Method for controlling information processing apparatus, information processing apparatus, and computer program

Abstract

The invention discloses a method for controlling an information processing apparatus, an information processing apparatus, and a computer program. The present invention addresses the problem of providing a means for confirming the quality of nucleic acid analysis in a predetermined site of a nucleotide sequence in a region to be analyzed, even if no variation is detected in the nucleotide sequence. The information processing device is controlled so as to acquire a detection result of a variation in the region to be analyzed in the sequence of the nucleic acid on the basis of a plurality of first read lengths read by the sequencer, and to determine the variation in the region to be analyzed on the basis of a second read length corresponding to at least one predetermined site selected from the base sequence of the region to be analyzed among the first read lengths. The present invention addresses the problem by generating information relating to the quality of nucleic acid analysis for a predetermined site, and outputting information relating to the quality regardless of whether or not there is a variation in the predetermined site.

Description

Technical Field

[0001] The present invention relates to a method for controlling an information processing device that analyzes the sequence of nucleic acids obtained from a specimen of a subject. The present invention relates to an information processing device that analyzes the sequence of nucleic acids obtained from a specimen of a subject. The present invention relates to a computer program for analyzing the sequence of nucleic acids obtained from a specimen of a subject. Background Art

[0002] In recent years, due to the progress of nucleic acid analysis technology based on next-generation sequencers (NGS), it has become possible to perform targeted sequence analysis of a predetermined region in the genome with high throughput. In addition, whole exome analysis and whole genome analysis can also be achieved at a lower cost than before. In whole exome analysis, the base sequences of all exon regions are analyzed, and in whole genome analysis, the sequences of the entire genome are analyzed. Nucleic acid analysis technology based on NGS is also used in genetic diagnosis in clinical practice. For example, cancer gene panel testing is known. In cancer gene panel testing, NGS is used to analyze the sequence of nucleic acids obtained from a patient's specimen to detect genetic mutations. A report is made on the detected genetic mutations, and based on this report, medical staff determine the treatment strategy.

[0003] For example, Non-Patent Document 1 describes an example of an RG sequencing report that records detected genetic mutations. In the RG sequencing report, together with the detected genetic mutations, the mutation allele frequency for the genetic mutation is recorded. The mutation allele frequency is calculated by "mutation depth / total depth". In the RG sequencing report, the values of the mutation depth and the total depth are also recorded together with the mutation allele frequency. The mutation depth refers to the number of reads that are aligned to the portion containing a predetermined base on the reference sequence and have a mutation at the position corresponding to the base. The total depth is the number of reads that are aligned to the portion containing the base. The total depth can be used to confirm the quality of nucleic acid analysis at the position where a sequence mutation occurs. In addition, in the RG sequencing report, the depth distribution of each gene in the analysis target region is recorded.

[0004] Prior Art Documents

[0005] Patent Documents

[0006] Non-Patent Document 1: OncoGuide (trademark) NCC Oncology Panel System Report Utilization Guide (https: / / products.sysmex.co.jp / products / genetic / AK401170 / report_guide.pdf) Summary of the Invention

[0007] Medical personnel who decide on treatment methods have expressed a desire to confirm the quality of nucleic acid analysis such as depth and quality score for positions on base sequences where no mutations have been detected. For example, when no mutations have been detected in a genetic gene associated with a disease or treatment, there is a desire to confirm 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 can respond to such a desire from medical personnel.

[0008] The present invention provides a method for controlling an information processing device for analyzing the sequence of a nucleic acid obtained from a specimen of a subject, comprising: a process for obtaining a detection result of a variation in an analysis target region in the sequence of the nucleic acid based on multiple first reads read using a sequencer; a process for generating information related to the quality of the nucleic acid analysis for a predetermined region based on a second read in the first read corresponding to at least one predetermined region selected from a base sequence of the analysis target region; and a process for outputting information related to the quality regardless of whether a variation exists in the predetermined region.

[0009] The present invention provides an information processing device for analyzing the sequence of a nucleic acid obtained from a sample of a subject, wherein the information processing device includes a control unit and an output unit, and the control unit executes: a process of obtaining a detection result of a variation in an analysis target region in the sequence of the nucleic acid based on multiple first reads read using a sequencer; a process of generating information related to the quality of the nucleic acid analysis for a predetermined position based on a second read in the first read corresponding to at least one predetermined position selected from the base sequence of the analysis target region; and a process of outputting the information related to the quality to the output unit regardless of whether there is a variation in the predetermined position.

[0010] The present invention provides a computer program for analyzing the sequence of a nucleic acid obtained from a subject's specimen, wherein the computer program is recorded on a computer-readable medium and causes the computer to execute: a process of obtaining a detection result of a variation in an analysis target region in the sequence of the nucleic acid based on multiple first reads read using a sequencer; a process of generating information related to the quality of the nucleic acid analysis for a predetermined position based on a second read in the first read corresponding to at least one predetermined position selected from the base sequence of the analysis target region; and a process of outputting information related to the quality regardless of whether a variation exists in the predetermined position.

[0011] According to the present invention, even when no mutation is detected in the base sequence of the analysis target region, the quality of nucleic acid analysis at a predetermined portion of the sequence can be confirmed. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a diagram showing an example of the configuration of a nucleic acid analysis system.

[0013] Figure 2A It is a diagram showing an example of the configuration of an information processing device.

[0014] Figure 2B It is a diagram showing an example of the structure of the inspection result database.

[0015] Figure 2C is a diagram showing an example of the structure of a sequencer.

[0016] Figure 3 This is a flowchart showing an example of a process of reading a sequence of a nucleic acid obtained from a sample of a subject using a sequencer.

[0017] Figure 4 This is a flowchart showing an example of analysis processing of nucleic acid sequence data using an information processing device.

[0018] Figure 5 is a flowchart showing an example of a process for detecting somatic cell mutations and germ cell mutations by matched pair testing.

[0019] Fig. 6A is a table showing examples of companion diagnostic (CDx) markers approved by the U.S. Food and Drug Administration (FDA).

[0020] Figure 6B is a table showing examples of CDx markers approved by the FDA.

[0021] Figure 6C is a table showing examples of CDx markers approved by the FDA.

[0022] Fig. 7A This is a diagram showing the relationship between the first read mapped to the analysis target region and the second read corresponding to a predetermined site (two locations) consisting of one base.

[0023] Figure 7B This is a diagram showing the relationship between a first read mapped to an analysis target region and a second read corresponding to a predetermined site composed of a plurality of bases.

[0024] Figure 8 This is a flowchart showing an example of processing for acquiring information on the quality of nucleic acid analysis at a predetermined site for each of tumor sequence data and normal sequence data.

[0025] Fig. 9 It is a figure which shows an example of an inspection result report.

[0026] Fig.10 This is a flowchart showing an example of a process in which a user of the information processing device determines a predetermined part.

[0027] Fig.11A It is a diagram showing an example of a screen for inputting classification information and selecting a predetermined part.

[0028] Fig. 11B 1 is a diagram showing an example of a screen for inputting classification information and sub-classification information to select a predetermined part.

[0029] Fig. 11C 1 is a diagram showing an example of a screen for inputting classification information and sub-classification information to select a predetermined part.

[0030] Fig.11D It is a diagram showing an example of a screen for a user to arbitrarily select a predetermined part.

[0031] Fig.12 is a flowchart showing an example of a process for detecting mutations without a matching pair check.

[0032] Fig.13 This is a flowchart showing an example of processing for acquiring information on the quality of nucleic acid analysis for a predetermined site based on tumor sequence data.

[0033] (Explanation of symbols)

[0034] 10: information processing device; 20: storage device; 30: sequencer; 40: data transmission and reception device; 100: nucleic acid analysis system; 110: analysis result database; 200: source facility; 300: destination facility; 400: network. DETAILED DESCRIPTION

[0035] (Nucleic acid analysis system)

[0036] First, a nucleic acid analysis system using the information processing device of this embodiment is described. Figure 1 The nucleic acid analysis system 100 includes a data transmission and reception device 40 provided in a source facility 200 for entrusting nucleic acid analysis, an information processing device 10, a storage device 20, and a sequencer 30 provided in a destination facility 300 for entrusting nucleic acid analysis in response to an entrustment from the source facility 200. The data transmission and reception device 40 and the information processing device 10 are communicatively connected via a network 400. In the destination facility 300, the information processing device 10, the storage device 20, and the sequencer 30 are communicatively connected via a network within the facility. The data transmission and reception device 40 may be composed of, for example, a computer.

[0037] The source facility 200 is, for example, a medical facility. A medical facility is a facility where medical personnel such as doctors, nurses, and clinical laboratory engineers perform medical activities such as specimen collection, examination, diagnosis, and treatment for patients or people suspected of having a disease. Examples of medical facilities include hospitals, clinics, and sanatoriums. Figure 1 In the example, the source facility 200 is not equipped with a sequencer, so it is impossible to perform nucleic acid analysis using a sequencer such as a genetic panel test. Therefore, the source facility 200 entrusts the destination facility 300 with nucleic acid analysis. The entrustment of nucleic acid analysis is carried out by sending electronic data of the entrustment letter (such as a PDF file) and / or submitting the entrustment letter printed on paper. In addition, the source facility 200 sends the specimen of the subject to the entrustment destination facility 300.

[0038] The destination facility 300 is a facility that performs nucleic acid analysis based on a request from the source facility 200 and provides a test result report recording the analysis result to the source facility 200. The destination facility 300 is, for example, a testing center. The destination facility 300 that accepts the request obtains nucleic acid from the specimen provided by the source facility 200 and analyzes it, creates a test result report based on the analysis result, and provides it to the source facility 200. The test result report is provided by sending electronic data (e.g., PDF file) of the test result report and / or submitting a report printed on paper.

[0039] like Figure 1 As shown, the information processing device 10, storage device 20 and sequencer 30 of this embodiment are provided in the entrusted destination facility 300. The information processing device 10 of this embodiment will be described later. The storage device 20 is a device for storing nucleic acid sequence data read by the sequencer 30. The storage device 20 can be, for example, a network-attached storage device (NAS). The NAS, for example, has a storage device such as a hard disk drive (HDD), a solid-state drive (SSD), a LAN interface and a simple OS. The data of the reference sequence described later can also be stored in advance in the storage device 20.

[0040] In this specification, "nucleic acid sequence data" refers to the read length obtained from a library sample derived from a specimen of a subject. Nucleic acid sequence data includes tumor sequence data and normal sequence data described later. "Read length" refers to the base sequence of an amplicon read by a sequencer. Library samples, amplicons, and read lengths will be described later.

[0041] Sequencer 30 is a device for reading the base sequence of polynucleotides. In this specification, the term "base sequence" has the same meaning as "nucleic acid sequence" and "nucleotide sequence". Base sequence refers to the one-dimensional arrangement (sequence) of nucleotides in nucleic acid molecules. Hereinafter, base sequence is sometimes referred to as "sequence". Sequencer 30 is preferably a next-generation sequencer. The term "next-generation sequencer" refers to the term used in comparison with the "first-generation sequencer", which is a sequencer based on capillary electrophoresis using the Sanger method. The next-generation sequencer can simultaneously and in parallel process tens of millions to hundreds of millions of nucleic acid fragments to read the sequence. The next-generation sequencer itself is well known, for example, HiSeq2500 (illumina), MiSeq (illumina), NextSeq (illumina), Ion Proton (ThermoFisher Scientific), Ion PGM (Thermo Fisher Scientific), GS FLX+ (Roche), GS Junior (Roche), etc. can be cited. The data of the base sequence read by the sequencer 30 is stored in the storage device 20 .

[0042] Reference Figure 2C , describing a structural example of a sequencer 30. The sequencer 30 includes a control unit 301, a transceiver unit 302, an input unit 303, an output unit 304, a storage unit 305, a circulation pool 306, and a photographing unit 307. The control unit 301 includes, for example, a processor such as a CPU, and a memory such as a ROM and a RAM. The transceiver 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, can also be used. The storage unit 305 is, for example, a storage device such as an HDD or an SSD. The circulation pool 306 includes a glass substrate having a flow path through which a reagent flows, causing cluster formation and sequence reaction of polynucleotides contained in a library sample introduced into the flow path. The photographing unit 307 photographs the clusters in the circulation pool 306 and stores the photographed 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.

[0043] "Library" refers to a collection of amplicons (amplification products) whose base sequences are analyzed by a sequencer. "Library sample" is a sample that includes a library, and is prepared by amplifying nucleic acids obtained from a specimen. In the preparation of the library sample, first, nucleic acids are extracted from the specimen of the subject. Depending on the purpose of the analysis, the type of nucleic acid is selected from DNA and RNA. In the extraction of DNA, the specimen and a solubilizing solution are mixed, and the solubilizing solution contains a surfactant that can solubilize cells or tissues (for example, sodium cholate, sodium dodecyl sulfate, etc.). The obtained mixed solution is physically treated (stirring, homogenization, ultrasonic disruption, etc.) to free the DNA contained in the specimen in the liquid. In the extraction of RNA, the specimen and a solubilizing solution containing guanidine thiocyanate and a surfactant are mixed. The obtained mixed solution is physically treated to free the RNA contained in the specimen in the liquid.

[0044] When the specimen is a formalin-fixed paraffin-embedded (FFPE) tissue, the extraction of nucleic acid can be performed, for example, as described below. First, xylene is added to the FFPE tissue for deparaffinization. The deparaffinized tissue is immersed in ethanol for hydrophilization. The hydrophilized tissue is treated with a protease to free the nucleic acid cross-linked by formalin in the liquid. Preferably, the mixed solution containing DNA or RNA is centrifuged to remove cell fragments, and a solution containing free DNA or RNA is obtained. Then, the obtained solution is subjected to phenol / chloroform extraction, so that the DNA or RNA can be refined. It is also possible to use commercially available kits to extract and refine nucleic acids from the specimen.

[0045] In the preparation of the library sample, it is preferred to fragment the nucleic acid. By fragmentation, the obtained nucleic acid can be made into a length suitable for being read by the sequencer 30 (tens to hundreds of bp). The nucleic acid can be fragmented, for example, by ultrasonic treatment. When the nucleic acid is DNA, fragmentation can also be performed by alkali treatment, restriction enzyme treatment, etc. For example, in the case of fragmenting DNA by alkali treatment, sodium hydroxide solution is added to the DNA solution in a manner to a final concentration of 0.1 to 1.0N, and incubated at 10 to 40°C for 5 to 15 minutes, so that the DNA is fragmented. In addition, in the case of fragmenting DNA by restriction enzyme treatment, restriction enzymes are appropriately selected according to the base sequence of the DNA, for example, MseI, BamHI, etc. are used. As needed, size selection of nucleic acid fragments, end smoothing, connection of adapter sequences, connection of index sequences, or connection of barcode sequences, etc. can also be performed.

[0046] The fragmented nucleic acid is preferably amplified by a PCR-based method. By designing a primer set capable of amplifying the region to be analyzed, and using these to amplify the nucleic acid by the PCR method, a library sample can be obtained. One primer set includes one forward primer and one reverse primer. It is also possible to concentrate the nucleic acid including the region to be analyzed from the nucleic acid fragments by a sequence capture method. By using the concentrated nucleic acid as a template for the PCR method and amplifying it, a library sample can be obtained. Hereinafter, the library sample derived from the DNA in the specimen is also referred to as a "DNA library sample."

[0047] It is also possible to attach additional sequences such as adapter sequences, index sequences, barcode sequences, and marker substances to the primers used for amplification. When multiple primer sets are used, these primer sets are preferably capable of performing multiplex PCR. Thus, multiple regions in the acquired nucleic acid can be amplified simultaneously. In this case, it is preferred to attach mutually different barcode sequences to each primer set. Thus, the amplicons formed by each primer set can be identified. It is also possible to use primer sets for multiplex PCR that are attached to commercially available kits such as exon sequencing kits.

[0048] The polymerase used for amplification can be appropriately selected from known thermostable polymerases for PCR, and among these, preferably a thermostable polymerase suitable for multiplex PCR and having few errors caused by PCR amplification. In the amplification reaction, a buffer suitable for the selected polymerase can be used. In order to suppress the errors caused by PCR amplification, the number of cycles of PCR is preferably set to the minimum limit within the range of obtaining the number of amplicons required for sequencing. The number of cycles is, for example, determined from a range of more than 10 cycles and less than 25 cycles.

[0049] Regarding the library sample obtained as described above, the base sequence can be read by a sequencing method known in the technical field. Although the sequencing method is not particularly limited, it is preferably an analysis based on a next-generation sequencer. As an analysis method based on a next-generation sequencer, ion semiconductor sequencing, pyrophosphate sequencing, SBS (sequencing by synthesis, sequencing by synthesis) method, etc. can be cited.

[0050] The information processing device 10 of this embodiment is a device for analyzing the sequence of nucleic acid obtained from a sample of a subject. Figure 2A, an example of the structure of the information processing device 10 is described. The information processing device 10 includes a control unit 101, a transceiver 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 variation information database 107, an analysis object table 108, a quality index table 109, and an analysis result database 110. Alternatively, the reference sequence database 106, the variation information database 107, the analysis object table 108, the quality index table 109, and the analysis result database 110 can also be stored in the storage device 20. The information contained in each database / table will be described later. The information processing device 10 can be composed of a computer, for example. In this case, the control unit 101 includes a processor such as a CPU, and a memory such as a ROM and a RAM. The transceiver 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 also be used. The storage unit 105 is, for example, a storage device such as an HDD or an SSD. A computer program for analyzing the sequence of nucleic acids is stored in the storage unit 105. The control unit 101 reads the computer program from the storage unit 105 and executes the analysis process of the nucleic acid sequence described later.

[0051] The information contained in the reference sequence database 106 and the variation information database 107 can be regularly updated to the latest information based on the information in the external database. The update of information can also be implemented by the manufacturer or user who provides the nucleic acid analysis system. Alternatively, the information can also be automatically updated by the nucleic acid analysis system. As an external database, for example, a database that accumulates information provided by academic groups and public institutions in various countries (reference sequence information, and various information related to known genetic gene mutations), a commercial database provided by a manufacturer, etc. can be cited.

[0052] "Reference sequence" refers to a sequence that serves as a reference for determining the base sequence corresponding to a certain position on the genomic region. A reference sequence is a sequence that includes the base sequence of the region to be analyzed. Examples of reference sequences include base sequences of the entire genomic region of a human, base sequences of the entire exon region, base sequences of target genes, and the like.

[0053] "Variation" and "genetic variation" include sudden mutation and genetic polymorphism. As variation, for example, sequence variation, structural variation and copy number variation can be cited. Sequence variation is the substitution, insertion, deletion and combination of one or more nucleotides. Regarding nucleotide substitution, for example, a base variation (SNV) and a base polymorphism (SNP) can be cited. Insertion and deletion of nucleotides are also called "InDel". Regarding structural variation, for example, translocation, inversion, deletion and duplication can be cited. Regarding copy number variation, for example, amplification and deletion can be cited.

[0054] The analysis object table 108 includes information of the analysis object area. Information about the analysis object area, for example, records information of the target gene selected as the analysis object area. As information of the target gene, for example, the name of the gene, position information and base sequence can be cited. As position information, the chromosome number (Chr), the starting point (Pos-Start) and the end point (Pos-End) of the base sequence of the gene on the chromosome sequence of the gene (Gene) can be cited. An example of the analysis object table 108 is shown in Table 1, but it is not limited to this.

[0055]

Table 1

[0056]

[0057] The "analysis target region" is a region in which the base sequence is expected to be analyzed in the nucleic acid obtained from the specimen of the subject. The analysis target region can be arbitrarily determined from the chromosome region. Preferably, the analysis target region is a part of the chromosome region containing at least one target genetic gene. The analysis target region can also be a whole chromosome region or a whole exosome region. The analysis target region can be one or more. For example, in a genetic gene panel test, dozens or hundreds of genetic genes are used as analysis target regions for nucleic acid analysis.

[0058] The "target gene" is a gene that is expected to be determined to have a mutation. The target gene is not particularly limited and can be appropriately determined according to the purpose of the test. For example, genes used for known gene panel tests can be cited. The base sequence of the target gene includes the base sequence of the transfer regulatory region such as the exon, intron, and promoter of the gene, and the sequence of the mRNA transferred from the gene. In the mRNA, pre-mRNA is included.

[0059] For example, the nucleic acid analysis system 100 can be used when a genetic panel test is performed. The genetic panel test is not limited to clinical tests, but also includes tests for research purposes. For example, the source facility 200 sends the entrustment information of nucleic acid analysis such as genetic panel tests to the destination facility 300 using the data sending and receiving device 40. In addition, the source facility 200 sends the specimen of the subject to the destination facility 300.

[0060] The subject is not particularly limited, and for example, patients, persons suspected of having a disease, healthy persons, etc. can be cited. The disease is not particularly limited, and for example, diseases that are considered useful by genetic examinations and chromosome group medicine can be cited. As such diseases, for example, cancer, autoimmune diseases, hereditary diseases, etc. can be cited. The specimen is not particularly limited as long as it contains the nucleic acid of the subject. Preferably, the specimen is a biological sample extracted from the subject. As a biological sample, for example, tissues, cells, body fluids, secretions, urine, stool, etc. can be cited. Regarding body fluids, for example, blood (whole blood), bone marrow fluid, cerebrospinal fluid, lymph fluid, ascites, pleural effusion, amniotic fluid, joint fluid, etc. can be cited. Regarding secretions, for example, saliva, sweat, tears, nasal mucus, semen, nipple secretions, etc. can be cited. The specimen can also be a modulated substance from a biological sample. For example, regarding modulated substances from blood, plasma and serum can be cited. As modulated substances from cells, cultures (including cultured cells and culture medium) obtained by culturing extracted cells can be cited. Examples of tissue-derived preparations include frozen tissue, fixed tissue, and FFPE tissue.

[0061] When a matched pair test is performed on a subject who is a patient with a solid tumor, two types of specimens, tumor specimens and non-tumor specimens, are used as specimens. A matched pair test refers to a test that can analyze the sequences of nucleic acids obtained from tumor specimens and non-tumor specimens of patients with solid tumors, respectively, and distinguish somatic cell mutations from germ cell mutations based on these results. Tumor specimens can be, for example, tumor tissues and their modulated substances extracted from the subject by surgery or biopsy. Non-tumor specimens can be non-tumor cells (e.g., whole blood) extracted from the same subject.

[0062] Solid tumors refer to cancers other than blood cancers among cancers. The type of solid tumor is not particularly limited, and may be any of epithelial cell cancers and non-epithelial cell cancers. Epithelial cell cancers are not particularly limited as long as they are cancers that occur in epithelial cells, and examples thereof include lung cancer, breast cancer, gastric cancer, colorectal cancer, liver cancer, uterine cancer, ovarian cancer, and the like. Regarding non-epithelial cell cancers, for example, osteosarcoma, chondrosarcoma, rhabdomyosarcoma, leiomyosarcoma, fibrosarcoma, liposarcoma, angiosarcoma, and the like may be cited.

[0063] The quality index table 109 includes at least position information of a predetermined part in the analysis target area as information related to the predetermined part described later. Figure 2B As shown, the analysis result database 110 includes, for each inspection request, a measurement result table including the detection result of the variation in the analysis target region, a quality information table including information related to the quality of the nucleic acid analysis for the predetermined part, and a report table including information of the inspection result report generated based on these. Each table is associated with an inspection request ID that uniquely identifies the inspection request.

[0064] The following describes the analysis of nucleic acid sequences using the nucleic acid analysis system 100. When the person in charge of the source facility 200 inputs the entrustment information of nucleic acid analysis to the data sending and receiving device 40, the entrustment information is sent to the information processing device 10 via the network 400 and received by the information processing device 10. The entrustment information may also include, for example, information of the subject, information of the specimen, etc. The information of the subject includes, for example, age, gender, type and condition of the disease, etc. The information of the specimen includes, for example, the type of specimen, the extraction period, the specimen ID that associates the specimen with the subject, etc. The entrustment information may also include the designation of the analysis object area and / or the predetermined part. In the case of a commission for a genetic panel examination, the designation of the desired genetic panel may also be included in the entrustment information. The predetermined part will be described later. The person in charge of the destination facility 300 inputs the entrustment of the analysis to the sequencer 30 based on the entrustment information received by the information processing device 10.

[0065] Reference Figure 3 The following describes the reading of the base sequence by the sequencer 30. In step S11, the control unit 301 of the sequencer 30 receives a request for analysis. In step S12, the control unit 301 of the sequencer 30 reads the base sequence of the library sample.

[0066] As described above, the base sequence of the amplicon read by the sequencer is the "read length". That is, in step S12, the sequencer 30 reads the base sequence of each amplicon of the library sample to obtain the read length. The length of the read length varies depending on the analysis method, the type of sequencer, etc., for example, it is more than 50 bases, preferably more than 100 bases, and more preferably more than 150 bases. In addition, the length of the read length is, for example, less than 500 bases, preferably less than 350 bases, and more preferably less than 250 bases. The number of read lengths is not particularly limited and varies according to the number of copies of the nucleic acid obtained from the specimen, the site amplified by the PCR method, etc.

[0067] In step S13, the control unit 301 of the sequencer 30 sends all the obtained read lengths to the storage device 20. The storage device 20 stores these read lengths. The file format of the read lengths sent from the sequencer 30 is, for example, FASTA, FASTQ, and uBAM. FASTA files are files that only include sequence information of the read lengths. FASTQ files are files that include sequence information of the read lengths including quality scores described later. uBAM files are binary files that include sequence information of the read lengths that have not been aligned to the reference sequence. Alignment will be described later. In addition, in step S13, the control unit 301 of the sequencer 30 may also send the obtained read lengths to the information processing device 10. In this case, the information processing device 10 stores these read lengths.

[0068] The file sent from the sequencer 30 may also include the name of the read length (or sequence ID), the quality score of each base in the sequence, and other information together with the read length data. The quality score is an indicator of the correctness of the base recognition (base designation) using the sequencer. Here, the base sequence of the read length is determined by performing base recognition based on the tracking data obtained by the sequencer (metadata such as waveform data of the signal obtained by the sequencing reaction). That is, the quality score represents the correctness of the base sequence determined by the sequencer. Base recognition is performed, for example, by a well-known base recognition program such as Phred. As a quality score, for example, the quality score (Q) output from the sequencer of Illumina (HiSeq2500, MiSeq, NextSeq, etc.) can be used. The quality score (Q) is calculated by the following formula (I). In the formula, E is an estimated value of the probability of base recognition error.

[0069] Q = -10log 10 E…(I)

[0070] Quality scores are assigned to each base in the read. For example, if a base in the read has a quality score of 20, the frequency of errors in that base is 10. -2 / base, when the quality score is 30, the frequency of errors in this base is 10 -3 / base. The average value of the quality score in the read length can indicate the frequency of errors. The average value of the quality score can be calculated by dividing the sum of the quality scores of each base of the read length by the length of the read length (number of bases). For example, when the average value of the quality score is 20, there is 1 error in the read length in 100 bases, and when the average value of the quality score is 30, there is 1 error in the read length in 1000 bases. In this way, the higher the quality score, the lower the probability of error. Using the next generation sequencer, the quality score and its average value are automatically calculated.

[0071] In the case of a matching pairing test using DNA as the object of analysis, DNA library samples are prepared according to the tumor specimen (e.g., FFPE specimen of tumor tissue) and the non-tumor specimen (e.g., whole blood). Then, in step S12, the sequencer 30 reads the base sequence of each amplicon of each library sample to obtain the read length. Hereinafter, the read length obtained from the DNA library sample from the tumor specimen is referred to as "tumor sequence data". In addition, the read length obtained from the DNA library sample from the non-tumor specimen is referred to as "normal sequence data".

[0072] Reference Figure 4 , an example of analysis processing of nucleic acid sequence data performed by the information processing device 10 is described. In step S21, the control unit 101 of the information processing device 10 reads the read length stored in the storage device 20. In step S22, the control unit 101 obtains the detection result of the variation in the analysis target region based on the read length.

[0073] As an embodiment of step S22, the process of detecting somatic cell mutation and germ cell mutation by matching pair test is described. Somatic cell mutation refers to mutation occurring in the genetic genes of somatic cells. Somatic cell mutation is known to be one of the causes of tumors. Figure 5 In step S31, the control unit 101 reads the 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 the normal sequence data and the reference sequence. The results of the alignment between the tumor sequence data and the reference sequence and the results of the alignment between the normal sequence data and the reference sequence are stored in the storage unit 105.

[0074] "Alignment" is the process of determining the corresponding area on the reference sequence for each read length. Alignment is also called mapping. The reference sequence is a base sequence that does not contain somatic mutations. For example, the reference sequence is the base sequence of the wild-type chromosome group. In the alignment of the read length and the reference sequence, well-known alignment tools (software) such as BWA (Burrows-Wheeler Aligner), BWA-MEM, Bowtie, Bowtie2, BLAST, etc. can be used.

[0075] Hereinafter, the read length corresponding to the analysis target region among the read lengths is also referred to as the “first read length”. The “read length corresponding to the analysis target region” refers to the read length of the base sequence arranged in the analysis target region when the alignment with the reference sequence including the base sequence of the analysis target region is performed. Fig. 7A as well as Figure 7BAs shown, in the base sequence of the analysis target region, multiple first reads are usually mapped. The base sequence of the analysis target region is usually longer than the first read. In the figure, the first read is represented by a white bar and a black bar. In addition, the black bar in the first read represents the second read described later.

[0076] The control unit 101 may also calculate the mapping quality score of each sequence read. The mapping quality score is an indicator of the correctness of the mapping of the read. The mapping quality score (Q) is calculated by the following formula (II). In the formula, P is the probability that the read is mapped to the wrong position.

[0077] Q = -10log 10 P…(II)

[0078] The higher the mapping quality score of a read, the lower the probability that the read is mapped to an incorrect position. Therefore, when the mapping quality score of a read is high, it can be said that the read is likely to have a base sequence corresponding to the analysis target region.

[0079] If there are parts in the tumor sequence data that are inconsistent with the reference sequence, the parts may be genetic mutations of the tumor tissue or genetic polymorphisms inherent in the subject. If there are parts in the normal sequence data that are inconsistent with the reference sequence, the parts may be genetic polymorphisms inherent in the subject or germ cell mutations.

[0080] In step S33, the control unit 101 determines whether there is a site inconsistent with the reference sequence in the normal sequence data. As described above, in the case where there is a site inconsistent with the reference sequence, the site may be a germ cell mutation or a genetic polymorphism inherent to the subject. When the control unit 101 determines that the normal sequence data is inconsistent with the reference sequence, the process enters step S34. In step S34, the control unit 101 determines that the site inconsistent with the reference sequence in the normal sequence data detected in step 33 is a germ cell mutation. Thereafter, the process enters step S37 described later. On the other hand, in step S33, when the control unit 101 determines that the normal sequence data is consistent with the reference sequence, the process enters step S35. In step S35, the control unit 101 determines whether the tumor sequence data corresponding to the site consistent with the reference sequence in the normal sequence data detected in step 33 is consistent with the reference sequence. In the case where the tumor sequence data is inconsistent with the reference sequence, the site inconsistent with the reference sequence in the tumor sequence data detected in step S35 is likely to be a genetic mutation that is only identified as a tumor tissue. The genetic mutation identified only as 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.

[0081] In step S35, when the tumor sequence data is consistent with the reference sequence, the control unit 101 ends the processing. In this case, it is considered that there is no somatic cell mutation or germ cell mutation in the subject.

[0082] In step S37, the control unit 101 searches the mutation information database 107 based on the detected somatic cell mutation or germ cell mutation. In the mutation information database 107, information for determining known genetic gene mutations is accumulated. As such information, there can be cited a mutation identifier (mutation ID), a genetic gene name, position information of the mutation (for example, a chromosome number (Chr) and a base number (Pos) of a chromosome sequence), REF, ALT, annotations, etc. The mutation ID is an identifier for identifying a mutation. The Chr in the position information of the mutation indicates the number of the chromosome where the mutation is located. Pos indicates the base number of the chromosome sequence. REF indicates the base in the wild type, and ALT indicates the mutated base. Annotations indicate information on amino acids and / or bases that have changed due to mutations. Annotations can also be displayed, for example, as "p.A146V" and "c.437C>T". "p.A146V" means that the 146th alanine residue of the protein has changed to a valine residue due to a mutation. "c.437C>T" means that the 437th cytosine was changed to thymine due to mutation.

[0083] For example, the control unit 101 can search the mutation information database 107 based on the name and position information of the gene in which the detected somatic cell mutation or germ cell mutation exists. In this way, it can be determined to which of the known genetic gene mutations the detected somatic cell mutation or germ cell mutation corresponds.

[0084] The mutation information database 107 may store not only information for determining known genetic mutations, but also disease information, drug information, and biomarker attribute information associated with these known genetic mutations. As disease information, for example, disease names associated with known genetic mutations (e.g., colorectal cancer, lung cancer, breast cancer, etc.), types of diseases (e.g., cancer, eye diseases, mental and neurological diseases, etc.), information related to driver mutations, information related to pathogenicity evaluation of mutations (e.g., pathogenicity, the possibility of pathogenicity, benignity, etc.), information related to the level of association between mutations and diseases (e.g., evidence level), category information of association between mutations and diseases (e.g., oncogenicity evidence, disease predisposing evidence, treatment effect prediction evidence, diagnostic evidence, prognostic evidence), etc. As drug information, for example, information such as the presence or absence of therapeutic drugs associated with known genetic mutations, the names of therapeutic drugs, and the countries / regions where therapeutic drugs are recognized may be cited. As the attribute information of the biomarker, for example, there can be cited the type of biomarker (such as companion diagnosis (CDx), malignancy, prognosis, risk of disease, risk of onset, etc.), information on the marker test (such as the name of the disease for which the test is applied, the name of the therapeutic drug, the country / region where the test is recognized, etc.).

[0085] In step S38, the control unit 101 annotates the detected somatic cell mutation or germ cell mutation according to the search result. Through the processing of steps S31 to S38, the control unit 101 obtains the information of genetic mutation in the analysis target area as the detection result of the mutation in step S22. As the information of genetic mutation, for example, the name of the genetic gene (Gene) in which the mutation is detected, the position information of the mutation (chromosome number (Chr), base number (Pos) of the chromosome group sequence, etc.), amino acid changes (AA) in genetic mutation, coding region changes (CDS) in genetic mutation, information on the category of somatic mutation or germ cell mutation (Somatic / Germline), type of mutation (Mutation type), etc. can be cited.

[0086] The control unit 101 stores the detection results of the mutations obtained through the process of step S22 into the measurement result table of the inspection result database 110. Table 2 shows an example of a measurement result table, but is not limited to this. The measurement result table includes all genetic mutations detected through the process of step S22. In the table, "Chr" represents the chromosome number of the detected genetic mutation, "Pos" represents the base number of the chromosome group sequence of the detected genetic mutation, "CDS" represents the coding region change in the detected genetic mutation, "AA" represents the amino acid change in the detected genetic mutation, "Somatic / Germline" represents the category of whether the detected genetic mutation is a somatic mutation or a germ cell mutation, and "Mutation type" represents the type of detected genetic mutation.

[0087]

Table 2

[0088]

[0089] The control unit 101 ends the process of obtaining the detection result of the variation, and the process enters Figure 4 In step S23, the control unit 101 generates information on the quality of nucleic acid analysis for a predetermined portion based on the nucleic acid sequence data.

[0090] "Predetermined position" refers to at least one position arbitrarily selected from the base sequence of the analysis object area. In order to investigate the quality of nucleic acid analysis and provide information related to the quality, the predetermined position is selected. The determination of the predetermined position by the control unit 101 will be described later. In the base sequence of the analysis object area, the predetermined position can be either one place or multiple places. In addition, the predetermined position is composed of one base or more than two continuous bases in the base sequence of the analysis object area. That is, the predetermined position can be either one base or a region composed of multiple continuous bases. In the case where the predetermined position is a region composed of multiple continuous 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.

[0091] The predetermined position preferably includes a position where there is a possibility of mutation. The predetermined position can be either a position where there is a possibility of mutation, or a position and its vicinity where there is a possibility of mutation. For example, in the case of a known mutation in the analysis object area, when it is known that a certain base may be substituted or deleted, or a base may be inserted, the predetermined position may also be a base itself that may produce the mutation. Alternatively, the predetermined position may also be a region with 1 to 5 bases on the upstream and downstream sides centered on a base that may produce the mutation. In this case, the predetermined position may also be a region including a base that may produce the mutation. Regardless of whether a mutation actually occurs at the predetermined position. The result of nucleic acid analysis may be that a mutation occurs at the predetermined position or no mutation occurs.

[0092] A variation that may occur at a predetermined site is, for example, a variation related to diagnosis or treatment of a disease in the analysis target region. Examples of such variations include the variations described in (1) to (3) below.

[0093] (1) Variants known to be associated with the effects and / or side effects of a drug,

[0094] (2) variants known to be associated with disease status, onset and / or prognosis, and

[0095] (3) Variants whose level of evidence indicating association with diagnosis or treatment is known to be above a predetermined level.

[0096] (1) The recorded variation is, for example, a companion diagnostic marker (CDx marker). As such a marker, for example, the genetic variation used in the genetic panel examination such as the FoundationOne (registered trademark) CDx cancer genome analysis test (Chugai Pharmaceutical Co., Ltd.) is known. (2) The recorded variation is, for example, a driver variation, a pathogenic variation, a variation as a malignancy marker, a variation as a prognosis prediction marker, a variation as a disease risk marker, and a variation as a disease risk marker. As such a marker, for example, the genetic variation used in the OncoGuide (trademark) NCC Oncopanel system (Sysmex Corporation) and the FoundationOne (registered trademark) CDx cancer genome analysis test (Chugai Pharmaceutical Co., Ltd.) is known.

[0097] The level of evidence indicates the degree to which the evidence is reliable or recommendable. (3) The level of evidence recorded is, for example, the level of evidence of tumorigenicity, disease predisposition association evidence, treatment effect prediction evidence, diagnostic evidence, or prognosis prediction evidence. Tumorigenicity evidence refers to genetic mutations that contribute to cell carcinogenesis, such as somatic cell mutations and germ cell mutations. Disease predisposition association evidence refers to germ cell mutations associated with carcinogenesis in hereditary breast cancer, ovarian cancer, etc. Treatment effect prediction evidence refers to markers associated with sensitivity and tolerance to drugs, radiotherapy, etc., drug metabolizing enzymes that affect drug dynamics, genetic mutations of drug transporters, etc. Diagnostic evidence is a marker associated with the patient's diagnosis, such as cell morphology, tumor tissue images, and the discovery and local presence of cancer-specific marker proteins based on immunohistochemical staining. Prognosis prediction evidence refers to markers related to the development, severity, and survival prognosis of cancer. For example, the levels of evidence on these have been published by academic groups such as the Japan Society of Clinical Oncology, the Japanese Society for Cancer Treatment, the Japanese Cancer Society, the American Society of Clinical Oncology (ASCO), the Association of American Pathologists (CAP), the Association for Molecular Pathology (AMP), and the European Society of Clinical Oncology (ESMO).

[0098] For example, variants associated with disease diagnosis or treatment can also be selected from CDx markers approved by the FDA. Figures 6A to 6C The biomarkers described in the table shown are selected from variants related to the diagnosis or treatment of a disease. Table 3 shows the names and manufacturers of tests or kits corresponding to each biomarker shown in these figures.

[0099]

Table 3

[0100]

[0101] It is also possible to select a predetermined site from the base sequence of the analysis target region based on the information in the above-mentioned variation information database 107. Specifically, the control unit 101 reads the information of the analysis target region and the information related to the known genetic variation from the storage unit 105. The information related to the known genetic variation is included in the variation information database 107. The information related to the known genetic variation is, for example, information for determining the above-mentioned known genetic variation, disease information, drug information, and attribute information of biomarkers. The control unit 101 determines the predetermined site based on the read information and extracts the information related to the predetermined site. The information related to the predetermined site may also be included in the quality indicator table 109 (refer to Figure 2B) is stored in the storage unit 105. In addition, the predetermined position can be selected by the control unit 101 according to a predetermined judgment rule or a user's instruction, or can be selected by a designer of a computer program for analyzing the sequence of nucleic acid stored in the storage unit 105, and the selected predetermined position is recorded in the computer program in advance.

[0102] As an embodiment, an example of determining a predetermined site based on attribute information of a biomarker is 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 can also be determined based on information of other biomarkers related to malignancy, prognosis, risk of disease, risk of onset, etc. The control unit 101 obtains information of a CDx marker from a variation information database 107. Next, the control unit 101 extracts a site of a CDx marker from an analysis object region of an analysis object table 108 based on the obtained information. Then, the control unit 101 stores information indicating the position of the extracted CDx marker site in a quality index table 109 of the storage unit 105. Thus, the control unit 101 can determine a site of a CDx marker in an analysis object region as a predetermined site. Table 4 shows an example of a quality index table 109 of this embodiment. In the table, "Region" indicates a country and region where a CDx marker is recognized.

[0103]

Table 4

[0104]

[0105] As shown in Table 4, in the quality index table 109, as information related to the predetermined part, the name of the genetic gene including the predetermined part (Gene), the position information of the predetermined part (the chromosome number (Chr) where the predetermined part is located, the base number (Pos) of the chromosome group sequence) is recorded. In the quality index table 109, as shown in Table 4, as information related to the possible variation occurring at the predetermined part, the amino acid variation (AA) in the genetic gene variation is recorded. In the quality index table 109 shown in Table 4, the type of marker (Marker type), the country and region (Region) where the CDx test is recognized, and the type of disease (cancer) for which the CDx test is applied (Cancer type) are further recorded.

[0106] As a further embodiment, an example of determining a predetermined site based on disease information is described. In this example, as disease information, the predetermined site is determined based on the name of a disease associated with a known genetic mutation. More specifically, the predetermined site is determined based on lung cancer. However, the disease information is not limited to lung cancer. The predetermined site can also be determined based on information about other diseases or types of diseases. The control unit 101 obtains information about genetic mutations associated with lung cancer from the mutation information database 107. Next, the control unit 101 obtains one or more bases associated with lung cancer from the analysis object area of ​​the analysis object table 108 based on the obtained information. Then, the control unit 101 stores the information of the extracted one or more bases associated with lung cancer in the storage unit 105 as a quality indicator table 109. Thus, the control unit 101 can determine one or more bases associated with lung cancer in the analysis object area as the predetermined site.

[0107] An example of determining a predetermined site based on other disease information is described. In this example, the predetermined site is determined based on information related to the level of association between a mutation and a disease as disease information. More specifically, the predetermined site is determined based on the level of evidence. However, disease information is not limited to the level of evidence. The predetermined site can also be determined based on category information of the association between a mutation and a disease. The control unit 101 obtains information about genetic mutations with an evidence level above a predetermined level from the mutation information database 107. Next, the control unit 101 extracts one or more bases that may produce genetic mutations with an evidence level above a predetermined level from the analysis object area of ​​the analysis object table 108 based on the acquired information. Moreover, the control unit 101 stores the information of the extracted one or more bases in the storage unit 105 as a quality indicator table 109. Thus, the control unit 101 can determine one or more bases in the analysis object area that may produce genetic mutations with an evidence level above a predetermined level as the predetermined site.

[0108] Furthermore, an example of determining a predetermined site based on other disease information is described. In this example, the predetermined site is determined based on information related to driver mutations as disease information. However, disease information is not limited to information related to driver mutations. The predetermined site can also be determined based on information related to pathogenicity evaluation of mutations. The control unit 101 obtains information related to driver mutations from the mutation information database 107. Next, the control unit 101 extracts one or more bases that may cause driver mutations from the analysis target area of ​​the analysis target table 108 based on the acquired information. Then, the control unit 101 stores the information of the extracted area as the quality indicator table 109 in the storage unit 105. As a result, the control unit 101 can determine one or more bases in the analysis target area that may cause driver mutations as the predetermined site.

[0109] Table 5 shows an example of a quality index table 109 based on disease information. In the table, "Disease type" indicates the type of disease associated with the variation, "Disease name" indicates the name of the disease associated with the variation, "Evidence type" indicates the category information of the association between the variation and the disease, and "Evidence level" is information indicating the level of association between the variation and the disease. As shown in Table 5, the position information of the predetermined part (the chromosome number (Chr) where the predetermined part is located, the base number (Pos) of the chromosome group sequence) and various disease information can also be recorded in the quality index table 109 in correspondence.

[0110]

Table 5

[0111]

[0112] As a further embodiment, an example of determining a predetermined position based on drug information is described. In this example, as drug information, the predetermined position is determined based on whether there is a therapeutic drug associated with a known genetic mutation. However, drug information is not limited to whether there is a therapeutic drug. The predetermined position can also be determined based on information such as the name of the therapeutic drug and the country / region where the therapeutic drug is recognized. The control unit 101 obtains information about whether there is 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 that may produce a genetic mutation with a known association with the therapeutic drug from the analysis object area of ​​the analysis object table 108 based on the acquired information. Then, the control unit 101 stores the information of one or more bases that may produce a genetic mutation with a known association with the therapeutic drug as a quality indicator table 109 in the storage unit 105. As a result, the control unit 101 can determine one or more bases that may produce a genetic mutation with a known association with the therapeutic drug as a predetermined position in the analysis object area. Table 6 shows an example of the quality indicator table 109 of this embodiment. In the table, "Drug" indicates an approved therapeutic drug, "Region" indicates a country and region where the therapeutic drug is approved, and "Disease name" indicates a type of cancer for which the approved therapeutic drug is targeted. In Table 6, lung cancer is exemplified as "Disease name".

[0113]

Table 6

[0114]

[0115] As shown in Table 6, the position information of the predetermined part (the chromosome number (Chr) where the predetermined part is located, the base number (Pos) of the genomic sequence) and various drug information may be recorded in correspondence in the quality index table 109. In addition, in the above-mentioned embodiment, the chromosome number (Chr) where the predetermined part is located and the base number (Pos) of the genomic sequence are used as the position information of the predetermined part, but it is not limited to this, and it only needs to be information that determines the position of the base in the analysis target area.

[0116] about Figure 4 In step S23, the control unit 101 of the information processing device 10 of the present embodiment generates information related to the quality of the nucleic acid analysis for the predetermined part based on the second read corresponding to the predetermined part in the first read. The control unit 101 generates information related to the quality of the nucleic acid analysis for the predetermined part with respect to the nucleic acid derived from the subject, regardless of whether there is a mutation in the predetermined part. Here, the "second read corresponding to the predetermined part" refers to the first read that is aligned to the area including the predetermined part in the analysis object area. Hereinafter, the second read corresponding to the predetermined part will also be referred to as the "second read". Refer to Fig. 7A 7B illustrates the relationship between the first read aligned to the analysis target region and the second read corresponding to the predetermined site. Fig. 7A In the figure, as shown by "X" and "Y" in the reference sequence, two predetermined positions of one base are selected from the base sequence of the target region for analysis. In the figure, the first read is represented by white and black bars and is aligned to the target region for analysis. Fig. 7A As shown, when the predetermined site is one base, the second read corresponding to the predetermined site is the first read including 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.

[0117] As information related to the quality of nucleic acid analysis, for example, depth information at a predetermined position of the analysis object area can be generated. "Depth" refers to the number of reads aligned to the position corresponding to the base on the reference sequence. Depth is also called read depth, which indicates how many times a certain base in the analysis object area is read in one measurement. "Depth information" refers to the depth of the base at the predetermined position and / or information obtained from the depth. For example, in the case where the predetermined position is a base in one place or multiple places, the depth information may be about the depth of each base. That is, the depth of the predetermined position is the number of second reads of each base aligned to the predetermined position. In the case where the predetermined position is an area composed of multiple bases, the depth information is the depth of each base contained in the predetermined position, and / or a statistical representative value of these depths. Regarding the statistical representative value of the depth, for example, the average value, the most frequent value, the central value, the minimum value, the maximum value, etc. of the depth can be cited. Depth information is one of the information related to the quality of nucleic acid analysis. In Fig. 7A In the example, for each base of X and Y at a predetermined position, depth A and depth B are acquired as depth information, respectively.

[0118] exist Figure 7B In the example, the region from "X" to "Y" in the reference sequence is selected as the predetermined region. Fig. 7A Similarly, the first read is represented by white and black bars and is aligned to the analysis target region. In addition, the second read is represented by a black bar. Figure 7B As shown in FIG. 1 , when the predetermined portion is composed of a plurality of consecutive bases, the second read length corresponding to the predetermined portion is the first read length including bases corresponding to a part or all of the predetermined portion. Figure 7B In the example, with respect to a predetermined portion (base sequence from X to Y), a depth C can be acquired as depth information.

[0119] As an embodiment of step S23, the process of obtaining depth information of a predetermined part based on each data of tumor sequence data and normal sequence data is described. Hereinafter, the depth information obtained based on tumor sequence data is referred to as "depth information T". In addition, the depth information obtained based on normal sequence data is referred to as "depth information N". Figure 8In step S41, the control unit 101 reads the result of the alignment of the tumor sequence data and the reference sequence performed in step S31 from the storage unit 105. In step S42, the control unit 101 refers to the result of the alignment of the tumor sequence data and the reference sequence, and obtains the depth information T according to the number of the second reads as the first read corresponding to the predetermined part of the analysis target region. In step S43, the control unit 101 reads the result of the alignment of the normal sequence data and the reference sequence performed in step S32 from the storage unit 105. In step S44, the control unit 101 refers to the result of the alignment of the normal sequence data and the reference sequence, and obtains the depth information N according to the number of the second reads as the first read corresponding to the predetermined part of the analysis target region. When there are multiple predetermined parts, the depth information T and N are obtained for each predetermined part. In step S45, the control unit 101 stores the depth information T and N at the predetermined part in the quality information table of the inspection result database 110 of the storage unit 105. Then, the control unit 101 ends the process of generating information related to the quality of nucleic acid analysis for the predetermined portion, and the process proceeds to Figure 4 Step S24.

[0120] In addition, in the acquisition of depth information T in step S42, mapping data can be used in reference to the results of alignment of tumor sequence data and reference sequence. Similarly, in the acquisition of depth information N in step S44, mapping data can also be used in reference to the results of alignment of normal sequence data and reference sequence. Mapping data refers to information on read lengths including the results of alignment of read lengths to reference sequences. In addition, in the case where the results of alignment of tumor sequence data and normal sequence data with reference sequence are not referred to in steps S42 and S44, the control unit 101 may also read out the tumor sequence data and reference sequence in step S41 and perform alignment of the tumor sequence data with the reference sequence in step S42. Furthermore, the normal sequence data and reference sequence may also be read out in step S43 and the alignment of the normal sequence data with the reference sequence may be performed in step S44.

[0121] Table 7 shows an example of a quality information table, but is not limited to this. In the table, each information corresponding to "Chr", "Gene", "Pos", and "AA" is information transferred from the quality index table 109, and is information related to the predetermined part. "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 respectively record the average value of the depth of the predetermined part in three places, but are not limited to this. For example, the depth information T and the depth information N may also be the maximum value, the middle value, or the minimum value of multiple predetermined parts, respectively. The depth information T and the depth information N may also be the depth information T and the depth information N of each predetermined part, respectively. "The detection result of the variation" is information about whether each predetermined part is determined to be a germ cell variation or a somatic variation through the processing of step S33 or S35. For example, the second predetermined part in Table 7 indicates that there is a variation, and the third and fourth predetermined parts indicate that there is no variation. The "detection result of the variation" can be determined based on whether the variation at the predetermined part included in the quality information table is included in the measurement result table. As shown in Table 7, in the quality information table, regardless of whether the detection result of the variation at the predetermined position is "YES" or "NO", that is, regardless of whether there is a variation at the predetermined position, the depth information T and the depth information N are included. The depth information T and the depth information N are examples of information related to the quality of the nucleic acid analysis for the predetermined position. In addition, the "variation detection result" can also be omitted from the quality information table.

[0122]

Table 7

[0123]

[0124] Examples of information related to the quality of nucleic acid analysis of a predetermined site include the information described in the following (1) to (4).

[0125] (1) information about the number and / or length of the second reads,

[0126] (2) information related to the accuracy of reading the base sequence by the sequencer, which is assigned to each base of the second read length;

[0127] (3) information on the accuracy of the mapping, assigned to each base of the second read in the alignment of the first read to the reference sequence, and

[0128] (4) The result of determining the quality based on at least one of the information described in (1) to (3) above.

[0129] (1) The information related to the number of second reads in the recorded information is, for example, depth information of a predetermined part. The depth information is as described above. The information related to the length of the second read is, for example, the average value, the most frequent value, the median value, the minimum value, the maximum value, etc. of the length of the second read.

[0130] The information recorded in (2) is, for example, an index value assigned to each base of the second read, indicating the correctness of base recognition. As such an index value, for example, the above-mentioned quality score can be cited. The quality score assigned to each base of the second read can also be used as the information recorded in (2). Alternatively, a statistical representative value (average value, most frequent value, central value, minimum value, maximum value, etc. of each quality score) assigned to each base of the second read can also be used as the information recorded in (2).

[0131] (3) The information recorded is, for example, an index value assigned to the second read length, indicating the correctness of the mapping. As such an index value, for example, the above-mentioned mapping quality score can be cited. The information recorded in (1) to (3) indicates the quality of nucleic acid analysis for a short region corresponding to a predetermined portion consisting of a base or the base and its vicinity. Therefore, for example, the depth information recorded in (1) indicates the quality of nucleic acid analysis at a predetermined portion with higher accuracy than the statistical representative value of the depth for the entire length of a genetic gene.

[0132] The determination recorded in (4) can also be performed, for example, by comparing any one value selected from the information recorded in (1) to (3) above with a threshold value. For example, when the depth of the predetermined part is above the corresponding threshold value, it can be determined that the quality of the nucleic acid analysis is good. In addition, when the depth of the predetermined part is less than the corresponding threshold value, it can be determined that the quality of the nucleic acid analysis is not good. The determination result can also be displayed using symbols, numbers, text, etc. For example, when it is determined that the quality of the nucleic acid analysis is good, a check mark can be displayed in the determination result column, and when it is determined that the quality of the nucleic acid analysis is not good, the determination result can be set to a blank column.

[0133] Reference Figure 4 In step S24, the control unit 101 outputs the inspection result report including the detection result of the variation obtained in step S22 and the information on the quality of the nucleic acid analysis of the predetermined part obtained in step S23 to the output unit 104. The control unit 101 may also output the inspection result report to the data transmission and reception device 40 via the network 400.

[0134] Fig. 9An example of an inspection result report is shown. The inspection result report R includes an area R1 recording inspection request information, an area R2 recording mutation detection results, and an area R3 recording information related to the quality of nucleic acid analysis for a predetermined site. In area R1, the request information sent from the source facility is recorded, for example, the inspection request ID, information about the subject, etc. are recorded. In area R2, the mutation detection results obtained in step S22 and stored in the measurement result table of the storage unit 105 are recorded. In area R3, information related to the quality of nucleic acid analysis for a predetermined site is recorded in the quality information table obtained in step S23 and stored in the storage unit 105. Fig. 9 In the example of , the region R3 further records the result of determining the quality of the nucleic acid analysis. Fig. 9 In the table, "determination result T" indicates the result obtained by determining the quality of nucleic acid analysis based on the value of Depth T and the threshold value, and "determination result N" indicates the result obtained by determining the quality of nucleic acid analysis based on the value of Depth N and the threshold value.

[0135] like Fig. 9 As shown, in the region R3 of the inspection result report output from the information processing device 10, regardless of whether there is a mutation in the predetermined position, information related to the quality of the nucleic acid analysis is recorded. Thus, even if the person in charge of the source facility 200 and / or the destination facility 300 is not detected in the predetermined position in the analysis target area of ​​the nucleic acid of the subject, it is possible to confirm the quality of the nucleic acid at the predetermined position. For example, regarding the second predetermined position of region R3 (29,432,664 of chromosome 2), the detection result of the mutation is "NO", and a check mark is displayed in the column of the determination result T of Depth T. This suggests that no mutation was detected at the predetermined position in the inspection, and the result is based on an analysis of sufficient quality. That is, the detection result of the mutation is true negative. In addition, regarding the third predetermined position of region R3 (29,432,682 of chromosome 2), the detection result of the mutation is "NO", and the determination result T of Depth T is a blank column. This suggests that although no mutation was detected at the predetermined position in the inspection, there is a suspicion that a mutation actually exists in the nucleic acid of the subject. That is, the test result of the suspected mutation is a false negative. In this case, it is possible to specifically study the next actions that medical personnel should take, such as re-implementing the genetic panel test or implementing other tests narrowed down to the genetic markers corresponding to the predetermined site. If a mutation is detected during the re-examination, appropriate diagnosis or treatment can be guided.

[0136] In addition, in this embodiment, the detection result of the variation and the information related to the quality of the nucleic acid analysis for the predetermined part are recorded in the same report, but the detection result of the variation and the information related to the quality of the nucleic acid analysis for the predetermined part may be generated as separate reports. For example, an analysis result report for reporting the detection result of the variation and a quality management report for reporting the information related to the quality of the nucleic acid analysis for the predetermined part may be generated separately.

[0137] In addition, the test result report may also include other quality information. Other quality information refers to quality information provided in conventional genome medical tests, for example, quality information obtained based on the entire nucleic acid sequence data of the analysis target region.

[0138] As other quality information, for example, the total number of reads obtained, the mapping rate, the repetition rate, the homogeneity, the statistical representative value of the depth of the analysis object area, the degree distribution of the depth frequency of the analysis object area, the degree distribution of the average quality score of the reads, the degree distribution of the length of the reads, etc. can be cited. "Mapping rate" refers to the proportion of the number of reads mapped to the analysis object area in the total reads. "Repetition rate" refers to the proportion of the number of reads from the same amplification area among the reads mapped to the analysis object area. "Homogeneity" refers to the proportion of the area in the analysis object area where the number of mapped reads is greater than a predetermined value. "Deep frequency distribution" refers to a histogram that sums the number of reads mapped to each base in the analysis object area, with the position of the base and the depth of the base as two axes. "Degree distribution of average quality score of reads" refers to a histogram that uses the average value of the quality score of each read and the number of reads representing the average value as two axes. The “frequency distribution of read lengths” refers to a histogram having the length of the read (number of bases) and the number of reads having the length as two axes.

[0139] When the variation detected in step S22 includes a variation detected in a site not listed in the quality information table, the test result report may also include information on the quality of nucleic acid analysis for that site (eg, depth information).

[0140] Reference Figure 4 In step S25 , the control unit 101 stores the inspection result report in the report table of the storage unit 105 .

[0141] (The user decides the intended location)

[0142] In a further embodiment, the user can determine the predetermined location. The user may also be a user of the information processing device 10 in the inspection destination facility 300. The user of the information processing device 10 may be, for example, the inspection manager of the inspection destination facility 300. In this embodiment, the predetermined location is determined based on the information input by the user. Fig.10 , describing an example in which a user of the information processing device 10 determines a predetermined part and analyzes the read length. In the present embodiment, in the quality indicator table 109 of the storage unit 105, for example, a quality indicator table that merges the quality indicator tables shown in Tables 4 to 6 is stored. In step S51, the control unit 101 selects a predetermined part with reference to the quality indicator table 109 based on information input by the user operating the input unit 103. The input of information by the user can also be performed via a screen displayed on the output unit 104 such as a display or a touch panel. The details of steps S52 to S56 are the same as those of Figure 4 The contents described in steps S21 to S25 of are the same. In addition, the user is not particularly limited. For example, the user may also be a user of the data sending and receiving device 40 in the inspection source facility 200. The user of the data sending and receiving device 40 may be, for example, a medical staff such as a doctor who is responsible for the subject. The operation input to determine the predetermined part is the same regardless of the user of any facility. In the case where the user is a user of the data sending and receiving device 40, in step S51, the control unit 101 receives information input by the user via the screen displayed on the data sending and receiving device 40 via the network 400.

[0143] Reference Fig.11A , an example of inputting classification information and selecting a predetermined part in screen D1 is described. In D11 of screen D1, attribute information of a biomarker is displayed as classification information so as to be selectable. For example, classification information is input by selecting attribute information of a biomarker from a pull-down menu. When classification information is input to D11, the control unit 101 reads out information related to a predetermined part corresponding to the classification information from the storage unit 105. Then, the read information related to the predetermined part is displayed in D12. The user selects one or more predetermined parts displayed in D12 by clicking, etc., and clicks a setting button in D13, so that the information of the selected predetermined part is stored in the storage unit 105. In the case where the user is a user of the data transmission and reception device 40 of the request source facility 200, the information of the selected predetermined part is sent to the information processing device 10 via the network 400 together with the request information.

[0144] Reference Fig. 11B, an example of inputting classification information and sub-classification information and selecting a predetermined part in screen D2 is described. In D21 of screen D2, CDx marker is selected as classification information. In this case, in D22, information of countries / regions where CDx markers are recognized is displayed as sub-classification information, for example. When classification information and sub-classification information are input, the control unit 101 reads information related to the predetermined part corresponding to these information from the storage unit 105, and displays the read information related to the predetermined part in D23. The user selects one or more predetermined parts displayed in D23 by clicking, etc., and clicks the setting button of D24, so that the information of the selected predetermined part is stored in the storage unit 105. In this way, the CDx marker recognized in the predetermined country / region can be set as the predetermined part from the analysis target area. In addition to the country / region, the sub-classification information may also be the name of the disease, the name of the therapeutic drug, etc., to which the CDx examination is applied.

[0145] The classification information may be other than the attribute information of the biomarker. Fig. 11C In D31 of screen D3, as classification information, not only the attribute information of the biomarker but also disease information, drug information, etc. are displayed optionally. In D31 of screen D3, the level of evidence is selected as the classification information. In this case, in D32, the categories of the level of evidence (for example, Lv A, Lv B, and Lv C, etc.) are displayed optionally as sub-classification information. When the classification information and sub-classification information are input, the control unit 101 reads out information related to the predetermined part corresponding to these information from the storage unit 105, and displays the read information related to the predetermined part in D33. The user selects one or more predetermined parts displayed in D33 by clicking, etc., and clicks the setting button of D34, so that the information of the selected predetermined part is stored in the storage unit 105.

[0146] Alternatively, the user may input an arbitrary area from the analysis target area to determine the predetermined portion. Fig.11D , in D41 of screen D4, "arbitrary selection" is selected as classification information. In this case, in D42, a text box for inputting position information such as chromosome number (Chr), base number (Pos_Start and Pos_End) on the chromosome sequence is displayed. The user inputs the position information of one or more bases desired as a predetermined position from the base sequence of the analysis target area into the text box. After inputting the position information, the user clicks the setting button of D43, and the input information of the predetermined position is stored in the storage unit 105.

[0147] (Detection of somatic variants without matched paired testing)

[0148] As Figure 4A further embodiment of step S22 of the present invention describes the process of detecting a variation without a matched pair check. In this case, a non-tumor specimen is not used, and the read length obtained from a library sample prepared from a tumor specimen is used as tumor sequence data. Fig.12 In step S61, the control unit 101 reads the 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 there is a site in the tumor sequence data that is inconsistent with the reference sequence. When the control unit 101 determines that the tumor sequence data is inconsistent with the reference sequence, the process proceeds to step S63. Fig.12 In the process of processing, if there is a site that is inconsistent with the reference sequence, it is determined that the site is a genetic mutation of the tumor tissue. In step S62, if the tumor sequence data is consistent with the reference sequence, the control unit 101 ends the processing. In this case, it is considered that there is no mutation in the tumor sequence data.

[0149] 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 adds annotations to the detected mutation based on the search results. Figure 5 The contents described in steps S37 and S38 are the same as those in step S37 and S38. Through the processing of steps S61 to S64, the control unit 101 obtains information on genetic mutations in the analysis target region as a result of mutation detection in step S22.

[0150] As Figure 4 A further embodiment of step S23 will be described to explain the process of obtaining the depth information T of the predetermined part based on the tumor sequence data. Fig.13 In step S71, the control unit 101 reads the alignment result of the tumor sequence data and the reference sequence obtained in step S61. In step S72, the control unit 101 refers to the alignment result of the tumor sequence data and the reference sequence, and obtains depth information T based on the number of second reads corresponding to the first read corresponding to the predetermined part of the analysis target area. The depth information T is preferably the depth of each base at the predetermined part. In step S73, the control unit 101 stores the depth information T at the predetermined part in the storage unit 105. Then, the control unit 101 ends the process of obtaining the depth information of the predetermined part, and the process enters step S74. Figure 4 Step S24.

Claims

1. A method of controlling an information processing device for analyzing a sequence of a nucleic acid obtained from a sample of a subject, wherein: include: A step of obtaining a detection result of a variation in an analysis target region in the sequence of the nucleic acid based on a plurality of first reads read by a sequencer; A step of generating information related to 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 in the first read corresponding to the predetermined site; as well as A process of outputting the information related to the quality regardless of whether or not there is a variation in the predetermined portion.

2. The method according to claim 1, wherein: The method further includes a step of outputting a detection result of a variation in the analysis target region.

3. The method according to claim 1, wherein: The method further includes a step of accepting a selection of the predetermined portion from the analysis target region.

4. The method according to claim 3, wherein: In the step of accepting the selection, input of information related to the predetermined portion is accepted, and the predetermined portion is set based on the input information.

5. The method according to claim 1, wherein: The information on the quality is generated for each of the plurality of predetermined sites selected from the base sequence of the analysis target region.

6. The method according to claim 1, wherein: The predetermined portion is composed of one base or two or more consecutive bases in the base sequence of the analysis target region.

7. The method according to claim 1, wherein: The predetermined site includes a site where a mutation is likely to occur.

8. The method according to claim 7, wherein: The variation that may occur in the predetermined portion is a variation related to the diagnosis or treatment of a disease in the analysis target region.

9. The method according to claim 8, wherein: The variation associated with the diagnosis or treatment of the disease is (1) Variants known to be associated with the effects and / or side effects of a drug, (2) variants known to be associated with disease status, onset and / or prognosis, and (3) Variants for which the level of evidence indicating association with diagnosis or treatment is above a predetermined level At least 1 of .

10. The method according to claim 9, wherein: The mutation described in (1) above 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 that serves as a malignancy marker, a mutation that serves as a prognosis prediction marker, a mutation that serves as a disease risk marker, or a mutation that serves as a disease risk marker.

12. The method according to claim 9, wherein: The level of evidence described in (3) is at least one level of evidence selected from the group consisting of tumorigenicity evidence, disease predisposition association evidence, treatment effect prediction evidence, diagnosis evidence, or prognosis prediction evidence.

13. The method according to claim 8, wherein: The variation associated with the diagnosis or treatment of a disease is at least one selected from the biomarkers described in the tables shown in FIG. 6A to FIG. 6C .

14. The method according to claim 1, wherein: The predetermined site is a site selected from the base sequence of the analysis target region based on information in a mutation information database that accumulates information on known genetic mutations.

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

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

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

18. The method according to claim 15, wherein: The information recorded in (3) is an index value assigned to the second read length and indicating the correctness of the mapping.

19. The method according to claim 1, wherein: The information on the quality and the information on the predetermined portion are associated with each other and output.

20. The method according to claim 1, wherein: In the step of outputting the information related to the quality, a quality management report including information related to the quality of the nucleic acid analysis of the predetermined site is generated and output.

21. The method according to claim 2, wherein: In the step of outputting the information related to the quality, an analysis result report including a detection result of a variation in the analysis target region is generated and output.

22. The method according to claim 1, wherein: The analysis target region is a part of a genomic region including a whole genomic region, a whole exosome region, or at least one target gene.

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

24. An information processing device for analyzing a sequence of a nucleic acid obtained from a sample of a subject, wherein: The information processing device includes a control unit and an output unit. The control unit performs: A step of obtaining a detection result of a variation in an analysis target region in the sequence of the nucleic acid based on a plurality of first reads read by a sequencer; A step of generating information related to 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 in the first read corresponding to the predetermined site; as well as A step of outputting the information on the quality to the output unit regardless of whether or not there is a variation in the predetermined portion.

25. A computer program for analyzing a sequence of a nucleic acid obtained from a sample of a subject, wherein: The computer program is recorded on a computer-readable medium and causes the computer to execute: A step of obtaining a detection result of a variation in an analysis target region in the sequence of the nucleic acid based on a plurality of first reads read by a sequencer; A step of generating information related to 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 in the first read corresponding to the predetermined site; as well as A process of outputting the information related to the quality regardless of whether or not there is a variation in the predetermined portion.

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