Automatic interpretation and analysis methods, devices, equipment, and storage media for sequencing data

Abstract

This invention belongs to the field of automated bioinformatics analysis technology, and discloses an automatic interpretation and analysis method, device, equipment, and storage medium for sequencing data. The method includes: automatically interpreting sequencing data according to rule expressions set by quality control rules to obtain quality control results; if the quality control results are all passed, displaying a sample list and the target variants obtained after double-layer filtering of selected samples in the sample list by rule expressions set by data filtering rules and report rules; extracting the elements required for the report; and automatically filling in and generating a report for the target batch of samples based on the elements. Thus, by customizing quality control rule settings, filtering rule settings, and report rule settings, automatic interpretation of quality control and automatic screening of variants can be achieved, which can improve the degree of automated interpretation, improve analysis efficiency, reduce reliance on manual interpretation, and reduce the error rate of report interpretation analysis.

Description

Technical Field

[0001] This invention belongs to the field of automated bioinformatics analysis technology, specifically relating to an automated interpretation and analysis method, apparatus, equipment, and storage medium for sequencing data. Background Technology

[0002] High-throughput sequencing, also known as next-generation sequencing (NGS) technology, is now widely used in fields such as oncology, genetic diseases, infectious diseases, and non-invasive prenatal testing. Its application in tumor diagnosis and treatment is an important part of precision medicine.

[0003] High-throughput sequencing can detect several types of variants, including single nucleotide variants (SNVs), insert-deletion mutations (Indels), and structural variants (SVs). Indels are small insertions or deletions (<50 bp) in the genome. Structural variants mainly include copy number variants (CNVs), flips or transversions within a chromosome, and inter-chromosome translocations. Copy number variants are variations in DNA fragments ranging from 50 bp to several MB in size, including deletions, insertions, inversions, and duplications. Gene fusion is a chromosomal rearrangement where two or more gene coding regions connect to form a new chimeric gene, producing a new fusion protein. Gene fusion can lead to abnormal protein function or altered expression levels, causing a range of diseases such as chronic myeloid leukemia and lung adenocarcinoma. In addition, NGS data of tumors can also be used to analyze tumor markers such as microsatellite instability (MSI) and tumor mutational burden (TMB).

[0004] Traditional NGS data analysis can be divided into primary, secondary, and tertiary analyses. Primary analysis utilizes sequencing technology to convert fluorescence signals into four-base signals. This primarily involves Basecall software using base interpretation techniques and algorithms to identify base types from the raw image, writing the results into a .cal file, and ultimately generating a sequencing report and FASTQ data. The workflow is essentially the same. Secondary analysis builds upon primary analysis, performing more in-depth data processing, including sequence quality control (removing low-quality sequences and adapter sequences), sequence alignment, variant screening, and annotation. Secondary analysis requires different analytical methods depending on the specific analytical purpose and also necessitates the integration of different databases for annotation. Primary and secondary analyses are performed by bioinformatics analysts, while tertiary analysis involves further variant screening by bioinformatics analysts, followed by further analysis and interpretation of variants by report interpreters in conjunction with clinical information.

[0005] The NGS dataset is large in volume, and the data analysis workflow is complex. It encompasses a wide variety of analyzable variants, involving steps such as data filtering, sequence alignment, variant annotation, variant screening, variant classification, and related quality control. Therefore, a professional and systematic data analysis workflow is necessary. These workflows are often developed in-house by laboratories, are complex, and require different analytical methods and variant screening procedures depending on the specific application, the type of variant being detected, and the specific testing items. All of these factors place high demands on bioinformatics analysts and data interpretation report providers.

[0006] In summary, compared to traditional PCR testing, NGS data analysis has more quality control parameters. After bioinformatics analysis and statistical quality control information, manual interpretation is required. However, the existing analysis process for NGS data is complex, inefficient, and lacks automation, leading to over-reliance on manual interpretation. Furthermore, the probability of errors in manual analysis by data interpretation personnel is relatively high. Summary of the Invention

[0007] The purpose of this invention is to provide an automated interpretation and analysis method, apparatus, device, and storage medium for sequencing data, which can improve the degree of automated interpretation, increase analysis efficiency, reduce reliance on manual interpretation, and lower the error rate of interpretation report analysis.

[0008] The first aspect of this invention discloses an automatic interpretation and analysis method for sequencing data, comprising:

[0009] In response to the first data analysis command, the corresponding first data analysis interface is displayed;

[0010] Based on the target batch sample selected on the first data analysis interface, the sequencing data of the target batch sample is determined;

[0011] According to the quality control rules, the corresponding rule expressions are set to automatically perform quality control interpretation on the sequencing data of the target batch of samples, and obtain the quality control results of the target batch of samples;

[0012] If the quality control results are all passed, and a click command for the batch is detected, the user will be redirected to the second data analysis interface.

[0013] The second data analysis interface displays a sample list and related information about the target variant. The target variant is a variant site obtained by filtering the selected samples in the sample list through a two-layer rule expression of data filtering rule setting and reporting rule setting. The related information includes at least the unique identifier of the target variant, whether the variant is reported, the interpretation result of the variant, and the interpretation of the result.

[0014] In response to the submission command entered on the second data analysis interface, the relevant information of the target mutation is submitted to the result entry interface. The result entry interface captures the elements required for the report and automatically fills in and generates a report for the target batch of samples based on the elements. The elements include at least the mutated gene, the mutated site, the mutated frequency, and the mutated interpretation.

[0015] In some embodiments, after automatically performing quality control interpretation on the sequencing data of the target batch of samples according to the corresponding rule expression set according to the quality control rules, and obtaining the quality control results of the target batch of samples, the method further includes:

[0016] In response to a click command targeting the entry point of the quality control analysis interface, enter the quality control analysis interface;

[0017] The quality control analysis interface displays specific information about the quality control results, including the quality control rules and corresponding values ​​for blank quality control, negative quality control, positive quality control, and internal sample control.

[0018] In some embodiments, according to the quality control rules, a corresponding rule expression is set to automatically perform quality control interpretation on the sequencing data of the target batch of samples, and the quality control results of the target batch of samples are obtained, including:

[0019] According to the quality control rules, set the variable names in the corresponding rule expressions to match the sequencing data of the target batch of samples with the first target value in the off-machine data table;

[0020] Based on the quality control rules, set the corresponding rule expressions, compare and perform logical calculations on the first target data value, and obtain the quality control results of the target batch samples.

[0021] In some embodiments, before displaying the corresponding first data analysis interface in response to the first data analysis instruction, the method further includes:

[0022] In response to quality control setting commands, the corresponding quality control setting interface is displayed;

[0023] The system detects the quality control parameter setting instructions for the enabled quality control types on the quality control settings interface and configures the corresponding quality control parameters for each enabled quality control type.

[0024] In the rule configuration interface of each of the quality control parameters, the header of the offline quality control information table imported by the rule configuration interface is received. After successful import, the corresponding column of the header is displayed in the name column of the rule configuration interface.

[0025] The system detects the quality control switch instructions for each name in the name column. If the quality control switch instruction for any name is on, the system completes the quality control rule setting for that name based on the input.

[0026] In some embodiments, the quality control rule settings corresponding to the name are completed based on the input, including:

[0027] Upon receiving the click command of the edit button corresponding to the name, a rule definition dialog box corresponding to the name will pop up; the rule expression entered in the rule definition dialog box corresponding to the name will be detected to complete the quality control rule setting corresponding to the name.

[0028] In some embodiments, before displaying the corresponding first data analysis interface in response to the first data analysis instruction, the method further includes:

[0029] In response to data analysis configuration commands, the corresponding data analysis configuration interface is displayed;

[0030] Clicking the rule configuration entry on the data analysis configuration interface will bring up a data filtering rule definition dialog box. The dialog box will then be used to check the rule expression entered in the data filtering rule definition dialog box to complete the data filtering rule settings.

[0031] In some embodiments, before displaying the corresponding first data analysis interface in response to the first data analysis instruction, the method further includes:

[0032] In response to project configuration commands, the corresponding project configuration interface is displayed;

[0033] Based on the search factors entered in the project configuration interface, the corresponding detection project information is output;

[0034] The system detects a click command on the edit button for the detected item information and pops up an item details configuration dialog box.

[0035] The system detects the selection instruction for a bioinformatics file of a certain target variant type in the project details configuration dialog box, adds that target variant type as a variant type that needs to be reported for the detection project, and displays the entry point for the reporting rule settings of the target variant type.

[0036] The system detects a click command on the entry point for setting the reporting rule for the target mutation type, which pops up a dialog box for setting the reporting rule for the target mutation type. The system then detects the rule expression entered in the dialog box to complete the setting of the reporting rule.

[0037] A second aspect of this invention discloses an automatic interpretation and analysis device for sequencing data, comprising:

[0038] The first display unit is used to display the corresponding first data analysis interface in response to the first data analysis command;

[0039] The determining unit is used to determine the sequencing data of the target batch sample based on the target batch sample selected on the first data analysis interface.

[0040] The interpretation unit is used to set corresponding rule expressions according to the quality control rules, automatically interpret the sequencing data of the target batch of samples for quality control, and obtain the quality control results of the target batch of samples.

[0041] The jump unit is used to jump to the second data analysis interface if the quality control results are all passed and a click command for the batch is detected.

[0042] The second display unit is used to display a sample list and related information about the target variant on the second data analysis interface. The target variant is a variant site obtained by filtering the selected samples in the sample list through a two-layer rule expression of data filtering rule setting and reporting rule setting. The related information includes at least the unique identifier of the target variant, whether the variant is reported, the interpretation result of the variant, and the interpretation of the result.

[0043] The submission unit is used to submit the relevant information of the target mutation to the result entry interface in response to the submission command input on the second data analysis interface.

[0044] The report generation unit is used to capture the required elements of the report form from the result entry interface and automatically fill in and generate the report form for the target batch of samples based on the elements; wherein, the elements include at least the mutated gene, mutated site, mutated frequency, and mutated interpretation.

[0045] A third aspect of the present invention discloses an electronic device, including a memory storing executable program code and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the automatic interpretation and analysis method for sequencing data disclosed in the first aspect.

[0046] A fourth aspect of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the automatic interpretation and analysis method for sequencing data disclosed in the first aspect.

[0047] The beneficial effects of this invention are that, based on the rule expressions set in the quality control rules, the sequencing data of the target batch of samples is automatically interpreted for quality control, and the quality control results are obtained. If the quality control results are all passed, a sample list is displayed, along with the target variants obtained after double-layer filtering of the selected samples in the sample list using the rule expressions set in the data filtering rules and the report rules. The necessary elements for the report are extracted from the relevant information of the target variants, and the report for the target batch of samples is automatically generated based on the elements. The elements include at least the variant gene, variant site, variant frequency, and variant interpretation. Thus, by customizing the quality control rule settings, filtering rule settings, and report rule settings, automatic interpretation of quality control and automatic screening of variants can be achieved, which can improve the degree of automated interpretation, improve analysis efficiency, and reduce reliance on manual interpretation, thereby reducing the error rate of report interpretation analysis. Attached Figure Description

[0048] The accompanying drawings illustrate specific examples of the technical solutions described in this invention and, together with the detailed embodiments, form part of the specification, serving to explain the technical solutions, principles, and effects of this invention.

[0049] Unless otherwise specified or defined, the same reference numerals in different figures represent the same or similar technical features, and different reference numerals may be used to represent the same or similar technical features.

[0050] Figure 1 This is the overall architecture of the automatic interpretation and analysis system disclosed in the embodiments of the present invention;

[0051] Figure 2 This is a flowchart illustrating the overall configuration and analysis process of the high-throughput sequencing detection system disclosed in this embodiment of the invention.

[0052] Figure 3 This is an example diagram of the data analysis configuration interface disclosed in an embodiment of the present invention;

[0053] Figure 4 This is an example diagram of the project configuration interface disclosed in an embodiment of the present invention;

[0054] Figure 5 This is an example diagram of the project details configuration dialog box disclosed in an embodiment of the present invention;

[0055] Figure 6 This is an example diagram of the report rule setting dialog box disclosed in an embodiment of the present invention;

[0056] Figure 7 This is a flowchart of the automatic interpretation and analysis method for sequencing data disclosed in the embodiments of the present invention;

[0057] Figure 8 This is an example diagram of the quality control result interpretation interface disclosed in the embodiments of the present invention;

[0058] Figure 9 This is a schematic diagram of the structure of the automatic sequencing data interpretation and analysis device disclosed in the embodiments of the present invention;

[0059] Figure 10 This is a schematic diagram of the structure of the electronic device disclosed in the embodiments of the present invention.

[0060] Explanation of reference numerals in the attached figures:

[0061] 901, First display unit; 902, Determination unit; 903, Judgment unit; 904, Jump unit; 905, Second display unit; 906, Submission unit; 907, Report generation unit; 1001, Memory; 1002, Processor. Detailed Implementation

[0062] Unless otherwise specified or defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. When combined with the technical solutions of the invention in a real-world scenario, all technical and scientific terms used herein may also have meanings corresponding to the purpose of achieving the technical solutions of the invention. The terms "first," "second," etc., used herein are merely for distinguishing names and do not represent a specific number or order. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0063] It should be noted that when a component is considered "fixed" to another component, it can be directly fixed to the other component or there can be an intervening component; when a component is considered "connected" to another component, it can be directly connected to the other component or there can be an intervening component; when a component is considered "mounted" on another component, it can be directly mounted on the other component or there can be an intervening component; when a component is considered "placed" on another component, it can be directly placed on the other component or there can be an intervening component.

[0064] Unless otherwise specified or defined, the terms "described" or "the" as used herein refer to the technical features or technical content mentioned or described prior to the relevant section, which may be the same as or similar to the technical features or technical content mentioned herein. Furthermore, the terms "comprising" and "having," and any variations thereof, as used herein, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0065] This invention discloses an automated interpretation and analysis method for sequencing data, which can be implemented through computer programming. The execution subject of this method can be an electronic device such as a computer, laptop, or tablet, or an automated interpretation and analysis device for sequencing data embedded in an electronic device; this invention does not limit this. To facilitate understanding of this invention, specific embodiments will be described in more detail below with reference to the accompanying drawings.

[0066] Taking an electronic device as the executing entity as an example, the electronic device is equipped with an automatic interpretation and analysis system for sequencing data. The overall architecture of this automatic interpretation and analysis system is as follows: Figure 1 As shown, it includes the user access layer, application layer, interface layer and persistence layer. Figure 1 The orange-highlighted sections represent the main innovative modules involved in this method: quality control, data analysis, results reporting, and their corresponding rule engine and knowledge base retrieval modules. This automated interpretation and analysis system is a high-throughput sequencing detection system, and its configuration and analysis workflow are as follows: Figure 2 As shown.

[0067] Before executing the automatic interpretation and analysis method of sequencing data of the present invention, probe subset configuration can be completed first based on human-computer interaction, specifically including: responding to probe subset configuration instructions, displaying the corresponding probe subset configuration interface; detecting the selection instruction for a certain probe subset on the probe subset configuration interface, and configuring the corresponding probe subset according to the selection instruction.

[0068] Furthermore, before executing the automated interpretation and analysis method for sequencing data according to this invention, the rule engine can be set up through human-computer interaction. The rule engine can dynamically configure rules by importing the sample download file template. Each rule includes a rule name and a filtering rule expression with syntactic constraints. After the samples are downloaded, logical calculations and comparison calculations are performed to achieve an automated process for quality control analysis and data analysis. The rule engine settings mainly include quality control rule settings, data filtering rule settings, and reporting rule settings.

[0069] (1) Quality control rule setting, including the following steps S11 to S14 (not shown):

[0070] S11. In response to the quality control setting command, display the corresponding quality control setting interface.

[0071] After executing step S11 and before executing step S12, quality control type settings can also be executed, including: detecting the enable or disable commands for each quality control type on the quality control setting interface, and performing corresponding enable or disable operations on each quality control type; wherein, each quality control type includes blank quality control (NTC), negative quality control (NC) and positive quality control (PC).

[0072] S12. On the quality control settings interface, commands are provided to set the quality control parameters for each enabled quality control type. These parameters include sample gender, sequencing quality, sequencing depth and coverage, and expected positive control results.

[0073] Due to the massive volume of NGS data and the complexity of quality control parameters, it is impossible to achieve the desired results using the "first-generation quality control" approach. Therefore, a new quality control setting method is proposed for sequencing data, which includes settings for sample gender, sequencing quality (QC), sequencing depth and coverage, and expected positive control results (Result-Filter). Batch quality control can be performed separately for sample gender, sequencing quality, sequencing depth and coverage, and expected positive control results. During the quality control parameter configuration process, first set the name, enable the quality control type, and then select Gender, QC, Depth, and Result-Filter in sequence.

[0074] S13. In the rule configuration interface of each quality control parameter, receive the header of the offline quality control information table imported from the rule configuration interface. After successful import, display the corresponding column of the header in the name column of the rule configuration interface.

[0075] Click the "Import Quality Control File" button to import the header of the corresponding offline quality control information table. After successful import, the corresponding column of the header will be displayed in the "Name" column.

[0076] S14. Detect the quality control switch instructions for each name in the name column. If the quality control switch instruction for any name is on, complete the quality control rule settings corresponding to that name based on the input.

[0077] The process of setting the quality control rule corresponding to the name based on input includes: receiving a click instruction from the edit button corresponding to the name and popping up the rule definition dialog box corresponding to the name; detecting the rule expression entered in the rule definition dialog box corresponding to the name to complete the quality control rule setting corresponding to the name.

[0078] In other words, users can turn on the "Quality Control" button for any name. If turned on, quality control is confirmed, and then the "Edit" button can be clicked to bring up the rule definition dialog box for that name. The "Variables," "Operations," and "Parameters" are set sequentially. This section also allows for the creation of custom rule expressions; multiple rule expressions can be set and connected using "and" or "or". For each quality control parameter—Gender, QC, Depth, and Result-Filter—the corresponding quality control rules are set in the same way (i.e., steps S13-S14).

[0079] The implementation principle of the rule expression is as follows: Import the download file template, with the template header as an optional variable. Configure the rule expression as: "variable a>'parameter a'". Replace the variable in the rule expression with the corresponding variable value from the download file, and then perform a comparison calculation. Here, ">" is the comparison operator, meaning greater than. The single quotes following the comparison operator enclose a parameter value. The variable value is compared with the parameter to obtain a True or False result. The comparison operators include eight operations: "=" (equal to), "!=" (not equal to), ">" (greater than), "<" (less than), ">=" (greater than or equal to), "<=" (less than or equal to), "in" (included in), and "not in" (not included in).

[0080] Regular expressions also support logical operations, including "and" and "or". For example, in the regular expression "variable a>='parameter a'and variable b<='parameter b'", the logical operator "and" is true only if both subexpressions "variable a>='parameter a'" and "variable b<='parameter b'" are true; otherwise, it is false. In the regular expression "variable a>='parameter a'or variable b<='parameter b'", the logical operator "or" is true if at least one subexpression is true, and false if all subexpressions are false.

[0081] (2) Setting data filtering rules, including the following steps S21 to S22 (not shown):

[0082] S21. In response to the data analysis configuration command, display the corresponding data analysis configuration interface.

[0083] After the corresponding data analysis configuration interface is displayed, you can also: select NGS sequencing as the detection process on the data analysis configuration interface, receive imported data of different variant types, and view the various table names of the imported data in the right-hand list interface. For example, selecting NGS sequencing as the detection process, such as "PCRBase," on the data analysis configuration interface; adding a new analysis file by importing data tables of different variant types such as SNV / Indel, CNV, and TMB into the analysis file; the right-hand list interface will then display the various table names of the imported data, such as... Figure 3 As shown.

[0084] S22. Clicking the rule configuration entry on the detection data analysis configuration interface will bring up the data filtering rule definition dialog box. The rule expression entered in the data filtering rule definition dialog box will be detected to complete the data filtering rule settings.

[0085] In the pop-up data filtering rule definition dialog box, you can set "variable", "operation" and "parameter" in sequence. You can also write your own rule expressions in this part. You can set multiple rule expressions and connect them in the form of "and" or "or".

[0086] (3) Reporting rule settings, including the following steps S31 to S35 (not shown):

[0087] S31. In response to the project configuration command, display the corresponding project configuration interface.

[0088] S32. Based on the search factors entered in the project configuration interface, output the corresponding detection project information.

[0089] The testing project information includes the project code, project name, report template, result template, probe group, data filtering rules, and reporting rules.

[0090] S33. Detect the click command of the edit button for the detection item information, and pop up the item details configuration dialog box.

[0091] S34. In the Detection Item Details Configuration dialog box, the selection command for a bioinformatics file of a certain target variant type adds the target variant type as a variant type that needs to be reported for this detection item, and displays the entry point for the reporting rule settings of the target variant type.

[0092] S35. Detect the click command for the entry of the reporting rule setting for the target variant type, pop up the reporting rule setting dialog box for the target variant type, and detect the rule expression entered in the reporting rule setting dialog box for the target variant type to complete the reporting rule setting.

[0093] After the data filtering rules set in steps S21 to S22, since there are many genes and variants detected by the probe subgroup, it is still necessary to screen and filter variants again on a per-detection-item basis.

[0094] Therefore, you can search for the corresponding detection project by entering search factors such as detection group, probe group, project code, or project name in the project configuration interface. Figure 4 As shown. Then you can click the edit button to bring up the project details configuration dialog box, as shown... Figure 5 As shown, you can click "Add", select the "Bioinformatics file" corresponding to a specific target variant type, add it as the variant type that needs to be reported for this detection project, and then in the pop-up window... Figure 6 In the report rule settings dialog box shown, set "Variables", "Operations" and "Parameters" in sequence. You can also write your own rule expressions in this part. You can set multiple rule expressions and connect them in the form of "and" or "or". The setting method is the same as the data filtering rule settings.

[0095] like Figure 7 As shown, the automated interpretation and analysis method for this sequencing data includes the following steps 110–160:

[0096] 110. In response to the first data analysis command, display the corresponding first data analysis interface.

[0097] 120. Based on the target batch sample selected on the first data analysis interface, determine the sequencing data of the target batch sample.

[0098] In this embodiment of the invention, the analysis object is high-throughput sequencing data that has undergone bioinformatics level I and II analysis. These sequencing data are named folders by experiment number and are uniformly placed on a shared cloud drive for automatic retrieval. Furthermore, the output format of bioinformatics level II analysis quality control information and variation information is standardized. Each sample undergoes bioinformatics level I and II analysis, and uniformly outputs result files such as qc, depth, gender, and result.

[0099] 130. Set the corresponding rule expression according to the quality control rules, and automatically perform quality control interpretation on the sequencing data of the target batch of samples to obtain the quality control results of the target batch of samples.

[0100] Users can select the target batch of samples to be analyzed on the data analysis interface, successfully capture the sequencing data of the target batch of samples, and then automatically perform quality control interpretation on the sequencing data by setting the corresponding rule expression through quality control rules to obtain the quality control results of the target batch of samples, which include two parts: external batch control results and internal sample control results, both of which are displayed as "pass" or "fail".

[0101] Specifically, step 130, the automatic quality control interpretation can include the following steps (not shown): 1301-1302.

[0102] 1301. Set the variable names in the corresponding rule expression according to the quality control rules, and match the sequencing data of the target batch of samples with the first target value in the off-line data table.

[0103] 1302. Based on the quality control rules, set the corresponding rule expressions, compare and perform logical calculations on the first target data value, and obtain the quality control results of the target batch of samples.

[0104] In other words, by setting the variable names in the corresponding rule expression of the quality control rules, the sequencing data of the target batch of samples to be analyzed is quickly matched with the first target value in the data table. The comparison and logical calculations are performed according to the corresponding rule expression (REL) set in the quality control rules, outputting a True or False quality control result for both external batch control and internal sample control. True represents "pass," and False represents "fail." Users can click "pass" or "fail" to enter the quality control analysis interface to view the specific information of the "pass" or "fail" quality control interpretation, such as... Figure 8 As shown.

[0105] Optionally, after obtaining the quality control results of the target batch of samples, the method further includes: responding to a click command for the entry point of the quality control analysis interface, entering the quality control analysis interface; displaying specific information of the quality control results on the quality control analysis interface, including the quality control rules and corresponding values ​​of blank quality control, negative quality control, positive quality control and internal sample control.

[0106] 140. If the quality control results are all passed and a click command for the batch is detected, jump to the second data analysis interface.

[0107] Once all quality control checks are passed, click "Batch on Machine" to proceed to the next data analysis interface, i.e., the second data analysis interface.

[0108] 150. Display the sample list and relevant information of the target variant on the second data analysis interface. The target variant is the variant site obtained after the selected sample in the sample list has been filtered by the rule expression of the data filtering rule setting and the reporting rule setting. The relevant information includes at least the unique identifier of the target variant, whether the variant is reported, the interpretation result of the variant, and the interpretation of the result.

[0109] The left side of the second data analysis interface displays a sample list, while the right side shows the target variants obtained after the selected samples in the list have undergone a two-layer filtering process using rule expressions set by data filtering rules and reporting rules. This two-layer filtering process using rule expressions set by data filtering rules and reporting rules enables automatic variant filtering analysis. Specific implementation methods for automatic variant filtering analysis may include:

[0110] Based on the variable names in the rule expressions of the data filtering and reporting rules, the sequencing data of the selected samples is matched with the second target value in the sequencing data table. Then, based on the rule expressions of the data filtering and reporting rules, the second target value is compared and logically calculated, outputting the sequencing file result row that satisfies the current rule interpretation. This yields the target variants obtained after the selected samples have undergone two-layer screening. These target variants are linked to a knowledge base through unique identifiers, and information such as whether the target variant is reported, the variant interpretation results, and the interpretation of the results are automatically presented, achieving automatic variant screening and analysis.

[0111] 160. In response to the submission command entered on the second data analysis interface, submit the relevant information of the target variant to the result entry interface, capture the required elements of the report on the result entry interface, and automatically fill in and generate the report of the target batch of samples based on the elements; wherein, the elements include at least the variant gene, variant site, variant frequency and variant interpretation.

[0112] After verifying that the automatic variant screening analysis results are correct, you can click the "Submit" button. The target variants and related information selected by the sample will be submitted to the next step, the "Results Entry Interface".

[0113] Example 1

[0114] Taking the JAK2 gene mutation detection project for hematological malignancies as an example, users can first complete the quality control rule settings in the "Probe Subset Configuration" entry on the operation interface, then complete the data filtering rule settings for the hematological malignancies (Leu) probe subset in the "Data Analysis Configuration" entry, and then set the reporting rules for the JAK2 gene mutation detection project. Next, in the "Data Analysis" entry, select the target batch to be analyzed (Runname: 240618_MN00827_0934_A000H7FFWC). After the system retrieves the sequencing data of the corresponding batch from the shared folder, it automatically interprets the quality control results for the batch, obtaining two parts: external batch control and internal sample control. After all results show "Pass", click on the batch to be used: 20240618-00006 to enter the data analysis interface.

[0115] The left side of the analysis interface displays the sample list, while the right side shows the target variants obtained after the selected samples have undergone a two-layer filtering process using data filtering and reporting rules. These target variants are linked to the knowledge base through unique identifiers. Information such as whether a variant is reported, the variant interpretation results, and the explanations are automatically presented, enabling automated variant filtering and analysis. After verifying the results of the automated variant filtering and analysis, click the "Submit" button. The selected target variants and related information are then submitted to the next step, the results entry interface. In the results entry interface, the system automatically extracts the necessary elements from the report, such as the variant gene, variant site, variant frequency, and variant explanation, and automatically generates a report for the target batch of samples. After previewing the report and confirming its accuracy, it can be approved and published.

[0116] In summary, existing conventional high-throughput sequencing solutions require bioinformatics analysts to employ different analytical methods and variant filtering conditions for each test, depending on the testing objective, the scope of genes being tested, and the type of variant. This results in a complex data analysis and variant screening process. Compared to existing workflows, the advantages of this invention are that bioinformatics analysts only need to output quality control information files and variant annotation files in a fixed format, eliminating the need for further variant filtering and screening. The system allows for customized quality control and variant filtering rules, enabling automatic interpretation of quality control information and automatic variant screening. Furthermore, integration with a knowledge base enables automatic variant analysis. This reduces the reliance on bioinformatics analysts for each test, minimizes the probability of errors in manual data interpretation, and makes modifying quality control parameters or variant filtering conditions more convenient and efficient.

[0117] like Figure 9 As shown, this embodiment of the invention discloses an automatic interpretation and analysis device for sequencing data, including a first display unit 901, a determination unit 902, an interpretation unit 903, a jump unit 904, a second display unit 905, a submission unit 906, and a report generation unit 907, wherein...

[0118] The first display unit 901 is used to display the corresponding first data analysis interface in response to the first data analysis command;

[0119] The determining unit 902 is used to determine the sequencing data of the target batch sample based on the target batch sample selected on the first data analysis interface.

[0120] The interpretation unit 903 is used to set the corresponding rule expression according to the quality control rules, automatically interpret the sequencing data of the target batch of samples for quality control, and obtain the quality control results of the target batch of samples.

[0121] Jump unit 904 is used to jump to the second data analysis interface if the quality control results are all passed and a click command for the batch is detected.

[0122] The second display unit 905 is used to display a sample list and related information of the target variant on the second data analysis interface. The target variant is the variant site obtained by double-layer filtering of the selected sample in the sample list through the rule expression of the data filtering rule setting and the reporting rule setting. The related information includes at least the unique identifier of the target variant, whether the variant is reported, the interpretation result of the variant, and the interpretation of the result.

[0123] Submission unit 906 is used to submit relevant information about the target mutation to the result entry interface in response to the submission command entered on the second data analysis interface.

[0124] The report generation unit 907 is used to capture the required elements of the report form from the result entry interface and automatically fill in the report form for the target batch of samples based on the elements; the elements include at least the variant gene, variant site, variant frequency, and variant interpretation.

[0125] Optionally, the aforementioned automatic interpretation and analysis device may further include a quality control analysis unit (not shown), used to automatically interpret the sequencing data of the target batch of samples after the interpretation unit 903 sets the corresponding rule expression according to the quality control rules and obtains the quality control results of the target batch of samples. Then, in response to the click command for the entry of the quality control analysis interface, the device enters the quality control analysis interface. The quality control analysis interface displays the specific information of the quality control results, including the quality control rules and corresponding values ​​of blank quality control, negative quality control, positive quality control and internal sample control.

[0126] Furthermore, the aforementioned interpretation unit 903 is specifically used to match the first target value in the sequencing data of the target batch sample with the first target value in the off-line data table according to the variable name set in the corresponding rule expression of the quality control rules; and to compare, calculate and logically calculate the first target data value to obtain the quality control result of the target batch sample according to the corresponding rule expression set in the quality control rules.

[0127] Optionally, the aforementioned automatic interpretation and analysis device may further include a first setting unit (not shown), used to display a corresponding quality control setting interface in response to a quality control setting command before the first display unit 901 displays the corresponding first data analysis interface in response to the first data analysis command; detect the quality control parameter setting command on the quality control setting interface for the enabled quality control type, and configure the corresponding quality control parameters for each enabled quality control type; in the rule configuration interface of each quality control parameter, receive the header of the offline quality control information table imported from the rule configuration interface, and after successful import, present the corresponding column of the header in the name column of the rule configuration interface; detect the quality control switch command for each name in the name column, and if the quality control switch command for any name is on, complete the quality control rule setting corresponding to that name according to the input.

[0128] Optionally, the aforementioned automatic interpretation and analysis device may further include a second setting unit (not shown), used to display a corresponding data analysis configuration interface in response to a data analysis configuration command before the first display unit 901 displays the corresponding first data analysis interface in response to the first data analysis command; detect a click command on the rule configuration entry on the data analysis configuration interface, pop up a data filtering rule definition dialog box, and detect the rule expression entered in the data filtering rule definition dialog box to complete the data filtering rule setting.

[0129] Optionally, the aforementioned automatic interpretation and analysis device may further include a third setting unit (not shown), used to display a corresponding project configuration interface in response to a project configuration command before the first display unit 901 displays the corresponding first data analysis interface in response to the first data analysis command; output corresponding detection project information based on the search factors input in the project configuration interface; detect click commands on the edit button for the detection project information and pop up a project detail configuration dialog box; detect the selection command for a bioinformatics file of a certain target variant type in the project detail configuration dialog box, add the target variant type as the variant type to be reported for the detection project, and display the reporting rule setting entry for the target variant type; detect click commands on the reporting rule setting entry for the target variant type, pop up a reporting rule setting dialog box for the target variant type, and detect the rule expression input in the reporting rule setting dialog box for the target variant type to complete the reporting rule setting.

[0130] like Figure 10 As shown, an embodiment of the present invention discloses an electronic device, including a memory 1001 storing executable program code and a processor 1002 coupled to the memory 1001;

[0131] The processor 1002 calls the executable program code stored in the memory 1001 to execute the automatic interpretation and analysis method of sequencing data described in the above embodiments.

[0132] This invention also discloses a computer-readable storage medium storing a computer program that causes a computer to execute the automatic interpretation and analysis method for sequencing data described in the above embodiments.

[0133] The purpose of the above embodiments is to reproduce and derive the technical solution of the present invention by way of example, and to fully describe the technical solution, purpose and effect of the present invention. The purpose is to enable the public to have a more thorough and comprehensive understanding of the disclosure of the present invention, and not to limit the scope of protection of the present invention.

[0134] The above embodiments are not an exhaustive list based on the present invention, and there may be many other embodiments not listed. Any substitutions and improvements made without departing from the concept of the present invention are within the protection scope of the present invention.

Claims

1. An automated interpretation and analysis method for sequencing data, characterized in that, include: In response to the first data analysis command, the corresponding first data analysis interface is displayed; Based on the target batch sample selected on the first data analysis interface, the sequencing data of the target batch sample is determined; According to the quality control rules, the corresponding rule expressions are set to automatically perform quality control interpretation on the sequencing data of the target batch of samples, and obtain the quality control results of the target batch of samples; If the quality control results are all passed, and a click command for the batch is detected, the user will be redirected to the second data analysis interface. The second data analysis interface displays a sample list and related information about the target variant. The target variant is a variant site obtained by filtering the selected samples in the sample list through a two-layer rule expression of data filtering rule setting and reporting rule setting. The related information includes at least the unique identifier of the target variant, whether the variant is reported, the interpretation result of the variant, and the interpretation of the result. In response to the submission command entered on the second data analysis interface, the relevant information of the target mutation is submitted to the result entry interface. The result entry interface captures the elements required for the report and automatically fills in and generates a report for the target batch of samples based on the elements. The elements include at least the mutated gene, the mutated site, the mutated frequency, and the mutated interpretation.

2. The automatic interpretation and analysis method for sequencing data as described in claim 1, characterized in that, After setting corresponding rule expressions according to the quality control rules, automatically performing quality control interpretation on the sequencing data of the target batch of samples, and obtaining the quality control results of the target batch of samples, the method further includes: In response to a click command targeting the quality control analysis interface entry, enter the quality control analysis interface; The quality control analysis interface displays specific information about the quality control results, including the quality control rules and corresponding values ​​for blank quality control, negative quality control, positive quality control, and internal sample control.

3. The automatic interpretation and analysis method for sequencing data as described in claim 1, characterized in that, Based on the quality control rules, corresponding rule expressions are set to automatically perform quality control interpretation on the sequencing data of the target batch of samples, and the quality control results of the target batch of samples are obtained, including: According to the quality control rules, set the variable names in the corresponding rule expressions to match the sequencing data of the target batch of samples with the first target value in the off-machine data table; Based on the quality control rules, the corresponding rule expressions are set, and the first target data value is compared, calculated, and logically calculated to obtain the quality control results of the target batch sample.

4. The automatic interpretation and analysis method for sequencing data as described in any one of claims 1 to 3, characterized in that, Before displaying the corresponding first data analysis interface in response to the first data analysis command, the method further includes: In response to quality control setting commands, the corresponding quality control setting interface is displayed; The system detects the quality control parameter setting instructions for the enabled quality control types on the quality control settings interface and configures the corresponding quality control parameters for each enabled quality control type. In the rule configuration interface of each of the quality control parameters, the header of the offline quality control information table imported by the rule configuration interface is received. After successful import, the corresponding column of the header is displayed in the name column of the rule configuration interface. The system detects the quality control switch instructions for each name in the name column. If the quality control switch instruction for any name is on, the system completes the quality control rule setting for that name based on the input.

5. The automatic interpretation and analysis method for sequencing data as described in claim 4, characterized in that, Complete the quality control rule settings corresponding to this name based on the input, including: Upon receiving the click command of the edit button corresponding to the name, a rule definition dialog box corresponding to the name will pop up; the rule expression entered in the rule definition dialog box corresponding to the name will be detected to complete the quality control rule setting corresponding to the name.

6. The automatic interpretation and analysis method for sequencing data as described in any one of claims 1 to 3, characterized in that, Before displaying the corresponding first data analysis interface in response to the first data analysis command, the method further includes: In response to data analysis configuration commands, the corresponding data analysis configuration interface is displayed; Clicking the rule configuration entry on the data analysis configuration interface will bring up a data filtering rule definition dialog box. The dialog box will then be used to check the rule expression entered in the data filtering rule definition dialog box to complete the data filtering rule settings.

7. The automatic interpretation and analysis method for sequencing data as described in any one of claims 1 to 3, characterized in that, Before displaying the corresponding first data analysis interface in response to the first data analysis command, the method further includes: In response to project configuration commands, the corresponding project configuration interface is displayed; Based on the search factors entered in the project configuration interface, the corresponding detection project information is output; The system detects a click command on the edit button for the detected item information and pops up an item details configuration dialog box. The system detects the selection instruction for a bioinformatics file of a certain target variant type in the project details configuration dialog box, adds that target variant type as a variant type that needs to be reported for the detection project, and displays the entry point for the reporting rule settings of the target variant type. The system detects a click command on the entry point for setting the reporting rule for the target mutation type, which pops up a dialog box for setting the reporting rule for the target mutation type. The system then detects the rule expression entered in the dialog box to complete the setting of the reporting rule.

8. An automatic interpretation and analysis device for sequencing data, characterized in that, include: The first display unit is used to display the corresponding first data analysis interface in response to the first data analysis command; The determining unit is used to determine the sequencing data of the target batch sample based on the target batch sample selected on the first data analysis interface. The interpretation unit is used to set corresponding rule expressions according to the quality control rules, automatically interpret the sequencing data of the target batch of samples for quality control, and obtain the quality control results of the target batch of samples. The jump unit is used to jump to the second data analysis interface if the quality control results are all passed and a click command for the batch is detected. The second display unit is used to display a sample list and related information about the target variant on the second data analysis interface. The target variant is a variant site obtained by filtering the selected samples in the sample list through a two-layer rule expression of data filtering rule setting and reporting rule setting. The related information includes at least the unique identifier of the target variant, whether the variant is reported, the interpretation result of the variant, and the interpretation of the result. The submission unit is used to submit the relevant information of the target mutation to the result entry interface in response to the submission command input on the second data analysis interface. The report generation unit is used to capture the required elements of the report form from the result entry interface and automatically fill in and generate the report form for the target batch of samples based on the elements; wherein, the elements include at least the mutated gene, mutated site, mutated frequency, and mutated interpretation.

9. An electronic device, characterized in that, It includes a memory storing executable program code and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the automatic interpretation and analysis method for sequencing data according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program causes a computer to perform the automatic interpretation and analysis method for sequencing data according to any one of claims 1 to 7.

Images