected nucleic acid cluster is determined based on the bases of each corrected site.

7. The method according to claim 6, characterized in that Also includes: If the consistency of the base quality of the base at the site is less than or equal to the threshold, the base at the site is removed; Based on the consistency of the base quality of the bases at other sites after excision, the bases at other sites continue to be corrected.

8. The method according to claim 1, characterized in that After obtaining the corrected nucleic acid clusters and before determining the corrected sequencing data according to the corrected nucleic acid clusters, the method further includes: Calculating the similarity between the corrected nucleic acid clusters corresponding to different tag sequences; When the similarity is greater than a similarity threshold, the corrected nucleic acid clusters corresponding to the different tag sequences are merged to obtain a merged nucleic acid cluster.

9. The method according to claim 1, characterized in that: The step of performing clone identification on the corrected sequencing data comprises: The corrected sequencing data are spliced ​​to obtain spliced ​​sequencing data, the spliced ​​sequencing data are compared with the immune data in a preset immune group database, and clone identification is performed on the corrected sequencing data according to the comparison result.

10. An electronic device, characterized in that: The electronic device comprises a processor and a memory, wherein the memory is used to store a program executable by the processor, and the processor is used to read the program in the memory and execute the steps of any one of the methods of claims 1 to 9.

11. A computer storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

Images