Method for controlling information processor, information processor and computer program

Abstract

To provide means for enabling confirmation on quality of a nucleic acid analysis at a prescribed portion of a base sequence of an analysis object area even if no mutation is detected in the sequence.SOLUTION: An information processor is controlled to: acquire a detection result of mutation at an analysis object area in a sequence of a nucleic acid, based on a plurality of first reads read by a sequencer; generate information on quality of a nucleic acid analysis to a prescribed portion, according to a second read corresponding to at least one prescribed portion selected from the base sequence of the analysis object area among the first reads; and output information on the quality regardless existence of the mutation at the prescribed portion.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to a method for controlling an information processing device that analyzes the sequence of a nucleic acid obtained from a subject's sample, and to an information processing device that analyzes the sequence of a nucleic acid obtained from a subject's sample.The present invention relates to a computer program for analyzing the sequence of a nucleic acid obtained from a subject's sample. [Background technology]

[0002] In recent years, advances in nucleic acid analysis technology using next-generation sequencers (NGS) have made it possible to perform high-throughput targeted sequencing analysis, which analyzes specific regions in the genome. In addition, whole-exome analysis and whole-genome analysis have become feasible at lower costs than before. In whole-exome analysis, the base sequences of all exon regions are analyzed, while in whole-genome analysis, the sequence of the entire genome is analyzed. Nucleic acid analysis technology using NGS is also used in clinical genetic diagnosis, for example, cancer gene panel testing. In cancer gene panel testing, the sequence of nucleic acids obtained from patient samples is analyzed by NGS to detect gene mutations. A report is created on the detected gene mutations, and medical professionals decide on a treatment plan based on the report.

[0003] For example, Non-Patent Document 1 describes an example of an RG sequencing report in which the detected gene mutation is described. The RG sequencing report describes the detected gene mutation and the mutant allele frequency for the gene mutation. The mutant allele frequency is calculated by "mutation depth / total depth". The RG sequencing report also describes the values ​​of mutation depth and total depth together with the mutant allele frequency. When focusing on a specific base on a reference sequence, the mutation depth is the number of reads that are aligned to a portion containing the base and have a mutation at a position corresponding to the base. The total depth is the number of reads that are aligned to a portion containing the base. The total depth can be used to confirm the quality of nucleic acid analysis at the position where the mutation occurred on the sequence. In addition, the RG sequencing report describes the distribution of depth for each gene in the region to be analyzed. [Prior art documents] [Patent documents]

[0004] [Non-Patent Document 1] OncoGuide(TM) NCC Oncopanel System Report User Guide (https: / / products.sysmex.co.jp / products / genetic / AK401170 / report_guide.pdf) Summary of the Invention [Problem to be solved by the invention]

[0005] Medical professionals who decide on a treatment method have expressed a desire to check the quality of nucleic acid analysis, such as depth and quality score, even for positions where no mutations in the base sequence are detected. For example, when no mutations are detected in a gene related to a disease or treatment, there is a desire to check the quality of nucleic acid analysis for that position. The present invention provides a method for controlling an information processing device, an information processing device, and a computer program that make it possible to meet such requests from medical professionals. [Means for solving the problem]

[0006] The present invention provides a method for controlling an information processing device that analyzes the sequence of a nucleic acid obtained from a subject's sample, the method including the steps of: obtaining a detection result of a mutation in an analysis target region in the nucleic acid sequence based on a plurality of first reads read by a sequencer; generating information relating to the quality of nucleic acid analysis for the specific site based on a second read from the first reads that corresponds to at least one specific site selected from the base sequence of the analysis target region; and outputting the information relating to the quality regardless of the presence or absence of a mutation in the specific site.

[0007] The present invention provides an information processing device that analyzes the sequence of a nucleic acid obtained from a subject sample, the information processing device having a control unit and an output unit, wherein the control unit executes the steps of: obtaining detection results of a mutation in an analysis target region in a nucleic acid sequence based on a plurality of first reads read by a sequencer; generating information relating to the quality of nucleic acid analysis for a specific site based on a second read from the first reads that corresponds to at least one specific site selected from the base sequence of the analysis target region; and outputting the quality information to the output unit regardless of the presence or absence of a mutation in the specific site.

[0008] The present invention provides a computer program for analyzing the sequence of a nucleic acid obtained from a subject sample, the computer program being recorded on a computer-readable medium and causing a computer to execute the following steps: obtaining a detection result of a mutation in an analysis target region in the nucleic acid sequence based on a plurality of first reads read by a sequencer; generating information relating to the quality of nucleic acid analysis for the specific site based on a second read from the first reads that corresponds to at least one specific site selected from the base sequence of the analysis target region; and outputting the information relating to the quality regardless of the presence or absence of a mutation in the specific site. Effect of the Invention

[0009] According to the present invention, even if no mutation is detected in the base sequence of the region to be analyzed, the quality of nucleic acid analysis of a specific site in the sequence can be confirmed. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing an example of the configuration of a nucleic acid analysis system. [Figure 2A] FIG. 1 illustrates an example of a configuration of an information processing device. [Figure 2B] FIG. 13 is a diagram showing an example of the configuration of an examination result database. [Figure 2C] FIG. 2 is a diagram illustrating an example of the configuration of a sequencer. [Diagram 3] 1 is a flowchart showing an example of a process for reading the sequence of a nucleic acid obtained from a subject's sample using a sequencer. [Figure 4] 1 is a flowchart showing an example of an analysis process of nucleic acid sequence data by an information processing device. [Diagram 5] 1 is a flowchart illustrating an example of a process for detecting somatic mutations and germline mutations by matched pair testing. [Figure 6A] 1 is a table showing examples of companion diagnostic (CDx) markers approved by the U.S. Food and Drug Administration (FDA). [Figure 6B] 1 is a table showing examples of FDA-approved CDx markers. [Figure 6C] 1 is a table showing examples of FDA-approved CDx markers. [Figure 7A] FIG. 1 shows the relationship between a first read mapped to an analysis target region and a second read corresponding to two predetermined sites each consisting of one base. [Figure 7B] FIG. 1 shows the relationship between a first read mapped to an analysis target region and a second read corresponding to a predetermined site consisting of multiple bases. [Figure 8] 13 is a flowchart showing an example of a process for acquiring information regarding the quality of nucleic acid analysis for a specified site based on each of tumor sequence data and normal sequence data. [Figure 9] FIG. 13 is a diagram showing an example of an inspection result report. [Figure 10] 13 is a flowchart illustrating an example of a process for determining a predetermined part by a user of an information processing device. [Figure 11A] FIG. 13 is a diagram showing an example of a screen for inputting category information and selecting a predetermined part. [Figure 11B] FIG. 13 is a diagram showing an example of a screen for inputting category information and subcategory information and selecting a specific part. [Figure 11C] FIG. 13 is a diagram showing an example of a screen for inputting category information and subcategory information and selecting a specific part. [Figure 11D] FIG. 13 is a diagram showing an example of a screen for a user to arbitrarily select a predetermined part. [Figure 12] 13 is a flowchart illustrating an example of a process for detecting a mutation without a matched pair test. [Figure 13] 13 is a flowchart showing an example of a process for obtaining information regarding the quality of nucleic acid analysis for a specific site based on tumor sequence data. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] (Nucleic Acid Analysis System) First, a nucleic acid analysis system using the information processing device of this embodiment will be described. With reference to FIG. 1, the nucleic acid analysis system 100 includes a data transmission / reception device 40 installed in a requesting facility 200 that requests nucleic acid analysis, and an information processing device 10, a storage 20, and a sequencer 30 installed in a requested facility 300 that performs nucleic acid analysis upon receiving a request from the requesting facility 200. The data transmission / reception device 40 and the information processing device 10 are communicatively connected via a network 400. In the requested facility 300, the information processing device 10, the storage 20, and the sequencer 30 are communicatively connected via an in-facility network. The data transmission / reception device 40 may be composed of, for example, a computer.

[0012] The requesting facility 200 is, for example, a medical facility. A medical facility is a facility where medical personnel such as doctors, nurses, and clinical laboratory technicians perform medical procedures such as sample collection, testing, diagnosis, and treatment on patients and those suspected of having a disease. Examples of medical facilities include hospitals, clinics, and sanatoriums. In the example of FIG. 1, the requesting facility 200 does not have a sequencer installed, so it cannot perform nucleic acid analysis using a sequencer such as a gene panel test. Therefore, the requesting facility 200 requests nucleic acid analysis to the requested facility 300. The request for nucleic acid analysis is made by sending electronic data (e.g., a PDF file) of a request form and / or by sending a request form printed on paper. The requesting facility 200 also sends the subject's sample to the requested facility 300.

[0013] The requested facility 300 is a facility that performs nucleic acid analysis in response to a request from the requesting facility 200 and provides the requesting facility 200 with a test result report that describes the analysis results. The requested facility 300 is, for example, a testing center. Upon receiving the request, the requested facility 300 obtains and analyzes nucleic acid from the sample provided by the requesting facility 200, creates a test result report based on the analysis results, and provides this to the requesting facility 200. The test result report is provided by sending electronic data of the test result report (for example, a PDF file) and / or by sending a paper printed report.

[0014] As shown in FIG. 1, an information processing device 10, a storage 20, and a sequencer 30 of this embodiment are installed in a request destination facility 300. The information processing device 10 of this embodiment will be described later. The storage 20 is a device that stores nucleic acid sequence data read by the sequencer 30. The storage 20 may be, for example, a network attached storage (NAS). The NAS includes, for example, a storage device such as a hard disk drive (HDD) or a solid state drive (SSD), a LAN interface, and a simple OS. The storage 20 may have reference sequence data, which will be described later, stored in advance.

[0015] As used herein, "nucleic acid sequence data" refers to reads obtained from a library sample derived from a subject's specimen. The nucleic acid sequence data includes tumor sequence data and normal sequence data, which will be described later. "Read" refers to the base sequence of an amplicon read by a sequencer. Library samples, amplicons, and reads are described below.

[0016] The sequencer 30 is a device for reading the base sequence of a polynucleotide. In this specification, the term "base sequence" is synonymous with "nucleic acid sequence" and "nucleotide sequence." A base sequence refers to a one-dimensional arrangement (order) of nucleotides in a nucleic acid molecule. Hereinafter, a base sequence may be simply referred to as a "sequence." The sequencer 30 is preferably a next-generation sequencer. The term "next-generation sequencer" is used in contrast to a "first-generation sequencer," which is a sequencer that uses capillary electrophoresis using the Sanger method. A next-generation sequencer can process tens to hundreds of millions of nucleic acid fragments simultaneously in parallel to read the sequence. Next-generation sequencers themselves are known, and examples thereof include HiSeq2500 (Illumina), MiSeq (Illumina), NextSeq (Illumina), Ion Proton (Thermo Fisher Scientific), Ion PGM (Thermo Fisher Scientific), GS FLX+ (Roche), GS Junior (Roche), etc. Data on the base sequence read by the sequencer 30 is stored in the storage 20.

[0017] With reference to FIG. 2C, a configuration example of the sequencer 30 will be described. The sequencer 30 includes a control unit 301, a transmission / reception unit 302, an input unit 303, an output unit 304, a storage unit 305, a flow cell 306, and an imaging unit 307. The control unit 301 includes a processor such as a CPU, and a memory such as a ROM and a RAM. The transmission / reception unit 302 is a communication interface for the control unit 301 to communicate with an external device. The input unit 303 is, for example, a keyboard, a mouse, a touch sensor, etc. The output unit 304 is, for example, a display, a printer, a speaker, etc. A device having both the functions of an input unit and an output unit, such as a touch panel in which a touch sensor and a display are integrated, may be used. The storage unit 305 is, for example, a storage device such as an HDD or SSD. The flow cell 306 includes a glass substrate having a flow path through which a reagent flows, and causes cluster formation and a sequence reaction of polynucleotides contained in a library sample introduced into the flow path. The imaging unit 307 captures an image of the clusters in the flow cell 306, and stores the captured image in the storage unit 305. The control unit 301 analyzes the image stored in the storage unit 305, and determines the base sequence of the polynucleotide.

[0018] A "library" refers to a collection of amplicons (amplified products) whose base sequences are to be analyzed by a sequencer. A "library sample" is a sample containing a library, and is prepared by amplifying nucleic acids obtained from a specimen. In preparing a library sample, first, nucleic acids are extracted from a specimen of a subject. The type of nucleic acid is selected from DNA and RNA depending on the purpose of the analysis. In extracting DNA, the specimen is mixed with a solubilizing solution containing a surfactant (e.g., sodium cholate, sodium dodecyl sulfate, etc.) that solubilizes cells or tissues. The resulting mixture is subjected to physical treatment (stirring, homogenization, ultrasonic disruption, etc.) to liberate the DNA contained in the specimen into the liquid. In extracting RNA, the specimen is mixed with a solubilizing solution containing guanidine thiocyanate and a surfactant. The resulting mixture is subjected to physical treatment to liberate the RNA contained in the specimen into the liquid.

[0019] When the specimen is a formalin-fixed paraffin-embedded (FFPE) tissue, the nucleic acid can be extracted, for example, as follows. First, xylene is added to the FFPE tissue to perform a deparaffinization process. The deparaffinized tissue is immersed in ethanol to perform a hydrophilization process. The hydrophilized tissue is treated with protease to liberate the nucleic acid crosslinked with formalin into the liquid. Preferably, the mixed solution containing DNA or RNA is centrifuged to remove cell debris, and a solution containing the liberated DNA or RNA is obtained. Then, the obtained solution is extracted with phenol / chloroform to purify the DNA or RNA. The extraction and purification of nucleic acid from the specimen may be performed using a commercially available reagent kit.

[0020] In preparing the library sample, it is preferable to fragment the nucleic acid. By fragmentation, the obtained nucleic acid can be made to a length (several tens to several hundreds of bp) suitable for reading by the sequencer 30. The nucleic acid can be fragmented, for example, by ultrasonic treatment. When the nucleic acid is DNA, the fragmentation can also be performed by alkali treatment, restriction enzyme treatment, or the like. For example, when fragmenting DNA by alkali treatment, a sodium hydroxide solution is added to the DNA solution so that the final concentration is 0.1 to 1.0 N, and the DNA is fragmented by incubating at 10 to 40°C for 5 to 15 minutes. When fragmenting DNA by restriction enzyme treatment, the restriction enzyme is appropriately selected based on the base sequence of the DNA, and for example, MseI, BamHI, or the like is used. If necessary, size selection of the nucleic acid fragment, end blunting, ligation of an adapter sequence, ligation of an index sequence, ligation of a barcode sequence, or the like may be performed.

[0021] The fragmented nucleic acid is preferably amplified by a method based on PCR. A library sample can be obtained by designing a primer set capable of amplifying the region to be analyzed and amplifying the nucleic acid by PCR using the primer set. One primer set includes one forward primer and one reverse primer. The nucleic acid containing the region to be analyzed may be enriched from the nucleic acid fragments by a sequence capture method. The enriched nucleic acid can be amplified using a template for PCR to obtain a library sample. Hereinafter, a library sample derived from DNA in a specimen is also referred to as a "DNA library sample".

[0022] Additional sequences such as adapter sequences, index sequences, and barcode sequences, labeling substances, etc. may be added to the primers used for amplification. When multiple primer sets are used, it is preferable that these primer sets are capable of multiplex PCR. This allows multiple regions in the obtained nucleic acid to be amplified simultaneously. In this case, it is preferable that each primer set is added with a barcode sequence that is different from the others. This allows the amplicons produced by each primer set to be identified. A primer set for multiplex PCR provided with a commercially available reagent kit such as an exome sequencing kit may be used.

[0023] The polymerase used for amplification can be appropriately selected from known thermostable polymerases used in PCR, among which a thermostable polymerase suitable for multiplex PCR and with few errors due to PCR amplification is preferable. A buffer suitable for the selected polymerase may be used for the amplification reaction. In order to suppress errors due to PCR amplification, it is preferable to minimize the number of PCR cycles within a range in which the number of amplicons required for sequencing can be obtained. The number of cycles may be determined, for example, from a range of 10 cycles to 25 cycles.

[0024] The base sequence of the library sample obtained as described above can be read by a sequencing method known in the art. The sequencing method is not particularly limited, but analysis by a next-generation sequencer is preferred. Examples of analysis methods by a next-generation sequencer include ion semiconductor sequencing, pyrosequencing, and SBS (sequencing by synthesis).

[0025] The information processing device 10 of this embodiment is a device for analyzing the sequence of a nucleic acid obtained from a specimen of a subject. An example of the configuration of the information processing device 10 will be described with reference to FIG. 2A. The information processing device 10 includes a control unit 101, a transmission / reception unit 102, an input unit 103, an output unit 104, and a storage unit 105. The storage unit 105 stores a reference sequence database 106, a mutation information database 107, an analysis target table 108, a quality index table 109, and an analysis result database 110. Alternatively, the reference sequence database 106, the mutation information database 107, the analysis target table 108, the quality index table 109, and the analysis result database 110 may be stored in the storage 20. Information contained in each database / table will be described later. The information processing device 10 may be configured, for example, by a computer. In this case, the control unit 101 includes a processor such as a CPU, and memories such as a ROM and a RAM. The transmission / reception unit 102 is a communication interface for the control unit 101 to communicate with an external device and a network 400. The input unit 103 is, for example, a keyboard, a mouse, a touch sensor, etc. The output unit 104 is, for example, a display, a printer, a speaker, etc. A device having both the functions of an input unit and an output unit, such as a touch panel in which a touch sensor and a display are integrated, may be used. The storage unit 105 is, for example, a storage device such as an HDD or SSD. A computer program for analyzing a nucleic acid sequence is stored in the storage unit 105. The control unit 101 reads out the computer program from the storage unit 105 and executes a nucleic acid sequence analysis process described later.

[0026] The information contained in the reference sequence database 106 and the mutation information database 107 may be periodically updated to the latest information based on information from an external database. The information may be updated by a vendor providing the nucleic acid analysis system or by a user. Alternatively, the information may be automatically updated by the nucleic acid analysis system. Examples of external databases include databases that accumulate information provided by academic societies and public institutions in various countries (reference sequence information and various information on known gene mutations), and commercial databases provided by vendors.

[0027] A "reference sequence" is a sequence that serves as a reference for determining where on a genome region a read corresponds to a base sequence. The reference sequence may be any sequence that includes the base sequence of the region to be analyzed. Examples of reference sequences include the base sequence of the entire human genome region, the base sequence of the entire exon region, and the base sequence of a target gene.

[0028] "Mutation" and "genetic variation" include mutations and genetic polymorphisms. Mutations include, for example, sequence variations, structural variations, and copy number variations. Sequence variations are substitutions, insertions, deletions, and combinations thereof of one or more nucleotides. Nucleotide substitutions include, for example, single nucleotide variations (SNVs) and single nucleotide polymorphisms (SNPs). Nucleotide insertions and deletions are also called "InDels". Structural variations include, for example, translocations, inversions, deletions, and duplications. Copy number variations include, for example, amplifications and deletions.

[0029] The analysis target table 108 includes information on the analysis target region. The information on the analysis target region is, for example, information on the target gene selected as the analysis target region. The information on the target gene includes, for example, the name of the gene, position information, and base sequence. The position information includes, for example, the chromosome number (Chr), the start point (Pos-Start) and the end point (Pos-End) of the base sequence of the gene on the gene genome sequence. An example of the analysis target table 108 is shown in Table 1, but is not limited to this.

[0030] [Table 1]

[0031] The "region to be analyzed" is a region in which analysis of the base sequence is desired in the nucleic acid obtained from the subject's sample. The region to be analyzed can be arbitrarily determined from the genomic region. Preferably, the region to be analyzed is a part of the genomic region that includes at least one target gene. The region to be analyzed may be the entire genome region or the entire exome region. There may be one or more regions to be analyzed. For example, in gene panel testing, nucleic acid analysis is performed with tens or a hundred or more genes as the region to be analyzed.

[0032] A "target gene" is a gene for which it is desired to determine whether or not there is a mutation. The target gene is not particularly limited and can be appropriately determined depending on the purpose of the test. For example, it can be a gene used in a known gene panel test. The base sequence of the target gene includes the base sequence of the transcriptional regulatory region such as exon, intron, and promoter of the gene, and the sequence of mRNA transcribed from the gene. The mRNA includes pre-mRNA.

[0033] The nucleic acid analysis system 100 can be used, for example, when carrying out a gene panel test. Gene panel tests are not limited to clinical tests, but also include tests for research purposes. For example, a requesting facility 200 transmits request information for nucleic acid analysis such as a gene panel test to a requested facility 300 via a data transmission / reception device 40. The requesting facility 200 also sends a sample from the subject to the requested facility 300.

[0034] The subject is not particularly limited, and examples thereof include patients, individuals suspected of having a disease, and healthy individuals. The disease is not particularly limited, and examples thereof include diseases for which genetic testing and genomic medicine are considered to be useful. Examples of such diseases include cancer, autoimmune diseases, and hereditary diseases. The specimen is not particularly limited, as long as it contains the subject's nucleic acid. Preferably, the specimen is a biological sample collected from the subject. Examples of the biological sample include tissues, cells, body fluids, secretions, urine, and feces. Examples of the body fluid include blood (whole blood), bone marrow fluid, cerebrospinal fluid, lymph, ascites, pleural fluid, amniotic fluid, and synovial fluid. Examples of the secretions include saliva, sweat, tears, nasal secretions, semen, and nipple secretions. The specimen may be a preparation from a biological sample. For example, preparations from blood include plasma and serum. Examples of preparations from cells include a culture (including cultured cells and medium) obtained by culturing collected cells. Preparations from tissues include, for example, frozen tissues, fixed tissues, FFPE tissues, and the like.

[0035] When performing matched pair testing on a subject who is a patient with a solid cancer, two types of samples are used: a tumor sample and a non-tumor sample. The matched pair test is a test that can distinguish and detect somatic mutations and germline mutations based on the results of analyzing the sequences of nucleic acids obtained from the tumor sample and non-tumor sample of a solid cancer patient. The tumor sample can be, for example, tumor tissue collected from the subject by surgery or biopsy and its preparation. The non-tumor sample can be non-tumor cells (e.g., whole blood) collected from the same subject.

[0036] Solid cancer refers to cancer other than blood cancer. The type of solid cancer is not particularly limited, and may be either epithelial cell cancer or non-epithelial cell cancer. Epithelial cell cancer is not particularly limited as long as it occurs in epithelial cells, and examples thereof include lung cancer, breast cancer, stomach cancer, colon cancer, liver cancer, uterine cancer, and ovarian cancer. Examples of non-epithelial cell cancer include osteosarcoma, chondrosarcoma, rhabdomyosarcoma, leiomyosarcoma, fibrosarcoma, liposarcoma, and angiosarcoma.

[0037] The quality index table 109 includes at least position information of the predetermined site in the analysis target region as information on the predetermined site described later. As shown in Fig. 2B, the analysis result database 110 includes, for each test request, a measurement result table including the detection result of a mutation in the analysis target region, a quality information table including information on the quality of nucleic acid analysis for the predetermined site, and a report table including information on the test result report generated from them. Each table is linked to a test request ID that individually identifies the test request.

[0038] The analysis of nucleic acid sequences by the nucleic acid analysis system 100 will be described below. When a person in charge of the requesting facility 200 inputs request information for nucleic acid analysis to the data transmission / reception device 40, the request information is transmitted to the information processing device 10 via the network 400 and received by the information processing device 10. The request information may include, for example, information on the subject and information on the specimen. The subject information includes, for example, age, sex, type and condition of disease. The specimen information includes, for example, type of specimen, collection time, specimen ID that associates the specimen with the subject, and the like. The request information may include designation of an area to be analyzed and / or a predetermined site. In the case of a request for a gene panel test, the request information may include designation of a desired gene panel. The predetermined site will be described later. The person in charge of the requested facility 300 inputs a request for analysis to the sequencer 30 according to the request information received by the information processing device 10.

[0039] 3, the reading of the base sequence by the sequencer 30 will be described. In step S11, the control unit 301 of the sequencer 30 accepts an analysis request. In step S12, the control unit 301 of the sequencer 30 reads the base sequence of the library sample.

[0040] As described above, the base sequence of the amplicon read by the sequencer is the "read". That is, in step S12, the sequencer 30 reads the base sequence of each amplicon of the library sample to obtain a read. The length of the read varies depending on the analysis method, the type of sequencer, etc., but is, for example, 50 bases or more, preferably 100 bases or more, and more preferably 150 bases or more. The length of the read is, for example, 500 bases or less, preferably 350 bases or less, and more preferably 250 bases or less. The number of reads is not particularly limited, and varies depending on the number of copies of the nucleic acid obtained from the sample, the site amplified by the PCR method, etc.

[0041] In step S13, the control unit 301 of the sequencer 30 transmits all the acquired reads to the storage 20. The storage 20 stores the reads. The file format of the reads transmitted from the sequencer 30 is, for example, FASTA, FASTQ, or uBAM. A FASTA file is a file that contains only sequence information of the reads. A FASTQ file is a file that contains sequence information of the reads including a quality score described later. A uBAM file is a binary file that contains sequence information of the reads that are not aligned to the reference sequence. The alignment will be described later. Note that in step S13, the control unit 301 of the sequencer 30 may transmit the acquired reads to the information processing device 10. In this case, the information processing device 10 stores the reads.

[0042] The file sent from the sequencer 30 may include information such as the name of the read (or sequence ID) and the quality score of each base in the sequence, together with the data of the read. The quality score is an index representing the accuracy of the base call (base designation) by the sequencer. Here, the base sequence of the read is determined by performing a base call from trace data (raw data such as waveform data of signals obtained in a sequencing reaction) acquired by the sequencer. In other words, the quality score represents the accuracy of the base sequence determined by the sequencer. The base call is performed by a known base calling program such as Phred. As the quality score, for example, a quality score (Q) output from a sequencer (HiSeq2500, MiSeq, NextSeq, etc.) made by Illumina can be used. The quality score (Q) is calculated by the following formula (I). In the formula, E is an estimate of the probability that the base call is incorrect.

[0043] Q=-10log 10 E (I)

[0044] A quality score is assigned to each base in a read. For example, if a base in a read has a quality score of 20, then the frequency of errors at that base is 10 -2 / base, and when the quality score is 30, the frequency of errors at that base is 10 -3 / base. The average quality score of a read can represent the frequency of errors. The average quality score can be calculated by dividing the sum of the quality scores of each base in the read by the length of the read (number of bases). For example, when the average quality score is 20, there is one error in the read in 100 bases, and when the average quality score is 30, there is one error in the read in 1,000 bases. Thus, the higher the quality score, the lower the probability of errors. The quality score and its average are automatically calculated by the next-generation sequencer.

[0045] When performing a matched pair test in which DNA is the analysis target, DNA library samples are prepared from each of a tumor specimen (e.g., an FFPE specimen of tumor tissue) and a non-tumor specimen (e.g., whole blood). Then, in step S12, the sequencer 30 reads the base sequence of each amplicon in each library sample to obtain reads. Hereinafter, the reads obtained from the DNA library sample derived from the tumor specimen are referred to as "tumor sequence data." Also, the reads obtained from the DNA library sample derived from the non-tumor specimen are referred to as "normal sequence data."

[0046] An example of an analysis process of nucleic acid sequence data by the information processing device 10 will be described with reference to Fig. 4. In step S21, the control unit 101 of the information processing device 10 reads out the reads stored in the storage 20. In step S22, the control unit 101 obtains a detection result of a mutation in the region to be analyzed based on the reads.

[0047] As one embodiment of step S22, a process flow for detecting somatic mutations and germline mutations by matched pair testing will be described. A somatic mutation is a mutation that occurs in a gene in a somatic cell. It is known that a somatic mutation is one of the causes of tumors. With reference to FIG. 5, in step S31, the control unit 101 reads a reference sequence from the reference sequence database 106, and performs alignment between the tumor sequence data read in step S21 and the reference sequence. In addition, in step S32, the control unit 101 performs alignment between normal sequence data and the reference sequence. The result of the alignment between the tumor sequence data and the reference sequence and the result of the alignment between the normal sequence data and the reference sequence are stored in the storage unit 105.

[0048] "Alignment" is a process of determining the corresponding region on a reference sequence for each read. Alignment is also called mapping. The reference sequence may be any base sequence that does not contain somatic mutations. For example, the reference sequence is the base sequence of a wild-type genome. A publicly known alignment tool (software) such as BWA (Burrows-Wheeler Aligner), BWA-MEM, Bowtie, Bowtie2, or BLAST can be used to align the read and the reference sequence.

[0049] Among the reads, the read corresponding to the region to be analyzed is also referred to as the "first read" below. The "read corresponding to the region to be analyzed" refers to a read that is arranged in the base sequence of the region to be analyzed when alignment is performed with a reference sequence including the base sequence of the region to be analyzed. As shown in Figures 7A and 7B described below, multiple first reads are usually mapped to the base sequence of the region to be analyzed. The base sequence of the region to be analyzed is usually longer than the first read. In the figure, the first read is represented by an open bar and a black bar. Note that, among the first reads, the black bar represents the second read described below.

[0050] The control unit 101 may calculate a mapping quality score for each sequence read. The mapping quality score is an index representing the accuracy of mapping of the read. The mapping quality score (Q) is calculated by the following formula (II): P = P ≠ ...

[0051] Q=-10log 10 P (II)

[0052] The higher the mapping quality score of a read, the lower the probability that the read is mapped to a wrong location. Therefore, when a read has a high mapping quality score, the read is more likely to have a base sequence that corresponds to the analyzed region.

[0053] When there is a site in the tumor sequence data that does not match the reference sequence, the site may be a genetic mutation in the tumor tissue or a genetic polymorphism specific to the subject.When there is a site in the normal sequence data that does not match the reference sequence, the site may be a genetic polymorphism specific to the subject or a germline mutation.

[0054] In step S33, the control unit 101 determines whether or not there is a site in the normal sequence data that does not match the reference sequence. As described above, when there is a site that does not match the reference sequence, the site may be a germline mutation or a genetic polymorphism specific to the subject. When the control unit 101 determines that the normal sequence data does not match the reference sequence, the process proceeds to step S34. In step S34, the control unit 101 determines that the site in the normal sequence data detected in step 33 that does not match the reference sequence is a germline mutation. Thereafter, the process proceeds to step S37, which will be described later. On the other hand, when the control unit 101 determines in step S33 that the normal sequence data matches the reference sequence, the process proceeds to step S35. In step S35, the control unit 101 determines whether or not the tumor sequence data corresponding to the site that matches the reference sequence in the normal sequence data detected in step 33 matches the reference sequence. When the tumor sequence data does not match the reference sequence, the site that does not match the reference sequence in the tumor sequence data detected in step S35 is likely to be a mutation found only in the genes of the tumor tissue. A mutation found only in the genes of the tumor tissue is a somatic mutation. Therefore, in step S36, the control unit 101 determines that the site detected in step S35 is a somatic mutation.

[0055] In step S35, if the tumor sequence data matches the reference sequence, the control unit 101 ends the process. In this case, it is considered that the subject has neither somatic mutations nor germline mutations.

[0056] In step S37, the control unit 101 searches the mutation information database 107 based on the detected somatic mutation or germline mutation. The mutation information database 107 stores information for identifying known gene mutations. Such information includes a mutation identifier (mutation ID), a gene name, position information of a mutation (e.g., a chromosome number (Chr) and a base number (Pos) in a genome sequence), REF, ALT, annotation, and the like. The mutation ID is an identifier for identifying a mutation. Among the position information of a mutation, Chr indicates the number of the chromosome where the mutation is located. Pos indicates the base number in a genome sequence. REF indicates a base in a wild type, and ALT indicates a base after a mutation. The annotation indicates information on an amino acid and / or a base that is changed by a mutation. The annotation may be displayed, for example, as "p.A146V" or "c.437C>T". "p.A146V" means that the 146th alanine residue of a protein has been changed to a valine residue by a mutation. "c.437C>T" means that the mutation changed the 437th cytosine to thymine.

[0057] For example, the control unit 101 can search the mutation information database 107 based on the name and location information of the gene in which the detected somatic mutation or germline mutation exists. This makes it possible to determine which of the known gene mutations the detected somatic mutation or germline mutation corresponds to.

[0058] The mutation information database 107 may store not only information for identifying known gene mutations, but also disease information, drug information, and biomarker attribute information associated with the known gene mutations. Examples of disease information include disease names associated with known gene mutations (e.g., colon cancer, lung cancer, breast cancer, etc.), disease types (e.g., cancer, eye disease, neuropsychiatric disease, etc.), information on driver mutations, information on pathogenicity evaluation of mutations (e.g., pathogenic, likely pathogenic, benign, etc.), information on the level of association between mutations and diseases (e.g., evidence level), and type information on the association between mutations and diseases (e.g., oncogenic evidence, disease predisposition-related evidence, predictive evidence of therapeutic effect, diagnostic evidence, prognostic evidence). Examples of drug information include information on the presence or absence of therapeutic drugs associated with known gene mutations, the names of therapeutic drugs, and countries and regions where therapeutic drugs are approved. Examples of biomarker attribute information include the type of biomarker (e.g., companion diagnostic (CDx), malignancy, prognosis, risk of disease, risk of onset, etc.) and marker test information (e.g., name of the disease for which the test is applicable, name of the therapeutic drug, country / region in which the test is approved, etc.).

[0059] In step S38, the control unit 101 annotates the detected somatic mutation or germline mutation based on the search result. Through the processes of steps S31 to S38, the control unit 101 obtains information on the genetic mutation in the analysis target region as a mutation detection result in step S22. Examples of the genetic mutation information include the name of the gene in which the detected mutation occurs (Gene), position information of the mutation (chromosome number (Chr), base number (Pos) of the genome sequence, etc.), amino acid change (AA) in the genetic mutation, coding region change (CDS) in the genetic mutation, information on the type of somatic mutation or germline mutation (Somatic / Germline), type of mutation (Mutation type), etc.

[0060] The control unit 101 stores the mutation detection results obtained by the process of step S22 in a measurement result table of the test result database 110. An example of the measurement result table is shown in Table 2, but is not limited to this. The measurement result table includes all gene mutations detected by the process of step S22. In the table, "Chr" indicates the chromosome number of the detected gene mutation, "Pos" indicates the base number of the genome sequence of the detected gene mutation, "CDS" indicates the coding region change in the detected gene mutation, "AA" indicates the amino acid change in the detected gene mutation, "Somatic / Germline" indicates the type of the detected gene mutation, whether it is a somatic mutation or a germline mutation, and "Mutation type" indicates the type of the detected gene mutation.

[0061] [Table 2]

[0062] The control unit 101 ends the process of acquiring the mutation detection result, and the process proceeds to step S23 in Fig. 4. In step S23, the control unit 101 generates information on the quality of nucleic acid analysis for a predetermined site based on the nucleic acid sequence data.

[0063] The "predetermined site" is at least one site arbitrarily selected from the base sequence of the analysis target region. The predetermined site is selected to examine the quality of nucleic acid analysis and provide information about the quality. The determination of the predetermined site by the control unit 101 will be described later. In the base sequence of the analysis target region, the predetermined site may be one site or multiple sites. In addition, the predetermined site consists of one base or two or more consecutive bases in the base sequence of the analysis target region. That is, the predetermined site may be one base or a region consisting of multiple consecutive bases. When the predetermined site is a region consisting of multiple consecutive bases, its length may be, for example, 2 bases, 3 bases, 4 bases, 5 bases, 6 bases, 7 bases, 8 bases, 9 bases, 10 bases, or 11 bases.

[0064] The predetermined site preferably includes a site where a mutation may occur. The predetermined site may be a site where a mutation may occur, or may be a site where a mutation may occur and its vicinity. For example, when it is known that a substitution or deletion may occur in a certain base, or a base may be inserted, as a known mutation in the region to be analyzed, the predetermined site may be the base itself where the mutation may occur. Alternatively, the predetermined site may be a region of 1 to 5 bases upstream and downstream of the base where the mutation may occur. In this case, the predetermined site may be a region including the base where the mutation may occur. It does not matter whether a mutation has actually occurred in the predetermined site. As a result of the nucleic acid analysis, a mutation may or may not occur in the predetermined site.

[0065] The mutation that may occur at the predetermined site is, for example, a mutation related to the diagnosis or treatment of a disease in the region to be analyzed. Examples of such a mutation include the following mutations (1) to (3).

[0066] (1) Mutations known to be associated with drug efficacy and / or side effects, (2) mutations known to be associated with disease state, onset and / or prognosis; and (3) Mutations with known diagnostic or therapeutic relevance based on a specified level or higher of evidence.

[0067] The mutation described in (1) is, for example, a companion diagnostic marker (CDx marker). As such a marker, for example, a gene mutation used in a gene panel test such as FoundationOne (registered trademark) CDx Cancer Genomic Profile (Chugai Pharmaceutical Co., Ltd.) is known. As such a marker, for example, a driver mutation, a pathogenic mutation, a mutation as a malignancy marker, a mutation as a prognosis prediction marker, a mutation as a morbidity risk marker, or a mutation as a development risk marker is known. As such a marker, for example, a gene mutation used in OncoGuide (trademark) NCC Oncopanel System (Sysmex Corporation) and FoundationOne (registered trademark) CDx Cancer Genomic Profile (Chugai Pharmaceutical Co., Ltd.) is known.

[0068] The evidence level indicates the degree to which the evidence is reliable or recommendable. The evidence levels described in (3) are, for example, the evidence levels of tumorigenicity evidence, disease predisposition-related evidence, treatment effect prediction evidence, diagnostic evidence, or prognostic prediction evidence. Oncogenicity evidence refers to gene mutations that contribute to cell carcinogenesis, such as somatic mutations and germ cell mutations. Disease predisposition-related evidence refers to germ cell mutations related to carcinogenesis in hereditary breast cancer and ovarian cancer. Treatment effect prediction evidence refers to markers related to sensitivity and resistance to drugs and radiation therapy, and genetic mutations of drug metabolizing enzymes and drug transporters that affect pharmacokinetics. Diagnostic evidence is a marker related to the diagnosis of a patient, such as cell morphology, tumor tissue image, and expression and localization of cancer type-specific marker proteins by immunohistochemical staining. Prognostic prediction evidence refers to markers related to cancer progression, severity, survival prognosis, etc. The evidence levels for this evidence have been published by academic organizations such as the Japanese Society of Clinical Oncology, the Japanese Society of Clinical Oncology, the Japanese Cancer Association, the American Society of Clinical Oncology (ASCO), the College of American Pathologists (CAP), the Society for Molecular Pathology (AMP), and the European Society for Medical Oncology (ESMO).

[0069] Mutations relevant to disease diagnosis or treatment may be selected, for example, from FDA approved CDx markers. Specifically, mutations relevant to disease diagnosis or treatment may be selected from the biomarkers listed in the tables shown in Figures 6A-6C. The names and manufacturers of tests or kits corresponding to each biomarker shown in these figures are listed in Table 3.

[0070] [Table 3]

[0071] The predetermined site may be selected from the base sequence of the analysis target region based on the information of the above-mentioned mutation information database 107. Specifically, the control unit 101 reads out information of the analysis target region and information on known genetic mutations from the storage unit 105. The information on known genetic mutations is included in the mutation information database 107. The information on known genetic mutations is, for example, information for identifying the above-mentioned known genetic mutations, disease information, drug information, and biomarker attribute information. The control unit 101 determines the predetermined site based on the read out information and extracts information on the predetermined site. The information on the predetermined site may be stored in the storage unit 105 as information included in the quality index table 109 (see FIG. 2B). The predetermined site may be selected by the control unit 101 according to a predetermined judgment rule or a user's instruction, or may be selected by a designer of a computer program for analyzing the sequence of a nucleic acid stored in the storage unit 105, and the selected predetermined site may be written in advance in the computer program.

[0072] As one embodiment, an example of determining a predetermined site based on attribute information of a biomarker will be described. In this example, the predetermined site is determined based on information of a CDx marker as attribute information of a biomarker. However, the attribute information of a biomarker is not limited to information of a CDx marker. The predetermined site may be determined based on information of other biomarkers related to malignancy, prognosis, morbidity risk, onset risk, and the like. The control unit 101 acquires information of the CDx marker from the mutation information database 107. Next, the control unit 101 extracts the site of the CDx marker from the analysis target region of the analysis target table 108 based on the acquired information. Then, the control unit 101 stores information indicating the position of the extracted site of the CDx marker in the quality index table 109 of the storage unit 105. This allows the control unit 101 to determine the site of the CDx marker in the analysis target region as the predetermined site. An example of the quality index table 109 of this embodiment is shown in Table 4. In the table, "Region" indicates the country and region in which the CDx marker is approved.

[0073] [Table 4]

[0074] As shown in Table 4, quality index table 109 lists, as information about the specific site, the name of the gene containing the specific site (Gene), and location information of the specific site (chromosome number (Chr) where the specific site is located, and base number (Pos) of the genome sequence). As shown in Table 4, quality index table 109 lists, as information about mutations that may occur at the specific site, amino acid changes (AA) in gene mutations. Quality index table 109 shown in Table 4 further lists the type of marker (Marker type), the country and region where the CDx test is approved (Region), and information on the type of disease (cancer) to which the CDx test is applied (Cancer type).

[0075] As a further embodiment, an example of determining a predetermined site based on disease information will be described. In this example, the predetermined site is determined based on a disease name related to a known gene mutation as disease information. More specifically, the predetermined site is determined based on lung cancer. However, the disease information is not limited to lung cancer. The predetermined site may be determined based on information on other diseases or types of diseases. The control unit 101 acquires information on gene mutations related to lung cancer from the mutation information database 107. Next, the control unit 101 extracts one or more bases related to lung cancer from the analysis target area of ​​the analysis target table 108 based on the acquired information. Then, the control unit 101 stores the extracted information on the one or more bases related to lung cancer in the storage unit 105 as a quality index table 109. This allows the control unit 101 to determine the one or more bases related to lung cancer in the analysis target area as the predetermined site.

[0076] An example of determining a predetermined site based on other disease information will be described. In this example, the predetermined site is determined based on information on the level of association between the mutation and the disease as disease information. More specifically, the predetermined site is determined based on the evidence level. However, the disease information is not limited to the evidence level. The predetermined site may be determined based on type information of the association between the mutation and the disease. The control unit 101 acquires information on genetic mutations whose evidence level is equal to or higher than a predetermined level from the mutation information database 107. Next, the control unit 101 extracts one or more bases in which a genetic mutation whose evidence level is equal to or higher than a predetermined level may occur from the analysis target area of ​​the analysis target table 108 based on the acquired information. Then, the control unit 101 stores information on the extracted one or more bases in the storage unit 105 as the quality index table 109. This allows the control unit 101 to determine one or more bases in which a genetic mutation whose evidence level is equal to or higher than a predetermined level may occur in the analysis target area as the predetermined site.

[0077] Further, an example of determining a predetermined site based on other disease information will be described. In this example, the predetermined site is determined based on information on driver mutation as disease information. However, the disease information is not limited to information on driver mutation. The predetermined site may be determined based on information on pathogenicity evaluation of mutation. The control unit 101 acquires information on driver mutation from the mutation information database 107. Next, the control unit 101 extracts one or more bases in which a driver mutation may occur from the analysis target region of the analysis target table 108 based on the acquired information. Then, the control unit 101 stores information on the extracted region in the storage unit 105 as a quality index table 109. Thereby, the control unit 101 can determine one or more bases in which a driver mutation may occur in the analysis target region as the predetermined site.

[0078] An example of the quality index table 109 based on disease information is shown in Table 5. In the table, "Disease type" indicates the type of disease associated with the mutation, "Disease name" indicates the name of the disease associated with the mutation, "Evidence type" indicates type information of the association between the mutation and the disease, and "Evidence level" is information indicating the level of association between the mutation and the disease. As shown in Table 5, the quality index table 109 may include position information of a predetermined site (the chromosome number (Chr) where the predetermined site is located, and the base number (Pos) of the genome sequence) in association with various types of disease information.

[0079] [Table 5]

[0080] As a further embodiment, an example of determining a predetermined site based on drug information will be described. In this example, the predetermined site is determined based on the presence or absence of a therapeutic drug associated with a known genetic mutation as the drug information. However, the drug information is not limited to the presence or absence of a therapeutic drug. The predetermined site may be determined based on information such as the name of the therapeutic drug and the country or region in which the therapeutic drug is approved. The control unit 101 acquires information on the presence or absence of a therapeutic drug associated with a known genetic mutation from the mutation information database 107. Next, the control unit 101 extracts one or more bases in which a genetic mutation known to be associated with a therapeutic drug may occur from the analysis target area of ​​the analysis target table 108 based on the acquired information. Then, the control unit 101 stores information on one or more bases in which a genetic mutation known to be associated with a therapeutic drug may occur in the storage unit 105 as a quality index table 109. As a result, the control unit 101 can determine one or more bases in which a genetic mutation known to be associated with a therapeutic drug may occur in the analysis target area as the predetermined site. An example of the quality index table 109 of this embodiment is shown in Table 6. In the table, "Drug" indicates the approved therapeutic drug, "Region" indicates the country or region where the therapeutic drug is approved, and "Disease name" indicates the type of cancer that the approved therapeutic drug targets. In Table 6, lung cancer is shown as an example of "Disease name."

[0081] [Table 6]

[0082] As shown in Table 6, the quality index table 109 may describe position information of the predetermined site (the chromosome number (Chr) where the predetermined site is located, and the base number (Pos) of the genome sequence) in association with various drug information. Note that in the above embodiment, the chromosome number (Chr) where the predetermined site is located and the base number (Pos) of the genome sequence are used as the position information of the predetermined site, but the present invention is not limited thereto, and any information that identifies the position of the base in the region to be analyzed may be used.

[0083] Regarding step S23 in FIG. 4, the control unit 101 of the information processing device 10 of this embodiment generates information on the quality of nucleic acid analysis for a predetermined site based on a second read corresponding to the predetermined site among the first reads. The control unit 101 generates information on the quality of nucleic acid analysis for the predetermined site for the nucleic acid derived from the subject, regardless of the presence or absence of a mutation at the predetermined site. Hereinafter, the second read corresponding to the predetermined site is also simply referred to as the "second read". With reference to FIGS. 7A and 7B, the relationship between the first read aligned to the analysis target region and the second read corresponding to the predetermined site will be described. In FIG. 7A, two predetermined sites of one base are selected from the base sequence of the analysis target region, as indicated by "X" and "Y" in the reference sequence. In the figure, the first read is indicated by a white bar and a black bar, and is aligned to the analysis target region. As shown in Figure 7A, when the predetermined site is a single base, the second read corresponding to the predetermined site is the first read that contains the base at the same position as the predetermined site in the analysis target region. In the figure, the second read is indicated by a black bar.

[0084] As information on the quality of nucleic acid analysis, for example, depth information at a predetermined site in the region to be analyzed can be generated. "Depth" is the number of reads aligned to a position corresponding to a base on a reference sequence. Depth is also called read depth, and indicates how many times a certain base in the region to be analyzed is read in one measurement. "Depth information" refers to the depth of a base at a predetermined site and / or information obtained from the depth. For example, when the predetermined site is a single base at one or more locations, the depth information can be the depth of each base. That is, the depth of the predetermined site is the number of second reads aligned to each base at the predetermined site. When the predetermined site is a region consisting of multiple bases, the depth information is the depth of each base included in the predetermined site and / or a statistical representative value of those depths. Examples of statistical representative values ​​of depth include the average value, mode, median, minimum value, and maximum value of the depth. The depth information is one of the pieces of information on the quality of nucleic acid analysis. In FIG. 7A, depth A and depth B are obtained as depth information for each base X and Y at a predetermined site, respectively.

[0085] In FIG. 7B, a region from "X" to "Y" in the reference sequence is selected as the predetermined site. As in FIG. 7A, the first read is indicated by an open bar and a black bar, and is aligned to the region to be analyzed. The second read is indicated by a black bar. As shown in FIG. 7B, when the predetermined site consists of multiple consecutive bases, the second read corresponding to the predetermined site is a first read that includes bases corresponding to part or all of the predetermined site. In FIG. 7B, a depth C can be obtained as depth information for the predetermined site (base sequence from X to Y).

[0086] As an embodiment of step S23, a process flow for acquiring depth information of a predetermined site based on each of tumor sequence data and normal sequence data will be described. Hereinafter, the depth information acquired based on the tumor sequence data will be referred to as "depth information T". Also, the depth information acquired based on the normal sequence data will be referred to as "depth information N". With reference to FIG. 8, in step S41, the control unit 101 reads out the result of the alignment between the tumor sequence data and the reference sequence executed in step S31 from the storage unit 105. In step S42, the control unit 101 refers to the result of the alignment between the tumor sequence data and the reference sequence, and acquires the depth information T based on the number of second reads, which are first reads corresponding to the predetermined site of the analysis target region. In step S43, the control unit 101 reads out the result of the alignment between the normal sequence data and the reference sequence executed in step S32 from the storage unit 105. In step S44, the control unit 101 refers to the result of the alignment between the normal sequence data and the reference sequence, and acquires depth information N based on the number of second reads, which are first reads corresponding to the predetermined site in the analysis target region. If there are multiple predetermined sites, depth information T and N are acquired for each predetermined site. In step S45, the control unit 101 stores the depth information T and N for the predetermined sites in the quality information table of the test result database 110 in the storage unit 105. Then, the control unit 101 ends the process of generating information regarding the quality of nucleic acid analysis for the predetermined sites, and the process proceeds to step S24 in FIG. 4.

[0087] In addition, in acquiring the depth information T in step S42, the mapping data can be used to refer to the result of alignment between the tumor sequence data and the reference sequence. Similarly, in acquiring the depth information N in step S44, the mapping data can be used to refer to the result of alignment between the normal sequence data and the reference sequence. The mapping data is information on the read including the result of aligning the read to the reference sequence. In addition, in the case where the result of alignment between the tumor sequence data and the normal sequence data and the reference sequence is not referred to in steps S42 and S44, the control unit 101 may read the tumor sequence data and the reference sequence in step S41, and execute alignment between the tumor sequence data and the reference sequence in step S42. Furthermore, the normal sequence data and the reference sequence may be read in step S43, and execute alignment between the normal sequence data and the reference sequence in step S44.

[0088] Table 7 shows an example of the quality information table, but is not limited thereto. In the table, each piece of information corresponding to "Chr", "Gene", "Pos", and "AA" is information transcribed from the quality index table 109, and is information about a specific site. "depth T" is depth information T, and "depth N" is depth information N. In the example of Table 7, the depth information T and the depth information N each describe the average value of the depth of three specific sites, but are not limited thereto. For example, the depth information T and the depth information N may each be the maximum value, the intermediate value, or the minimum value of a plurality of specific sites. The depth information T and the depth information N may each be the depth information T and the depth information N for each specific site. The "detection result of mutation" is information indicating whether or not each specific site has been determined to be a germ cell mutation or a somatic mutation by the process of step S33 or S35. For example, it is indicated that a mutation exists in the second specific site in Table 7, and that no mutation exists in the third and fourth specific sites. The "mutation detection result" can be determined based on whether or not a mutation at a specified site included in the quality information table is included in the measurement result table. As shown in Table 7, the quality information table includes depth information T and depth information N regardless of whether the mutation detection result at the specified site is YES or NO, i.e., regardless of the presence or absence of a mutation at the specified site. Depth information T and depth information N are examples of information regarding the quality of nucleic acid analysis for the specified site. Note that the "mutation detection result" may be omitted from the quality information table.

[0089] [Table 7]

[0090] Examples of information regarding the quality of nucleic acid analysis for a predetermined site include the information described in (1) to (4) below.

[0091] (1) Information regarding the number and / or length of second leads; (2) Information about the accuracy of the sequencer's reading of the base sequence, which is provided for each base in the second read; (3) information on the accuracy of mapping, which is assigned to each base of the second read in the alignment of the first read to the reference sequence; and (4) The result of a quality assessment based on at least one of the information set forth in (1) to (3) above.

[0092] Among the information described in (1), the information on the number of second leads is, for example, depth information of a predetermined site. The depth information is as described above. The information on the length of the second leads is, for example, the average value, mode, median, minimum value, maximum value, etc. of the length of the second leads.

[0093] The information described in (2) is, for example, an index value indicating the accuracy of the base call, which is assigned to each base of the second read. Examples of such index values ​​include the above-mentioned quality scores. The quality scores assigned to each base of the second read may be used as is as the information described in (2). Alternatively, a statistical representative value of the quality scores assigned to each base of the second read (such as the average, mode, median, minimum, and maximum of each quality score) may be used as the information described in (2).

[0094] The information described in (3) is, for example, an index value indicating the accuracy of mapping given to the second read. Examples of such index values ​​include the above-mentioned mapping quality score. The information described in (1) to (3) indicates the quality of nucleic acid analysis for a short region corresponding to a predetermined site consisting of a single base or the single base and its vicinity. Therefore, for example, the depth information described in (1) indicates the quality of nucleic acid analysis at a predetermined site with higher accuracy compared to a statistical representative value of the depth for the entire length of one gene.

[0095] The judgment described in (4) may be performed, for example, by comparing any value selected from the information described in (1) to (3) above with a threshold value. For example, when the depth of a predetermined site is equal to or greater than the corresponding threshold value, the quality of the nucleic acid analysis may be judged to be good. Also, when the depth of a predetermined site is less than the corresponding threshold value, the quality of the nucleic acid analysis may be judged to be poor. The judgment result may be displayed using symbols, numbers, letters, or the like. For example, when the quality of the nucleic acid analysis is judged to be good, a check mark may be displayed in the judgment result column, and when the quality of the nucleic acid analysis is judged to be poor, the judgment result may be left blank.

[0096] 4, in step S24, the control unit 101 outputs a test result report including the mutation detection result obtained in step S22 and information on the quality of the nucleic acid analysis for the predetermined site obtained in step S23 to the output unit 104. The control unit 101 may output the test result report to the data transmission / reception device 40 via the network 400.

[0097] FIG. 9 shows an example of a test result report. The test result report R includes an area R1 in which test request information is described, an area R2 in which a mutation detection result is described, and an area R3 in which information on the quality of nucleic acid analysis for a predetermined site is described. The area R1 describes the request information transmitted from the requesting facility, such as a test request ID and subject information. The area R2 describes the mutation detection result acquired in step S22 and stored in the measurement result table of the storage unit 105. The area R3 describes information on the quality of nucleic acid analysis for a predetermined site acquired in step S23 and stored in the quality information table of the storage unit 105. In the example of FIG. 9, the area R3 further describes the result of judging the quality of the nucleic acid analysis. In the table of FIG. 9, "judgment result T" indicates the result of judging the quality of the nucleic acid analysis based on the value of Depth T and the threshold value, and "judgment result N" indicates the result of judging the quality of the nucleic acid analysis based on the value of Depth N and the threshold value.

[0098] As shown in FIG. 9, the region R3 of the test result report output from the information processing device 10 describes information on the quality of the nucleic acid analysis, regardless of the presence or absence of a mutation at the predetermined site. This allows the person in charge at the requesting facility 200 and / or the requested facility 300 to confirm the quality of the nucleic acid at the predetermined site even if no mutation is detected at the predetermined site in the analysis target region of the subject's nucleic acid. For example, for the second predetermined site in the region R3 (position 29,432,664 of chromosome 2), the mutation detection result is "NO", and a check mark is displayed in the column of the determination result T of Depth T. This suggests that no mutation is detected at the predetermined site in this test, and that the result is based on an analysis of sufficient quality. In other words, it suggests that the mutation detection result is a true negative. Furthermore, for the third predetermined site in the region R3 (position 29,432,682 of chromosome 2), the mutation detection result is "NO", and the determination result T of Depth T is left blank. This suggests that although the test did not detect a mutation at the specific site, the subject's nucleic acid may actually have a mutation. In other words, the mutation detection result is suspected to be a false negative. In this case, it becomes possible to specifically consider the next action that medical personnel should take, such as conducting a gene panel test again or conducting another test focused on the genetic marker corresponding to the specific site. If a mutation is detected in the retest, it becomes possible to lead to an appropriate diagnosis or treatment.

[0099] In this embodiment, the mutation detection result and the information on the quality of the nucleic acid analysis for the specified site are described in the same report, but the mutation detection result and the information on the quality of the nucleic acid analysis for the specified site may be generated as separate reports. For example, an analysis result report for reporting the mutation detection result and a quality control report for reporting the information on the quality of the nucleic acid analysis for the specified site may be generated separately.

[0100] The test result report may further include other quality information, such as quality information provided in conventional genomic medical tests, which is obtained based on the entire nucleic acid sequence data of the analysis target region.

[0101] Other quality information includes, for example, the total number of reads obtained, the mapping rate, the overlap rate, the homogeneity, the statistical representative value of the depth of the region to be analyzed, the frequency distribution of the depth frequency of the region to be analyzed, the frequency distribution of the average quality score of the reads, and the frequency distribution of the read length. "Mapping rate" refers to the ratio of the number of reads mapped to the region to be analyzed out of the total reads. "Overlap rate" refers to the ratio of the number of reads that originate from the same amplified region out of the reads mapped to the region to be analyzed. "Homogeneity" refers to the ratio of the region to be analyzed in which the number of mapped reads is equal to or greater than a predetermined value. "Frequency distribution of depth frequency" refers to a histogram in which the number of reads mapped to each base in the region to be analyzed is tallied and the position of the base and the depth to that base are plotted on two axes. "Frequency distribution of average quality score of reads" refers to a histogram in which the average quality score of each read and the number of reads showing that average value are plotted on two axes. "Frequency distribution of read length" refers to a histogram in which the length of the read (number of bases) and the number of reads having that length are plotted on two axes.

[0102] If the mutations detected in step S22 include a mutation detected at a site not listed in the quality information table, the test result report may further include information regarding the quality of the nucleic acid analysis for that site (e.g., depth information).

[0103] 4, in step S25, control unit 101 stores the examination result report in a report table in storage unit 105.

[0104] (User determines designated area) In a further embodiment, the user can determine the predetermined site. The user may be a user of the information processing device 10 at the requested facility 300 for the test. The user of the information processing device 10 may be, for example, an inspector at the requested facility 300. In this embodiment, the predetermined site is determined based on information input by the user. Hereinafter, an example of determining the predetermined site by the user of the information processing device 10 and analyzing the lead will be described with reference to FIG. 10. In this embodiment, the quality index table 109 of the storage unit 105 stores, for example, a quality index table that integrates each quality index table shown in Tables 4 to 6. In step S51, the control unit 101 refers to the quality index table 109 based on information input by the user by operating the input unit 103, and selects the predetermined site. The user may input information via a screen displayed on the output unit 104 such as a display or a touch panel. Details of steps S52 to S56 are the same as those described for steps S21 to S25 in FIG. 4. The user is not particularly limited. For example, the user may be a user of the data transmission / reception device 40 at the facility 200 requesting the test. The user of the data transmission / reception device 40 may be, for example, a medical professional such as a doctor in charge of the subject. The input operation for determining the predetermined site is the same regardless of the user at any facility. If the user is a user of the data transmission / reception device 40, in step S51, the control unit 101 receives, via the network 400, information that the user input via the screen displayed on the data transmission / reception device 40.

[0105] With reference to FIG. 11A, an example of selecting a specific site by inputting category information on screen D1 will be described. In D11 of screen D1, attribute information of a biomarker is displayed as category information in a selectable manner. Category information is input, for example, by selecting attribute information of a biomarker from a pull-down menu. When category information is input in D11, control unit 101 reads out information on the specific site corresponding to the category information from storage unit 105. Then, in D12, information on the read out specific site is displayed. When a user selects one or more specific sites displayed in D12 by clicking or the like, and clicks a setting button in D13, information on the selected specific site is stored in storage unit 105. When a user is a user of data transmission / reception device 40 of requesting facility 200, information on the selected specific site is transmitted to information processing device 10 via network 400 together with request information.

[0106] With reference to FIG. 11B, an example of selecting a predetermined site by inputting category information and subcategory information on screen D2 will be described. In D21 of screen D2, CDx marker is selected as category information. In this case, in D22, information on a country or region where the CDx marker is approved is displayed as subcategory information in a selectable manner. When the category information and subcategory information are input, the control unit 101 reads out information on the predetermined site corresponding to the information from the storage unit 105, and the read-out information on the predetermined site is displayed in D23. When the user selects one or more predetermined sites displayed in D23 by clicking or the like, and clicks a setting button in D24, the information on the selected predetermined site is stored in the storage unit 105. This allows a CDx marker approved in a predetermined country or region to be set as a predetermined site from the analysis target region. The subcategory information may be a disease name or a therapeutic drug name to which the CDx test is applied, in addition to a country or region.

[0107] The category information may be other than the attribute information of the biomarker. Referring to FIG. 11C, in D31 of the screen D3, not only the attribute information of the biomarker but also disease information, drug information, and the like are displayed as selectable category information. In D31 of the screen D3, the evidence level is selected as the category information. In this case, in D32, the classification of the evidence level (for example, Lv A, Lv B, and Lv C) is displayed as selectable subcategory information. When the category information and subcategory information are input, the control unit 101 reads out information on the predetermined site corresponding to the information from the storage unit 105, and the read-out information on the predetermined site is displayed in D33. When the user selects one or more predetermined sites displayed in D33 by clicking or the like and clicks the setting button in D34, the information on the selected predetermined site is stored in the storage unit 105.

[0108] The user may determine the predetermined site by inputting an arbitrary region from the region to be analyzed. Referring to FIG. 11D, in D41 of screen D4, "arbitrary selection" is selected as category information. In this case, in D42, a text box for inputting position information such as a chromosome number (Chr) and base numbers (Pos_Start and Pos_End) on the genome sequence is displayed. The user inputs position information of a desired single base or multiple bases as the predetermined site from the base sequence of the region to be analyzed in the text box. After inputting the position information, the user clicks a setting button in D43, and the input information of the predetermined site is stored in the storage unit 105.

[0109] (Detection of somatic mutations without matched-pair testing) As a further embodiment of step S22 in FIG. 4, a process flow for detecting a mutation without a matched pair test will be described. In this case, a non-tumor specimen is not used, and a read obtained from a library sample prepared from a tumor specimen is used as tumor sequence data. With reference to FIG. 12, in step S61, the control unit 101 reads a reference sequence from the reference sequence database 106 and performs alignment between the tumor sequence data and the reference sequence. In step S62, the control unit 101 determines whether or not there is a site in the tumor sequence data that does not match the reference sequence. When the control unit 101 determines that the tumor sequence data does not match the reference sequence, the process proceeds to step S63. In the process of FIG. 12, if there is a site that does not match the reference sequence, it is determined that the site is a mutation found in a gene of the tumor tissue. In step S62, if the tumor sequence data matches the reference sequence, the control unit 101 ends the process. In this case, it is considered that there is no mutation in the tumor sequence data.

[0110] In step S63, the control unit 101 searches the mutation information database 107 based on the detected mutation. In step S64, the control unit 101 annotates the detected mutation based on the search result. Details of steps S63 and S64 are the same as those described for steps S37 and S38 in Fig. 5. Through the processing of steps S61 to S64, the control unit 101 obtains information on gene mutations in the analysis target region as a mutation detection result in step S22.

[0111] As a further embodiment of step S23 in FIG. 4, a process flow for acquiring depth information T of a predetermined site based on tumor sequence data will be described. Referring to FIG. 13, in step S71, the control unit 101 reads out the alignment result between the tumor sequence data acquired in step S61 and the reference sequence. In step S72, the control unit 101 refers to the alignment result between the tumor sequence data and the reference sequence, and acquires depth information T based on the number of second reads that are the first reads corresponding to the predetermined site in the analysis target region. As the depth information T, the depth for each base of the predetermined site is preferable. In step S73, the control unit 101 stores the depth information T at the predetermined site in the storage unit 105. Then, the control unit 101 ends the process for acquiring depth information of the predetermined site, and the process proceeds to step S24 in FIG. 4. [Explanation of symbols]

[0112] 10. Information processing device 20. Storage 30 Sequencer 40 Data transmission and reception device 100 Nucleic Acid Analysis System 110 Analysis Results Database 200 Requesting Facility 300 Requested Facility 400 Network

Claims

1. A method for controlling an information processing device that analyzes a sequence of a nucleic acid obtained from a sample of a subject, comprising: Obtaining a detection result of a mutation in a region to be analyzed in the sequence of the nucleic acid based on a plurality of first reads read by a sequencer; generating information on the quality of nucleic acid analysis for at least one predetermined site selected from the base sequence of the analysis target region based on a second read corresponding to the at least one predetermined site selected from the base sequence of the analysis target region among the first reads; outputting information regarding the quality regardless of the presence or absence of a mutation at the predetermined site; A method comprising:

2. The method according to claim 1 , further comprising the step of outputting a result of detection of a mutation in the region to be analyzed.

3. The method of claim 1 , further comprising accepting a selection of the predetermined portion from the region to be analyzed.

4. The method according to claim 3 , wherein, in the step of accepting the selection, an input of information regarding the predetermined region is accepted, and the predetermined region is set based on the input information.

5. The method according to claim 1 , further comprising generating information about the quality for each of a plurality of the predetermined sites selected from the base sequence of the region to be analyzed.

6. The method according to claim 1 , wherein the predetermined site consists of one base or two or more consecutive bases in the base sequence of the region to be analyzed.

7. The method of claim 1 , wherein the predetermined site comprises a site where a mutation may occur.

8. The method according to claim 7 , wherein the mutation that may occur at the predetermined site is a mutation related to the diagnosis or treatment of a disease in the region to be analyzed.

9. A mutation relevant to the diagnosis or treatment of the disease, (1) Mutations known to be associated with drug efficacy and / or side effects, (2) mutations known to be associated with disease state, onset and / or prognosis; and (3) A mutation with a known relevance to diagnosis or treatment with a certain level or higher of evidence The method according to claim 8, wherein the at least one of

10. The method according to claim 9, wherein the mutation described in (1) is a companion diagnostic marker.

11. The method according to claim 9, wherein the mutation described in (2) is at least one selected from the group consisting of a driver mutation, a pathogenic mutation, a mutation as a malignancy marker, a mutation as a prognosis prediction marker, a mutation as a morbidity risk marker, or a mutation as a development risk marker.

12. The method according to claim 9, wherein the evidence level described in (3) is at least one evidence level selected from the group consisting of tumorigenicity evidence, disease predisposition-related evidence, therapeutic effect prediction evidence, diagnostic evidence, or prognostic prediction evidence.

13. The method according to claim 8, wherein the mutation associated with the diagnosis or treatment of the disease is at least one selected from the biomarkers listed in the tables shown in Figures 6A to 6C.

14. The method according to claim 1 , wherein the predetermined site is a site selected from the base sequence of the region to be analyzed based on information from a mutation information database in which information on known gene mutations is accumulated.

15. The information regarding the quality is (1) information regarding the number and / or length of the second leads; (2) information about the accuracy of the reading of the base sequence by the sequencer, which is assigned to each base of the second read; (3) information on the accuracy of the mapping, which is assigned to each base of the second read in the alignment of the first read to a reference sequence; and (4) The result of judging the quality based on at least one of the information described in (1) to (3) above. The method according to claim 1, wherein the at least one selected from the group consisting of:

16. The method according to claim 15, wherein the information described in (1) is at least one selected from depth information of the specified region and an average length of the second read.

17. The method according to claim 15, wherein the information described in (2) is an index value indicating the accuracy of a base call, which is assigned to each base of the second read.

18. The method according to claim 15, wherein the information described in (3) is an index value indicating the accuracy of mapping assigned to the second read.

19. The method according to claim 1 , wherein the information regarding the quality is output in association with the information regarding the predetermined portion.

20. The method according to claim 1 , wherein the step of outputting information regarding quality comprises generating and outputting a quality control report including information regarding the quality of nucleic acid analysis for the predetermined site.

21. The method according to claim 2 , wherein in the step of outputting the information relating to the quality, an analysis result report including a detection result of a mutation in the region to be analyzed is generated and output.

22. The method of claim 1 , wherein the region to be analyzed is a whole genome region, a whole exome region, or a portion of a genome region that includes at least one target gene.

23. The method according to claim 1, wherein the nucleic acid obtained from the subject's sample is DNA or RNA.

24. An information processing device that analyzes a sequence of a nucleic acid obtained from a sample of a subject, The information processing device includes a control unit and an output unit, The control unit is Obtaining a detection result of a mutation in a region to be analyzed in the sequence of the nucleic acid based on a plurality of first reads read by a sequencer; generating information on the quality of nucleic acid analysis for at least one predetermined site selected from the base sequence of the analysis target region based on a second read corresponding to the at least one predetermined site selected from the base sequence of the analysis target region among the first reads; outputting information about the quality to the output unit regardless of the presence or absence of a mutation at the predetermined site; An information processing device that executes the above.

25. A computer program for analyzing a sequence of a nucleic acid obtained from a subject's sample, comprising: The computer program is recorded on a computer-readable medium, and the computer Obtaining a detection result of a mutation in a region to be analyzed in the sequence of the nucleic acid based on a plurality of first reads read by a sequencer; generating information on the quality of nucleic acid analysis for at least one predetermined site selected from the base sequence of the analysis target region based on a second read corresponding to the at least one predetermined site selected from the base sequence of the analysis target region among the first reads; outputting information regarding the quality regardless of the presence or absence of a mutation at the predetermined site; A computer program that executes the following:

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