Flow cytometry sequencing analysis method and apparatus, storage medium and computer device

Abstract

Provided are a flow cytometry sequencing analysis method and apparatus, a storage medium and a computer device, relating to the technical field of gene sequencing. After a sample to be analyzed and corresponding analysis requirements and an availability status of each current sequencing instrument are acquired, since a first sequencing instrument using second-generation sequencing technology and a second sequencing instrument using third-generation sequencing technology have different sequencing advantages, a target sequencing instrument can be determined by considering sample characteristics of said sample, the analysis requirements, and the availability status of each sequencing instrument, wherein the target sequencing instrument may be the first sequencing instrument or the second sequencing instrument, or the first sequencing instrument and the second sequencing instrument can also be used for hybrid sequencing, thus providing diversified use scenarios for users, and also improving the sequencing efficiency and sequencing precision to a certain extent; and then, the target sequencing instrument is used to perform sequencing of said sample to obtain a base sequence corresponding to the said sample, the base sequence being a binary sequence.

Description

Flow sequencing analysis method, device, storage medium and computer equipment

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on July 10, 2023, with application number 202310834707.1 and invention name “Flow sequencing analysis method, device, storage medium and computer equipment”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of gene sequencing technology, and in particular to a flow cytometry analysis method, apparatus, storage medium, and computer equipment. Background Art

[0003] Since its invention, DNA sequencing technology has played a crucial role in advancing molecular biology. In 1977, Walter Gilbert and Frederick Sanger invented the first sequencer and used it to sequence the first genome, that of bacteriophage X174, which spanned 5,375 bases. From this point on, humanity gained the ability to explore the genetic nature of life, ushering in the era of genomics. Over the past four decades, sequencing technology has advanced significantly, from first to third generation sequencing. First-generation sequencing, invented by Sanger, remains widely used today, but it can only produce sequences of 700 to 1,000 bases at a time, failing to meet the urgent need for obtaining biological gene sequences in modern scientific development. Next Generation Sequencing (NGS) or second generation sequencing is high-throughput sequencing (HTS), which is a revolutionary change to traditional Sanger sequencing. It solves the limitation of first generation sequencing that it can only determine one sequence at a time. In a single run, it can obtain the sequences of hundreds of thousands to millions of nucleic acid molecules at the same time. Although the second generation sequencing technology has greatly increased the sequencing throughput, the length of the single sequence obtained is very short. To obtain accurate gene sequence information, it depends on high sequencing coverage and accurate sequence splicing technology, which also means that there will be certain errors in the final results. Therefore, researchers have invented the third generation sequencing technology, also known as single molecule sequencing technology. This technology, while ensuring the sequencing throughput, performs de novo sequencing on a single long sequence and can directly obtain nucleic acid sequence information of tens of thousands of bases in length.

[0004] After sequencing is completed using a sequencer using the aforementioned sequencing technologies, supporting genetic sequencing analysis software is required to analyze and interpret the data. Currently, due to the massive amount of genetic data, relatively limited usage scenarios, and a high reliance on servers for analysis, the parallel input of large numbers of samples can easily cause I / O congestion, leading to thread or process suspensions and significantly impacting analysis efficiency and accuracy.

[0005] Summary of the Invention

[0006] The purpose of this application is to solve at least one of the above-mentioned technical defects, especially the technical defects in the existing technology that due to the huge amount of genetic data, the relatively single usage scenarios, the analysis process is highly dependent on the server, and when a large number of samples are input in parallel, it is easy to cause I / O congestion, and the thread or process will be suspended, which greatly affects the analysis efficiency and accuracy.

[0007] The present application provides a flow sequencing analysis method, the method comprising:

[0008] Obtain the samples to be analyzed and the corresponding analysis requirements, as well as the current availability of each sequencer;

[0009] Determining a target sequencer based on the sample characteristics of the sample to be analyzed, analysis requirements, and the current availability of each sequencer, and sequencing the sample to be analyzed using the target sequencer to obtain a base sequence corresponding to the sample to be analyzed, wherein the base sequence is a binary sequence;

[0010] The base sequence is input into the memory, and the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer is called to analyze the base sequence and generate a sequencing report.

[0011] Optionally, the current sequencers include a first sequencer using second-generation sequencing technology and / or a second sequencer using third-generation sequencing technology.

[0012] Optionally, determining a target sequencer based on sample characteristics of the sample to be analyzed, analysis requirements, and current availability of each sequencer includes:

[0013] Inputting the sample characteristics and analysis requirements of the sample to be analyzed into a pre-configured target classification model, and obtaining the type of sequencer applicable to the sample to be analyzed as output by the target classification model; wherein the target classification model is obtained by training using historical analysis samples containing sample characteristics and analysis requirements as training samples, and using the type of sequencer applicable to the training samples as sample labels;

[0014] The target sequencer is determined based on the type of sequencer applicable to the sample to be analyzed and the current idle status of each sequencer.

[0015] Optionally, the training process of the target classification model includes:

[0016] Obtain multiple historical analysis samples that include sample characteristics and analysis requirements, as well as the actual sequencer type applicable to each historical analysis sample, and divide the multiple historical analysis samples into training sets and test sets;

[0017] Inputting the historical analysis samples in the training set into the initial classification model to obtain the predicted sequencer type of the historical analysis samples output by the initial classification model;

[0018] Training the initial classification model with the goal of making the predicted sequencer type closer to the actual sequencer type applicable to the historical analysis samples;

[0019] When the initial classification model meets the preset training conditions, the historical analysis samples in the test set are used to adjust and optimize the trained initial classification model to obtain the final target classification model.

[0020] Optionally, determining a target sequencer based on sample characteristics of the sample to be analyzed, analysis requirements, and current availability of each sequencer includes:

[0021] The sample characteristics and analysis requirements of the sample to be analyzed are respectively compared with the corresponding thresholds, or the analysis requirements of the sample to be analyzed are separately compared with the corresponding thresholds, and the target sequencer is determined based on the comparison results and the current idle status of each sequencer.

[0022] Optionally, comparing the sample characteristics and analysis requirements of the sample to be analyzed with corresponding thresholds respectively, or comparing the analysis requirements of the sample to be analyzed with corresponding thresholds alone, and determining the target sequencer based on the comparison results and the current availability of each sequencer, includes:

[0023] If the analysis requirements of the sample to be analyzed are that there is no sequencing cost requirement or it is lower than a preset cost threshold, the analysis accuracy is greater than a preset accuracy threshold, or there is a detection requirement for a specific function, then the first sequencer and the second sequencer are used as target sequencers, and the sequencing results of the target sequencers are verified by a sequencer using first-generation sequencing technology;

[0024] If the analysis requirement of the sample to be analyzed is that the sequencing cost is lower than the preset cost threshold and the analysis accuracy is higher than the preset accuracy threshold, determining the target sequencer according to the idle status of different types of first sequencers;

[0025] If the analysis requirements of the sample to be analyzed are that the sequencing cost is lower than the preset cost threshold, the analysis accuracy is higher than the preset accuracy threshold, and the sample characteristic of the sample to be analyzed is that the amount of data off the machine is less than the preset data amount threshold, then based on the accuracy and function of the first sequencer and the second sequencer, the sequencer with higher accuracy and function that meets the requirements is selected as the target sequencer. Alternatively, if the first sequencer and the second sequencer have the same accuracy and function, the target sequencer is determined based on the availability of the first sequencer and the second sequencer.

[0026] If the analysis requirements of the sample to be analyzed are that there is no requirement for sequencing cost, the analysis accuracy is less than the preset accuracy threshold, the sequencing time is less than the preset sequencing time, and the analysis environment of the sample to be analyzed is an abnormal environment, then the Nanopore in the second sequencer is selected as the target sequencer.

[0027] Optionally, sequencing the sample to be analyzed by the target sequencer to obtain a base sequence corresponding to the sample to be analyzed includes:

[0028] The sample to be analyzed is sequenced by the target sequencer, and the sequencing result of the target sequencer is converted into a binary sequence according to the sequencing method of the target sequencer to obtain a base sequence corresponding to the sample to be analyzed.

[0029] Optionally, sequencing the sample to be analyzed by the target sequencer and converting the sequencing result of the target sequencer into a binary sequence according to the sequencing method of the target sequencer to obtain a base sequence corresponding to the sample to be analyzed includes:

[0030] If the target sequencer is a first sequencer, the sample to be analyzed is sequenced directly by the first sequencer, and after base recognition is performed on the fluorescent signal obtained by sequencing by an optical device, the base recognition result is converted into a binary sequence using a binary coding format to obtain a base sequence corresponding to the sample to be analyzed;

[0031] Alternatively, the sample to be analyzed is sequenced by the first sequencer, and after detecting the light intensity value of the fluorescence signal obtained by sequencing using a semiconductor chip, the light intensity signal is converted into an electrical signal in a binary coding format to obtain a base sequence corresponding to the sample to be analyzed;

[0032] If the target sequencer is a second sequencer, the sample to be analyzed is sequenced directly by the second sequencer, and the current signal obtained by sequencing is converted into a binary sequence using a binary coding format to obtain a base sequence corresponding to the sample to be analyzed;

[0033] Alternatively, the sample to be analyzed is sequenced by the second sequencer, and after the light intensity value of the fluorescence signal obtained by sequencing is detected using a semiconductor chip, the light intensity signal is converted into an electrical signal in a binary coding format to obtain a base sequence corresponding to the sample to be analyzed.

[0034] Optionally, the optical device includes a beam splitter and a convex lens;

[0035] After performing base recognition on the fluorescent signal obtained by sequencing by the optical device, the base recognition result is converted into a binary sequence using a binary coding format, including:

[0036] The beam of photons corresponding to the fluorescence signal obtained by sequencing is divided into four beams by the spectroscope, and the four beams are filtered respectively, and then the filtered four beams are converted into parallel light by four convex lenses;

[0037] The parallel light is converted into a binary sequence using a CMOS camera.

[0038] Optionally, the method of using a semiconductor chip to detect the light intensity value of the fluorescence signal obtained by sequencing and converting the light intensity signal into an electrical signal in a binary coding format includes:

[0039] After packaging the upper stack of semiconductor chips, the packaged semiconductor chips are used to perform intelligent color filter processing on the fluorescence signals obtained by sequencing, so that the fluorescence signals are filtered by the four color filters in the intelligent color filter and fall on the designated position of each filter in the lower light pipe;

[0040] After collecting the filtered fluorescence signal at the lower light guide, the light intensity value of the filtered fluorescence signal is detected by the photodiode in the semiconductor chip to obtain a detection result;

[0041] The detection result is converted into an electrical signal in a binary coding format by a CMOS camera.

[0042] Optionally, the invoking an analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer to analyze the base sequence includes:

[0043] If the species to which the sample to be analyzed belongs is humans for which a reference genome exists, then when the target sequencer is the first sequencer, the first analysis method is called to analyze the base sequence; when the target sequencer is the second sequencer, the second analysis method is called to analyze the base sequence; and when the target sequencers are the first sequencer and the second sequencer, the third analysis method is called to analyze the base sequence;

[0044] If the species to which the sample to be analyzed belongs is another species for which there is no reference genome, then when the target sequencer is the first sequencer, the first assembly method is called to assemble the base sequence; when the target sequencer is the second sequencer, the second assembly method is called to assemble the base sequence; when the target sequencer is the first sequencer and the second sequencer, the third assembly method is called to assemble the base sequence, and the assembled base sequence is analyzed.

[0045] Optionally, when the target sequencer is a second sequencer, invoking a second analysis method to analyze the base sequence includes:

[0046] When the target sequencer is a second sequencer, performing sequence comparison, sorting, duplication removal, variation detection, sequence annotation, and interpretation on the base sequence to obtain a sequencing report;

[0047] Alternatively, the base sequences are spliced ​​using a preset sequence splicing algorithm to obtain variation information corresponding to the base sequences, and the variation information is annotated and interpreted to obtain a sequencing report.

[0048] Optionally, when the target sequencers are the first sequencer and the second sequencer, calling a third assembly method to assemble the base sequence, and analyzing the assembled base sequence, including:

[0049] When the target sequencers are the first sequencer and the second sequencer, determining evaluation results of a plurality of pre-provided assembly methods evaluated by a user according to different evaluation indicators, and selecting at least one assembly method from the plurality of pre-provided assembly methods as a third assembly method based on the evaluation results;

[0050] The third assembly method is called to assemble the base sequence, and the assembled base sequence is analyzed.

[0051] Optionally, calling the third assembly method to assemble the base sequence and analyzing the assembled base sequence includes:

[0052] Invoking the third assembly method to assemble the base sequence of the first sequencer according to the kmer cutting and de Bruijn graph formation method, and splicing the assembled base sequence with the base sequence of the second sequencer to obtain a spliced ​​genome and corresponding variation information;

[0053] Alternatively, the third assembly method is invoked to compare the base sequence of the first sequencer to the base sequence of the second sequencer according to the kmer and hash alignment method, and after obtaining the alignment data, the base sequence of the second sequencer is error-corrected according to the alignment data, and the corrected base sequence is spliced ​​with the base sequence of the first sequencer to obtain a spliced ​​genome and corresponding variation information;

[0054] Alternatively, the third assembly method is invoked to pre-assemble the base sequences of the first sequencer into contigs, and then the base sequences of the second sequencer are corrected using the contigs. The corrected base sequences are assembled to obtain a spliced ​​genome and corresponding variation information.

[0055] Alternatively, the third assembly method is called to assemble the base sequence of the first sequencer according to the method of cutting kmers and forming a De Bruijn graph, and the base sequence of the second sequencer is aligned to the assembled De Bruijn graph, and a scaffold is constructed according to the alignment results to obtain a spliced ​​genome and corresponding variation information.

[0056] Optionally, the invoking an analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer to analyze the base sequence further includes:

[0057] If the target sequencer is the first sequencer or the second sequencer, calling a species tree construction method corresponding to the species to which the sample to be analyzed belongs, constructing a corresponding species tree for the species to which the sample to be analyzed belongs, and analyzing the base sequence according to the constructed species tree;

[0058] Alternatively, if the target sequencers are a first sequencer and a second sequencer, the base sequence of the first sequencer and the base sequence of the second sequencer are transcribed to form transcriptome data, and the transcriptome data are compared, and the data length, quality, and integrity are analyzed to analyze the regulatory mechanism of expression metabolism of the species to which the sample to be analyzed belongs.

[0059] Optionally, when the target sequencer is a first sequencer and a second sequencer, the method further includes:

[0060] When annotating the variation results of the base sequence, or performing species annotation on the assembled base sequence, if the quality values ​​of some sites in the base sequence or the assembled base sequence are worse than the preset quality threshold and have a direct impact on the annotation results, the site mutation or short fragment mutation of the some sites are verified by using a sequencer using first-generation sequencing technology.

[0061] The present application also provides a flow sequencing analysis device, comprising:

[0062] The data acquisition module is used to obtain samples to be analyzed and the corresponding analysis requirements, as well as the current idle status of each sequencer;

[0063] A sequencing module is configured to determine a target sequencer based on the sample characteristics of the sample to be analyzed, analysis requirements, and the current availability of each sequencer, and to sequence the sample to be analyzed using the target sequencer to obtain a base sequence corresponding to the sample to be analyzed, wherein the base sequence is a binary sequence;

[0064] The analysis module is used to input the base sequence into the memory, call the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer, analyze the base sequence, and generate a sequencing report.

[0065] The present application also provides a storage medium storing computer-readable instructions. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the flow sequencing analysis method as described in any one of the above embodiments.

[0066] The present application also provides a computer device, comprising: one or more processors, and a memory;

[0067] The memory stores computer-readable instructions, and when the computer-readable instructions are executed by the one or more processors, the steps of the flow sequencing analysis method described in any one of the above embodiments are performed.

[0068] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0069] The flow sequencing analysis method, device, storage medium and computer equipment provided by the present application, after obtaining the sample to be analyzed and the corresponding analysis requirements and the current idle status of each sequencer, since the sequencing advantages of the first sequencer using the second-generation sequencing technology and the second sequencer using the third-generation sequencing technology are different, the present application can determine the target sequencer in combination with the sample characteristics of the sample to be analyzed, the analysis requirements and the idle status of each sequencer. The target sequencer can be the first sequencer or the second sequencer, and the first sequencer and the second sequencer can also be used for mixed sequencing, which not only provides users with diverse usage scenarios, but also improves sequencing efficiency and sequencing accuracy to a certain extent; then, the present application can sequence the sample to be analyzed through the target sequencer and obtain the base sequence corresponding to the sample to be analyzed. The base sequence is a binary sequence, that is, the ACGT base can be represented by 00, The binary data of 01, 10, and 11 are stored and transferred to the memory, and then the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer is directly called in the memory to analyze the base sequence and generate a sequencing report. In this way, the basecall process of sequencing and the subsequent analysis process can be connected through the memory. The sequencing and analysis processes of the sample to be analyzed are carried out by one process, which is easy and quick for operators to get started. After the memory is connected, the analysis efficiency can be improved and I / O congestion can be reduced. In addition, the base sequence in the binary encoding format shortens the reading and writing time, is more convenient for subsequent analysis process processing, improves the analysis efficiency of the overall process, and has strong adaptability. Without basically changing the existing machine parameters, through the new encoding form and process processing, it can improve the program operation efficiency without affecting the accuracy of sequencing analysis, and extend the service life of the machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0071] FIG1 is a schematic diagram of a flow cytometry analysis method provided in an embodiment of the present application;

[0072] FIG2 is a schematic diagram comparing the sequencing characteristics and advantages and disadvantages of sequencers using different sequencing technologies provided in an embodiment of the present application;

[0073] FIG3 is a schematic diagram of a process for analyzing a base sequence according to an embodiment of the present application;

[0074] FIG4 is a schematic structural diagram of a flow sequencing analysis device provided in an embodiment of the present application;

[0075] FIG5 is a schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0076] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0077] Currently, due to the huge amount of genetic data, the relatively limited usage scenarios, and the high server reliance on analysis processes, the parallel input of a large number of samples can easily cause I / O congestion, causing threads or processes to be suspended, greatly affecting analysis efficiency and accuracy. Based on this, this application provides the following technical solutions, which are detailed below:

[0078] In one embodiment, as shown in FIG1 , FIG1 is a schematic flow chart of a flow sequencing analysis method provided in an embodiment of the present application; the present application provides a flow sequencing analysis method, which may include:

[0079] S110: Obtain samples to be analyzed and corresponding analysis requirements, as well as the current idle status of each sequencer.

[0080] In this step, when performing sequencing analysis, you can first obtain the samples to be analyzed and the corresponding analysis requirements, as well as the current idle status of each sequencer. In this way, you can determine the target sequencer based on the samples to be analyzed and the corresponding analysis requirements and the current idle status of each sequencer.

[0081] It is understandable that the sample to be analyzed in this application can be a single sample or a project consisting of multiple samples, and this is not limited here. The analysis requirements of the sample to be analyzed in this application refer to the user's requirements for analysis accuracy, sequencing cost, emphasis on sequencing analysis, etc.; and the current sequencers in this application refer to the first sequencer using second-generation sequencing technology and the second sequencer using third-generation sequencing technology. The current idle status of each sequencer refers to whether each sequencer is currently working, whether there are any remaining resources to process the sample to be analyzed, or whether sequencing analysis is performed when the sample to be analyzed needs to be sequenced and analyzed.

[0082] Among them, the workflow of the second-generation sequencing technology of this application mainly includes the following:

[0083] 1) First, perform biochemical amplification and imaging to output an img file: randomly interrupt the DNA sequence to be tested, connect adapters for amplification (Illumina uses bridge PCR + reversible termination method, i.e. 3', while BGI uses rolling circle replication of the cssDNA library and amplification with DNB nanospheres, and then the DNA nanospheres are loaded onto a high-density grid). Then, perform a biochemical reaction, emit fluorescence, take a picture to obtain an img file, and output it;

[0084] 2)basecall: input img file and output call file;

[0085] 3)writefq: input the call file and output the fq file;

[0086] 4) Data quality control: input fq file + sample + machine information, and output quality control results;

[0087] 5) Data archiving: fq double backup archiving;

[0088] 6) Information analysis of genetic data from NGS: Because the size and characteristics of FASTQ data from sequencers of different brands and models vary, different customized operations are sometimes required before processing, such as separate splitting, merging, and quality control of different parameters, followed by bioinformatics analysis and interpretation.

[0089] The third-generation sequencing technologies of this application include two categories. One is the application of single-molecule real-time sequencing (SMRT), which uses fluorescent labels on the phosphate groups of deoxyribonucleotides during sequencing. The fluorescently labeled nucleotides will emit fluorescent signals at the incorporation site. Then, the DNA polymerase is fixed to the bottom of the nanochamber using a solid-phase enzyme, and the zero-mode waveguide technology (ZMW) is used to observe the fluorescent signal at the 20-30nm small hole at the bottom of the nanochamber; the other is a third-generation sequencer based on biological nanopore sequencing, which reduces the DNA sequencing speed through the molecular motor, process enzyme and ratchet effect on the nanopore, and distinguishes bases through restriction sites. When the nucleic acid sequence passes through, the conductivity of the ionic current in the hole will change. Since nucleotides have different shapes, the bases can be identified by the influence of different nucleotides on the change of ionic current.

[0090] S120: Determine a target sequencer based on the sample characteristics of the sample to be analyzed, analysis requirements, and the current idleness of each sequencer, and sequence the sample to be analyzed using the target sequencer to obtain a base sequence corresponding to the sample to be analyzed.

[0091] In this step, after obtaining the sample to be analyzed and the corresponding analysis requirements, as well as the current idle status of each sequencer through S110, the present application can determine the target sequencer based on the sample characteristics, analysis requirements and the current idle status of each sequencer of the sample to be analyzed, and then use the target sequencer to sequence the sample to be analyzed to obtain the base sequence corresponding to the sample to be analyzed.

[0092] It is understandable that since the advantages and disadvantages of sequencers using different sequencing technologies are different, and the sample characteristics and analysis requirements of each sample to be analyzed are also different, in order to obtain more accurate sequencing results and to meet user needs, this application can determine the target sequencer based on the sample characteristics and analysis requirements of the sample to be analyzed and the current idle status of each sequencer, so as to improve sequencing efficiency and sequencing accuracy.

[0093] For example, sequencing cost, read length, and throughput are three important indicators for evaluating the advancement of a sequencing technology. In addition to the differences in throughput and cost, the core sequencing principles of the first and second generation sequencing technologies (except for Solid, which performs sequencing while ligating) are all based on the idea of ​​sequencing while synthesizing. The advantage of the second generation sequencing technology is that the cost is greatly reduced and the throughput is greatly improved compared to the first generation, but the disadvantage is that the introduction of the PCR process increases the error rate of sequencing to a certain extent, and it has system bias, and the read length is also relatively short. The third generation sequencing technology was developed to address the shortcomings of the second generation. Its fundamental feature is single-molecule sequencing, which does not require any PCR process. This is to effectively avoid system errors caused by PCR bias, while improving read length and maintaining the high throughput and low cost advantages of the second generation sequencing technology.

[0094] For the samples to be analyzed in this application, their sample characteristics are diverse. Some samples have too large an amount of data off the machine. When a sequencer with higher sequencing costs is used for sequencing analysis, a lot of sequencing costs will be incurred. Some samples have a small or average amount of data off the machine. It depends on whether there are requirements for analysis accuracy. If there are requirements for analysis accuracy, it is necessary to select a suitable sequencer according to the specific analysis accuracy requirements. In addition, when any sequencer can be selected for sequencing, it is also necessary to consider whether each sequencer is idle. Only when it is idle can the sequencer be selected for sequencing analysis.

[0095] In addition, this application determines the target sequencer, and uses the target sequencer to sequence the sample to be analyzed, and the base sequence obtained is a binary sequence. The use of this binary sequence can not only shorten the reading and writing time and facilitate the subsequent analysis process, but also improve the analysis efficiency of the overall process. It has strong adaptability and can basically not change the existing machine parameters. Through new coding forms and process processing, it can improve the program operation efficiency without affecting the accuracy of sequencing analysis, and also extend the service life of the machine.

[0096] S130: Input the base sequence into the memory, call the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer, analyze the base sequence, and generate a sequencing report.

[0097] In this step, the target sequencer is determined through S120, and the target sequencer is used to sequence the sample to be analyzed. After obtaining the base sequence corresponding to the sample to be analyzed, the present application can also input the base sequence into the memory, and call the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer to analyze the base sequence, thereby generating a corresponding sequencing report.

[0098] Specifically, the present application transfers the base sequence in binary encoding format to the memory, and then directly calls the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer in the memory to analyze the base sequence and generate a sequencing report. In this way, the sequencing basecall process and the subsequent analysis process can be connected through the memory, and the sequencing and analysis processes of the sample to be analyzed are carried out by one process, making it easy and quick for operators to get started. Moreover, after the memory is connected, the analysis efficiency can be improved and I / O congestion can be reduced.

[0099] Furthermore, when analyzing the base sequence, the present application takes into account both the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer. For example, when the sample to be analyzed is a human sample, the steps and specific detection contents during the analysis of the human sample are different from the analysis steps and detection contents of other species. In view of this difference, the present application can pre-set different analysis methods. Different sequencing technologies have different advantages and disadvantages. The present application can learn from each other's strengths and weaknesses, or pre-set corresponding analysis methods in the form of leveraging strengths and avoiding weaknesses. In this way, the base sequence can be analyzed through multiple analysis methods, thereby enriching the usage scenarios while improving the analysis accuracy of the base sequence.

[0100] In addition, when producing sequencing reports, the present application can automatically generate sequencing reports according to the agreed report generation rules and / or template calling rules, thereby improving analysis efficiency while meeting user needs.

[0101] In the above embodiment, after obtaining the sample to be analyzed and the corresponding analysis requirements and the current idle status of each sequencer, since the sequencing advantages of the first sequencer using the second-generation sequencing technology and the second sequencer using the third-generation sequencing technology are different, the present application can determine the target sequencer based on the sample characteristics of the sample to be analyzed, the analysis requirements and the idle status of each sequencer. The target sequencer can be the first sequencer or the second sequencer, and the first sequencer and the second sequencer can also be used for mixed sequencing. This not only provides users with diverse usage scenarios, but also improves sequencing efficiency and sequencing accuracy to a certain extent; then, the present application can sequence the sample to be analyzed through the target sequencer and obtain the base sequence corresponding to the sample to be analyzed. The base sequence is a binary sequence, that is, the ACGT base can be represented by the binary sequence of 00, 01, 10, and 11. The system is stored and transferred to the memory, and then the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer is directly called in the memory to analyze the base sequence and generate a sequencing report. In this way, the basecall process of sequencing and the subsequent analysis process can be connected through the memory, and the sequencing and analysis processes of the sample to be analyzed are carried by one process, which is easy and quick for operators to get started. After the memory is connected, the analysis efficiency can be improved and I / O congestion can be reduced. Moreover, the base sequence in the binary encoding format shortens the reading and writing time, is more convenient for subsequent analysis process processing, improves the analysis efficiency of the overall process, and has strong adaptability. Under the condition that the existing machine parameters are basically unchanged, through the new encoding form and process processing, it can improve the program operation efficiency while extending the service life of the machine without affecting the accuracy of sequencing analysis.

[0102] In one embodiment, determining the target sequencer in S120 based on the sample characteristics of the sample to be analyzed, analysis requirements, and the current availability of each sequencer may include:

[0103] S101: Input the sample characteristics and analysis requirements of the sample to be analyzed into a pre-configured target classification model, and obtain the type of sequencer applicable to the sample to be analyzed output by the target classification model; wherein, the target classification model is obtained after training using historical analysis samples containing sample characteristics and analysis requirements as training samples, and using the type of sequencer applicable to the training samples as sample labels.

[0104] S102: Determine a target sequencer based on the type of sequencer applicable to the sample to be analyzed and the current availability of each sequencer.

[0105] In this embodiment, when determining the target sequencer, the present application can use a pre-configured target classification model. The target classification model is obtained after training using historical analysis samples containing sample characteristics and analysis requirements as training samples and the sequencer type applicable to the training samples as sample labels. Therefore, the present application can input the sample characteristics and analysis requirements of the sample to be analyzed into the target classification model, and the target classification model can output the sequencer type corresponding to the sample to be analyzed. Then, the present application can also combine the sequencer type output by the target classification model and the current idle status of each sequencer to determine the final target sequencer.

[0106] Among them, the sample characteristics and analysis requirements of the samples to be analyzed in this application include but are not limited to sample size, sequencing type, sequencing depth, sequencing time, sequencing cost, sequencing accuracy, etc. This application can construct corresponding functions based on the sample characteristics and analysis requirements of each historical analysis sample, such as sequencer type = f(sample size, sequencing type, sequencing depth, sequencing time, sequencing cost, sequencing accuracy), where f represents a function that can be obtained by modeling and training existing data. Specifically, this application can use a classification algorithm in machine learning (integrating models such as decision trees, support vector machines, and neural networks) to train a classification model to predict the type of sequencer suitable for the current conditions.

[0107] After obtaining the sequencer type through the target classification model, this application also needs to determine the final target sequencer based on the current idle status of each sequencer, which can not only reduce the sequencing waiting time but also improve the sequencing efficiency.

[0108] In one embodiment, the training process of the target classification model in S101 may include:

[0109] S1010: Acquire multiple historical analysis samples including sample characteristics and analysis requirements, as well as actual sequencer types applicable to each historical analysis sample, and divide the multiple historical analysis samples into a training set and a test set.

[0110] S1011: Inputting the historical analysis samples in the training set into the initial classification model to obtain the predicted sequencer type of the historical analysis samples output by the initial classification model.

[0111] S1012: Training the initial classification model with the goal of making the predicted sequencer type close to the actual sequencer type applicable to the historical analysis samples.

[0112] S1013: When the initial classification model meets the preset training conditions, the trained initial classification model is adjusted and optimized using the historical analysis samples in the test set to obtain a final target classification model.

[0113] In this embodiment, when training the target classification model, multiple historical analysis samples containing sample characteristics and analysis requirements and the actual sequencer type applicable to each historical analysis sample can be obtained first. Then, the multiple historical analysis samples can be divided into a training set and a test set. The historical analysis samples in the training set can be used to train the initial classification model, while the historical analysis samples in the test set can be used to test the performance of the trained initial classification model, and adjustments and optimizations can be made based on the test results to improve the accuracy and generalization ability of the model.

[0114] Specifically, when training the model, the present application can prepare a data set containing multiple historical analysis samples based on past sequencing experience. Each historical analysis sample contains sample size, sequencing type, sequencing depth, sequencing time, sequencing cost, sequencing accuracy, and the corresponding sequencer type. Then, the present application can divide the data set into a training set and a test set, and use the training set to train the initial classification model, and use the test set to test the performance of the trained initial classification model. Adjust and optimize according to the test results to improve the accuracy and generalization ability of the model, thereby obtaining the final target classification model.

[0115] In one embodiment, determining a target sequencer in S120 based on the sample characteristics of the sample to be analyzed, analysis requirements, and the current availability of each sequencer includes:

[0116] S121: Compare the sample characteristics and analysis requirements of the sample to be analyzed with the corresponding thresholds respectively, or compare the analysis requirements of the sample to be analyzed with the corresponding thresholds alone, and determine the target sequencer based on the comparison results and the current idle status of each sequencer.

[0117] In this embodiment, when determining the target sequencer based on the sample characteristics, analysis requirements and current idle status of each sequencer of the sample to be analyzed, the present application can compare the sample characteristics and analysis requirements of the sample to be analyzed with the corresponding thresholds respectively, or directly compare the analysis requirements of the sample to be analyzed with the corresponding thresholds separately, and then determine the target sequencer based on the comparison results and the current idle status of each sequencer.

[0118] It should be noted that since the sample characteristics of the samples to be analyzed may have general and special cases, such as too much downstream data, or too little downstream data, or normal downstream data, when there are special cases in the sample characteristics of the samples to be analyzed, this application can compare the sample characteristics and analysis requirements of the samples to be analyzed with the corresponding thresholds respectively, and when the sample characteristics of the samples to be analyzed are general, only the analysis requirements of the samples to be analyzed can be considered, and the target sequencer can be determined based on the comparison results between the analysis requirements and the corresponding thresholds and the current idle status of each sequencer.

[0119] In one embodiment, S121 compares the sample characteristics and analysis requirements of the sample to be analyzed with corresponding thresholds respectively, or compares the analysis requirements of the sample to be analyzed with corresponding thresholds alone, and determines the target sequencer based on the comparison results and the current availability of each sequencer, which may include:

[0120] S1210: If the analysis requirements of the sample to be analyzed are that there is no sequencing cost requirement or it is lower than a preset cost threshold, the analysis accuracy is greater than a preset accuracy threshold, or there is a detection requirement for a specific function, then the first sequencer and the second sequencer are used together as target sequencers, and the sequencing results of the target sequencer are verified by a sequencer using first-generation sequencing technology.

[0121] S1211: If the analysis requirement of the sample to be analyzed is that the sequencing cost is lower than the preset cost threshold and the analysis accuracy is higher than the preset accuracy threshold, a target sequencer is determined according to the idle status of different types of first sequencers.

[0122] S1212: If the analysis requirements of the sample to be analyzed are that the sequencing cost is lower than the preset cost threshold, the analysis accuracy is higher than the preset accuracy threshold, and the sample characteristic of the sample to be analyzed is that the amount of data downloaded from the machine is less than the preset data amount threshold, then based on the accuracy and whether the functions of the first sequencer and the second sequencer meet the requirements, a sequencer with higher accuracy and functions that meet the requirements is selected as the target sequencer. Alternatively, if the accuracy and functions of the first sequencer and the second sequencer are the same, the target sequencer is determined based on the idle status of the first sequencer and the second sequencer.

[0123] S1213: If the analysis requirement of the sample to be analyzed is that there is no requirement for sequencing cost, the analysis accuracy is less than the preset accuracy threshold, the sequencing time is less than the preset sequencing time, and the analysis environment of the sample to be analyzed is an abnormal environment, then Nanopore in the second sequencer is selected as the target sequencer.

[0124] In this embodiment, when determining the target sequencer, the sample characteristics and analysis requirements of the sample to be analyzed can be compared with the corresponding thresholds respectively, or the analysis requirements of the sample to be analyzed can be directly compared with the corresponding thresholds alone, and the target sequencer can be determined based on the comparison results and the current idle status of each sequencer.

[0125] Specifically, the present application can compare the analysis requirements of the samples to be analyzed with the corresponding thresholds separately, such as comparing the sequencing cost with the preset cost threshold, comparing the analysis accuracy with the preset accuracy threshold, and comparing the analysis accuracy with the preset accuracy threshold. The sequencing time can also be compared with the preset sequencing time, etc.; alternatively, the present application can also compare the sample characteristics and analysis requirements of the samples to be analyzed with the corresponding thresholds respectively, where the comparison part of the analysis requirements is consistent with the above-mentioned comparison situations, and for the comparison part of the sample characteristics, the present application can compare the amount of offline data of the samples to be analyzed with the preset data amount threshold. Of course, after the comparison, the analysis environment of the samples to be analyzed, whether the accuracy and function of the sequencer meet the requirements, etc. can also be introduced, which are not limited here.

[0126] In a specific embodiment, as shown in Figure 2, Figure 2 is a comparative schematic diagram of the sequencing characteristics and advantages and disadvantages corresponding to sequencers using different sequencing technologies provided in the embodiments of the present application; it can be seen from Figure 2 that the first-generation sequencing data is suitable for verification of a small number of sites, the second-generation sequencing has low cost and high throughput (a high amount of data can be downloaded at one time), the third-generation PacBio sequencing has high cost, but in the detection of data between capture cells with a small amount of data, the cost has no obvious disadvantage; the third-generation Nanopore sequencing has high cost, but the sequencer is small. In remote areas, there are pathogenic microorganisms that do not require high accuracy (patients with unexplained fever), and this type of detection can be used, which is easy to carry.

[0127] Based on this, when determining the target sequencer, the present application can determine the target sequencer based on the sample characteristics of the sample to be analyzed, the analysis requirements, and the current idleness of each sequencer. Specifically, if the analysis requirements of the sample to be analyzed are that there is no requirement for sequencing cost, but the analysis accuracy requirements are high, then the first sequencer and the second sequencer can be used together as the target sequencer, and the sequencing results of the target sequencer can be verified by a sequencer using first-generation sequencing technology; and when the analysis requirements of the sample to be analyzed are that the sequencing cost is lower than the preset cost threshold, the analysis accuracy requirements are high, and there are specific functional detection requirements, such as methylation, RNA, GC interval, high variable region detection, pseudogene detection and other functional detection requirements, the first sequencer and the second sequencer can also be selected as the target sequencer, and the sequencing results of the target sequencer can be verified by a sequencer using first-generation sequencing technology.

[0128] Furthermore, if the analysis requirements of the samples to be analyzed are that the sequencing cost is lower than the preset cost threshold and the analysis accuracy is higher than the preset accuracy threshold, the target sequencer can be determined based on the idleness of different types of first sequencers, such as Illumina and BGI sequencers, and the one that is idle can be selected; and when the analysis requirements of the samples to be analyzed are that the sequencing cost is lower than the preset cost threshold and the analysis accuracy is higher than the preset accuracy threshold, and the sample characteristics of the samples to be analyzed are that the amount of data off the machine is less than the preset data amount threshold, the accuracy between the first sequencer and the second sequencer and whether the functions meet the requirements can be used as selection conditions, and the sequencer with higher accuracy and accuracy can be finally selected. A sequencer with functions that meet the requirements can be used as the target sequencer, or when the accuracy and functions of the first sequencer and the second sequencer are the same, the target sequencer can be determined based on the idle status of the first sequencer and the second sequencer; when the analysis requirements of the samples to be analyzed are no requirements for sequencing cost, the analysis accuracy requirements are also low, but the sequencing time requirements are high, and the analysis environment of the samples to be analyzed is an abnormal environment, such as a relatively harsh climate, a relatively remote area, and an area with inconvenient transportation, then the Nanopore in the second sequencer can be selected as the target sequencer. This sequencer is easy for the tester to carry, so treatment can be done nearby.

[0129] The above-mentioned preset accuracy threshold refers to an accuracy threshold related to analysis accuracy, such as the overall analysis accuracy, the analysis accuracy of each detection part, etc., and is not limited here.

[0130] In one embodiment, in S120, sequencing the sample to be analyzed by the target sequencer to obtain a base sequence corresponding to the sample to be analyzed may include:

[0131] S210: Sequencing the sample to be analyzed by the target sequencer, and converting the sequencing result of the target sequencer into a binary sequence according to the sequencing method of the target sequencer to obtain a base sequence corresponding to the sample to be analyzed.

[0132] In this embodiment, when the sample to be analyzed is sequenced by the target sequencer and the base sequence corresponding to the sample to be analyzed is obtained, the present application can convert the sequencing results of the target sequencer into a binary sequence according to the sequencing method of the target sequencer when the sample to be analyzed is sequenced by the target sequencer, thereby obtaining the base sequence corresponding to the sample to be analyzed.

[0133] For example, since different sequencers use different sequencing methods, such as second-generation sequencing technology or third-generation sequencing technology, and there are different technical branches under second-generation sequencing technology or third-generation sequencing technology, when different sequencing technologies are used to sequence the samples to be analyzed, the sequencing results obtained are also different. Therefore, the present application can set corresponding sequence conversion methods for target sequencers using different sequencing methods, and use the sequence conversion method to convert the sequencing results of the target sequencer into a binary sequence, and then obtain the base sequence corresponding to the sample to be analyzed.

[0134] In one embodiment, S210 may include sequencing the sample to be analyzed by the target sequencer, converting the sequencing result of the target sequencer into a binary sequence according to the sequencing method of the target sequencer, and obtaining a base sequence corresponding to the sample to be analyzed.

[0135] S211: If the target sequencer is the first sequencer, the sample to be analyzed is sequenced directly by the first sequencer, and the base recognition is performed on the fluorescent signal obtained by sequencing by an optical device. The base recognition result is converted into a binary sequence using a binary coding format to obtain a base sequence corresponding to the sample to be analyzed.

[0136] S212: Alternatively, the sample to be analyzed is sequenced by the first sequencer, and after the light intensity value of the fluorescence signal obtained by sequencing is detected using a semiconductor chip, the light intensity signal is converted into an electrical signal in a binary coding format to obtain a base sequence corresponding to the sample to be analyzed.

[0137] S213: If the target sequencer is a second sequencer, the sample to be analyzed is directly sequenced by the second sequencer, and the current signal obtained by sequencing is converted into a binary sequence using a binary coding format to obtain a base sequence corresponding to the sample to be analyzed.

[0138] S214: Alternatively, the sample to be analyzed is sequenced by the second sequencer, and after the light intensity value of the fluorescence signal obtained by sequencing is detected using a semiconductor chip, the light intensity signal is converted into an electrical signal in a binary coding format to obtain a base sequence corresponding to the sample to be analyzed.

[0139] In this embodiment, if the target sequencer of the present application is the first sequencer, that is, a sequencer using second-generation sequencing technology, since the sequencer using second-generation sequencing technology uses optical equipment to perform base recognition on the fluorescent signal obtained by sequencing, the present application can convert the sequencing results of the target sequencer into a binary sequence by changing the basecalling logic of a part of the upstream second-generation sequencer, or by directly changing the sequence format of the sequencing results without changing its basecalling logic. If the target sequencer of the present application is the second sequencer, that is, a sequencer using third-generation sequencing technology, since sequencers using third-generation sequencing technology are mainly divided into two categories, one using single-molecule real-time sequencing (SMRT) and the other using biological nanopore sequencing, the sequencing results generated by the two categories of sequencers are also different. Therefore, for different sequencing technologies, the present application can also use different conversion methods to convert the sequencing results of the target sequencer into a binary sequence.

[0140] In a specific implementation method, if the target sequencer of the present application is the first sequencer, the sample to be analyzed can be sequenced directly by the first sequencer, and after the base recognition is performed on the fluorescent signal obtained by sequencing by an optical device, the base recognition result is converted into a binary sequence using a binary coding format, and then the base sequence corresponding to the sample to be analyzed is obtained; or, the sample to be analyzed can be sequenced by the first sequencer, and after the light intensity value of the fluorescent signal obtained by sequencing is detected using a semiconductor chip, the light intensity signal is converted into an electrical signal in a binary coding format, and then the base sequence corresponding to the sample to be analyzed is obtained.

[0141] For the second sequencer using single-molecule real-time sequencing (SMRT) technology, fluorescent labels are added to the phosphate groups of deoxyribonucleotides during sequencing. The fluorescently labeled nucleotides emit a fluorescent signal at the site of incorporation. PacBio uses a solid-phase enzyme to immobilize the DNA polymerase at the bottom of the nanochamber and uses zero-mode waveguide technology (ZMW) to observe the fluorescent signal through a 20-30nm hole at the bottom of the nanochamber, improving the signal-to-noise ratio and accuracy. Therefore, the present application can use the second sequencer to sequence the sample to be analyzed, and after using a semiconductor chip to detect the light intensity value of the fluorescent signal obtained by sequencing, the light intensity signal is converted into an electrical signal in a binary coded format, and then the base sequence corresponding to the sample to be analyzed is obtained. As for the second sequencer based on biological nanopore sequencing, since it uses molecular motors, process enzymes and ratchet effects on the nanopore to reduce the DNA sequencing speed, and uses restriction sites to distinguish bases, when the nucleic acid sequence passes through, the conductivity of the ionic current in the pore will change. Since nucleotides have different shapes, bases can be identified by the influence of different nucleotides on the change of ionic current. Therefore, the present application can also directly sequence the sample to be analyzed through the second sequencer, and use a binary coding format to convert the current signal obtained by sequencing into a binary sequence, and then obtain the base sequence corresponding to the sample to be analyzed.

[0142] In the above embodiment, a sequencer using second-generation sequencing technology or a sequencer using third-generation sequencing technology can store the fastq results output by basecall into the memory, or store the electrical signals converted from the light intensity values ​​detected after intelligent color filtering of the semiconductor chip, that is, ACGT represented by 00, 01, 10, and 11 into the memory for subsequent comparison or assembly analysis; the entire process reduces two network transmissions and I / O reading and writing, thereby improving analysis efficiency; and the Fastq format no longer follows the existing format of 4 lines in a group, but adopts the new format of 00 / 01 / 10 / 11 to represent ATCG, which further improves the reading and writing analysis efficiency; in addition, during the sequencing and analysis process, the present application connects processes that do not require output results, such as biochemical imaging, basecall or photoelectric signal conversion and comparison, through memory, and can customize the output results (whether to output new fastq or not), thereby further reducing I / O communication.

[0143] In one embodiment, the optical device comprises a beam splitter and a convex lens.

[0144] After performing base recognition on the fluorescent signal obtained by sequencing by an optical device in S211, the base recognition result is converted into a binary sequence using a binary coding format, which may include:

[0145] S2110: Splitting a beam of photons corresponding to the fluorescence signal obtained by sequencing into four beams through the spectroscope, filtering the four beams respectively, and converting the filtered four beams into parallel light through four convex lenses.

[0146] S2111: Convert the parallel light into a binary sequence using a CMOS camera.

[0147] In this embodiment, when base recognition is performed on the fluorescent signal obtained by sequencing through an optical device, the light quantum corresponding to the fluorescent signal obtained by sequencing can be first divided into four light beams by the spectroscope, and the four light beams are filtered respectively. The four filtered light beams are then converted into parallel light through a corresponding number of convex lenses, and then the optical signal corresponding to the parallel light is converted into a binary electrical signal sequence, such as 00, 01, 10, 11, through the CMOS element.

[0148] In one embodiment, in S212 or S214, the semiconductor chip is used to detect the light intensity value of the fluorescence signal obtained by sequencing, and the light intensity signal is converted into an electrical signal in a binary coding format, which may include:

[0149] S401: After packaging the upper stack of semiconductor chips, use the packaged semiconductor chips to perform intelligent color filter processing on the fluorescence signal obtained by sequencing, so that the fluorescence signal is filtered by the four color filters in the intelligent color filter and falls on the specified position of each filter in the lower light guide.

[0150] S402: After collecting the filtered fluorescence signal at the lower light guide tube, the light intensity value of the filtered fluorescence signal is detected by the photodiode in the semiconductor chip to obtain a detection result.

[0151] S403: Convert the detection result into an electrical signal in a binary coding format through a CMOS camera.

[0152] In this embodiment, when the target sequencer is the first sequencer or the second sequencer, and a semiconductor chip is used to detect the light intensity value of the fluorescence signal obtained by sequencing, the present application can first package the upper stack of the semiconductor chip, and use the packaged semiconductor chip to perform intelligent color filter processing on the fluorescence signal obtained by sequencing. After the light quantum passes through the four color filters, it falls on the designated position of the fluorescent color (four filters correspond to four positions), and the fluorescence signal is collected at the lower light guide. The light intensity value of the fluorescence emitted by the semiconductor chip is used by the photosensitive diode (well) to detect the light quantum signal intensity. The optical signal is then simplified into an electrical signal through a CMOS camera. That is, the fluorescent ball is covered with a transparent silicon wafer, and there is no need for a convex lens to focus the light. The optical signal can be directly converted into an electrical signal through the CMOS camera. In addition, ACGT can be stored and transmitted through binary 00, 01, 10, and 11. Compared with optical images, more base sequences can be detected per unit space, and the basecall and conversion to fastq files are eliminated. The process of subsequent storage and analysis is optimized, solving the problems of long time consumption, slow analysis efficiency, cumbersome process, and strong dependence on storage, I / O and network performance.

[0153] It is understandable that a semiconductor chip is an electronic device made of semiconductor materials. It is usually a small, integrated circuit used to control and amplify current, calculate and store data, etc. Semiconductor chips can be used to make various electronic devices, such as computers, mobile phones, televisions, air conditioners, cars, etc. Therefore, the present application can personalize the design of the semiconductor chip so that it has the functions of performing intelligent color filter processing on the fluorescence signal obtained by sequencing, collecting the filtered fluorescence signal at the lower light guide, and detecting the light intensity value of the filtered fluorescence signal. In addition, the stack packaging method used for the semiconductor chip in the present application can be packaged using the packaging method in the prior art, which is not limited here.

[0154] In one embodiment, as shown in FIG3 , FIG3 is a schematic diagram of a process for analyzing a base sequence according to an embodiment of the present application; in S130 , calling an analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer to analyze the base sequence may include:

[0155] S131: If the species to which the sample to be analyzed belongs is humans for which a reference genome exists, when the target sequencer is the first sequencer, the first analysis method is called to analyze the base sequence; when the target sequencer is the second sequencer, the second analysis method is called to analyze the base sequence; and when the target sequencer is the first sequencer and the second sequencer, the third analysis method is called to analyze the base sequence.

[0156] S132: If the species to which the sample to be analyzed belongs is another species for which there is no reference genome, when the target sequencer is the first sequencer, the first assembly method is called to assemble the base sequence; when the target sequencer is the second sequencer, the second assembly method is called to assemble the base sequence; when the target sequencer is the first sequencer and the second sequencer, the third assembly method is called to assemble the base sequence, and the assembled base sequence is analyzed.

[0157] In this embodiment, due to the differences in the species to which the samples to be analyzed belong, such as humans with reference genomes, or other species without reference genomes, the sequencing analysis processes of different species are different. For example, for the human genome, when analyzing it, the analysis steps of the first sequencer or the second sequencer include sequence alignment, sorting, deduplication, variation detection, and annotation. For other species without reference genomes, the analysis process may include obtaining individual SNPs, indels, CNVs, SVs, etc. through the genome and results / GC high repeat region, low complexity region analysis, or species evolution and kinship construction, species annotation and abundance analysis, phenotypic group and its typing with proteome, metabolome, methylation group, transcriptome, etc. Correlation evolution study. Therefore, for different species, the present application can adopt different analysis methods. Of course, the sequencing technology used by the target sequencer must also be considered. Different sequencing technologies have different corresponding sequencing methods. Therefore, the subsequent analysis methods will also be different.

[0158] Specifically, when the species to be analyzed belongs to humans for which a reference genome exists, the present application can call the first analysis method to analyze the base sequence when the target sequencer is the first sequencer, call the second analysis method to analyze the base sequence when the target sequencer is the second sequencer, and call the third analysis method to analyze the base sequence when the target sequencer is the first sequencer and the second sequencer; wherein, the first analysis method of the present application refers to the sequencing method used by a sequencer using the second-generation sequencing technology, such as performing sequence alignment, sorting, deduplication, variation detection, and annotation in a general manner; the second analysis method of the present application refers to the sequencing method used by a sequencer using the third-generation sequencing technology, such as automatically adopting an adaptive length alignment algorithm according to different flow cytometry sequence lengths when performing sequence alignment, sorting, deduplication, variation detection, and annotation; and the third analysis method of the present application combines the advantages of the second-generation sequencing technology and the advantages of the third-generation sequencing technology to perform sequence alignment, sorting, deduplication, variation detection, and annotation.

[0159] For example, when the present application uses the second-generation sequencing technology and the third-generation sequencing technology to work together, variation detection can be performed together according to the comparison results of the second and third generations, especially in terms of repeat regions, high GC complex regions, pseudogene regions, methylation regions, complex variation regions, etc. The third generation has an advantage in detecting 1k-10k CNV regions or short repeats of STR. In the part where the quality of the third generation is low, the third generation length result can be corrected by measuring several passes or based on the short read length high-precision data detected by the second generation, and the second generation reads can be aligned to the third generation length. The short sequence alignment result with the highest alignment value is subjected to base recognition and error correction under the kmer sliding window, and then covered to the gap position to correct the length, in order to obtain the most accurate mapping result, and then remove data redundancy. In addition, the present application can also select software algorithms including SNP, indel, CNV, and SV according to the variation detection requirements of different projects, and obtain variation detection results, which can be used for transcript structure analysis, differential enrichment analysis, etc. In addition, during the annotation process, this application comprehensively annotates the variation results through annotation and filtering of bioinformatics analysis, basic information of second-generation or third-generation variants, disease information, population frequency, software prediction results and pathogenicity reports, and selects pathogenic variants based on comprehensive consideration of biological hazard, genetic consistency and clinical feature consistency.

[0160] When the species to be analyzed belongs to other species for which there is no reference genome, the present application can call the first assembly method to assemble the base sequence when the target sequencer is the first sequencer, call the second assembly method to assemble the base sequence when the target sequencer is the second sequencer, and call the third assembly method to assemble the base sequence when the target sequencer is the first sequencer and the second sequencer, and analyze the assembled base sequence.

[0161] In a specific implementation method, the present application can combine the characteristics of second-generation and third-generation sequencing to perform denovo sequence assembly. The second-generation sequence performs de novo assembly of sequences of 50 to 400 bp using OLC or de Burin graphs; the third-generation sequence performs denovo assembly of data of approximately 1k to 40kbp in length, and can also be assembled through graphs, OCL and other methods; when the second and third generations work together, base errors can be corrected according to the third-generation sequencing results, and the results of the third-generation assembly can be used to fill gaps, and then subsequent species evolution and kinship construction, species annotation and abundance analysis, large-fragment CNV, GC high-repeat region, low-complexity region analysis, representatives of the species' subspecies, subpopulations and individual strains, individual genome analysis (the relationship between phenotype and specific segments, genes, and nucleotide variations), and the integration of different omics (evolutionary studies of the correlation between phenotypic groups and their typing and proteomes, metabolomes, methylation groups, transcriptomes, etc.) can be carried out to obtain relevant results.

[0162] In one embodiment, when the target sequencer is a second sequencer, in S131, invoking a second analysis method to analyze the base sequence may include:

[0163] S1311: When the target sequencer is a second sequencer, the base sequence is subjected to sequence comparison, sorting, duplication removal, variation detection, sequence annotation, and interpretation to obtain a sequencing report.

[0164] S1312: Alternatively, after performing sequence splicing on the base sequence using a preset sequence splicing algorithm, variation information corresponding to the base sequence is obtained, and after performing sequence annotation and interpretation on the variation information, a sequencing report is obtained.

[0165] In this embodiment, when the target sequencer is a second sequencer, that is, a sequencer using third-generation sequencing technology, the present application may use the second analysis method to analyze the base sequence.

[0166] Specifically, the second analysis method of the present application can be to perform sequence comparison, sorting, deduplication, variation detection, sequence annotation, and interpretation on the base sequence to obtain a sequencing report; or, to use a preset sequence splicing algorithm to perform sequence splicing on the base sequence to obtain the variation information corresponding to the base sequence, and then perform sequence annotation and interpretation on the variation information to obtain a sequencing report.

[0167] Among them, the present application can pre-set multiple sequence splicing algorithms to perform sequence splicing on the base sequence, such as the greedy algorithm, OLC algorithm, De Bruijn graph method, etc. The specific selection can be made according to the actual situation and is not limited here.

[0168] In one embodiment, when the target sequencers are the first sequencer and the second sequencer, in S132, calling the third assembly method to assemble the base sequence and analyzing the assembled base sequence may include:

[0169] S1321: When the target sequencers are the first sequencer and the second sequencer, determine the evaluation results of the user after evaluating the multiple pre-provided assembly methods according to different evaluation indicators, and select at least one assembly method from the multiple pre-provided assembly methods as the third assembly method based on the evaluation results.

[0170] S1322: Calling the third assembly method to assemble the base sequence, and analyzing the assembled base sequence.

[0171] In this embodiment, when the present application uses the first sequencer and the second sequencer to perform mixed sequencing on other species for which no reference genome exists, the user can evaluate the multiple pre-provided assembly methods according to different evaluation indicators and obtain corresponding evaluation results. At this time, the present application can select at least one assembly method from the multiple pre-provided assembly methods as the third assembly method based on the evaluation results, and call the third assembly method to assemble the base sequence, and then analyze the assembled base sequence.

[0172] Among them, when users evaluate the various pre-provided assembly methods according to different evaluation indicators, the evaluation indicators include but are not limited to splicing length, error rate, running time, genome completion length, etc., when evaluating different assembly methods, they can also conduct a multi-dimensional comprehensive evaluation of their analysis performance, accuracy, advantages and disadvantages, etc. The specific settings can be made according to actual conditions and are not restricted here.

[0173] In one embodiment, in S1322, calling the third assembly method to assemble the base sequence and analyzing the assembled base sequence may include:

[0174] S3221: Call the third assembly method to assemble the base sequence of the first sequencer according to the kmer cutting and de Bruijn graph forming method, and splice the assembled base sequence with the base sequence of the second sequencer to obtain a spliced ​​genome and corresponding variation information.

[0175] S3222: Alternatively, the third assembly method is called to compare the base sequence of the first sequencer to the base sequence of the second sequencer according to the kmer and hash alignment method, and after obtaining the alignment data, the base sequence of the second sequencer is corrected according to the alignment data, and the corrected base sequence is spliced ​​with the base sequence of the first sequencer to obtain a spliced ​​genome and corresponding variation information.

[0176] S3223: Alternatively, the third assembly method is called to pre-assemble the base sequence of the first sequencer into contigs, and then the base sequence of the second sequencer is corrected by using the contigs. The corrected base sequence is spliced ​​with the base sequence of the first sequencer to obtain a spliced ​​genome and corresponding variation information.

[0177] S3224: Alternatively, the third assembly method is called to assemble the base sequence of the first sequencer according to the method of cutting kmers and forming a De Bruijn graph, and the base sequence of the second sequencer is aligned to the assembled De Bruijn graph, and a scaffold is constructed according to the alignment results to obtain a spliced ​​genome and corresponding variation information.

[0178] In this embodiment, since the third assembly method is selected by the user after evaluating multiple assembly methods provided in advance, the specific content of the third assembly method changes dynamically according to the evaluation index selected by the user.

[0179] For example, the present application can assemble the base sequence of the first sequencer according to the method of cutting kmer and forming de Bruijn graph, and splice the assembled base sequence with the base sequence of the second sequencer. During the process, the second sequencer can correct some splicing errors in the first sequencer, and the first sequencer can correct the sequencing errors of the second sequencer, and fill the gap area for the sequencing result of the second sequencer, so as to obtain the spliced ​​genome and the corresponding variation information. This is an assembly method; the present application can also compare the base sequence of the first sequencer to the base sequence of the second sequencer according to the method of cutting kmer and hashing, allowing m mismatches in the middle. After obtaining the comparison data, the comparison data can be used to compare the base sequence of the first sequencer to the base sequence of the second sequencer. The base sequence of the second sequencer is error-corrected, and then the corrected base sequence is spliced ​​with the base sequence of the first sequencer to obtain a spliced ​​genome and corresponding variation information. This is also an assembly method. The present application can also pre-splice the base sequence of the first sequencer into contigs, and then perform error correction on the base sequence of the second sequencer through contigs, and then assemble the corrected base sequence to obtain a spliced ​​genome and corresponding variation information. This is also an assembly method. Furthermore, the present application can also assemble the base sequence of the first sequencer according to the method of cutting kmers and forming a de Bruijn graph, and align the base sequence of the second sequencer to the assembled de Bruijn graph, and then construct a scaffold based on the alignment results to obtain a spliced ​​genome and corresponding variation information. This is also an assembly method.

[0180] Based on this, the present application can assemble the base sequence through at least the above four assembly methods and analyze the assembled base sequence.

[0181] In one embodiment, in S130, invoking an analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer to analyze the base sequence may further include:

[0182] S133: If the target sequencer is the first sequencer or the second sequencer, call the species tree construction method corresponding to the species to which the sample to be analyzed belongs, construct a corresponding species tree for the species to which the sample to be analyzed belongs, and analyze the base sequence according to the constructed species tree.

[0183] S134: Alternatively, if the target sequencers are a first sequencer and a second sequencer, the base sequence of the first sequencer and the base sequence of the second sequencer are transcribed to form transcriptome data, and the transcriptome data are compared, and the data length, quality, and integrity are analyzed to analyze the regulatory mechanism of expression metabolism of the species to which the sample to be analyzed belongs.

[0184] In this embodiment, when analyzing the base sequence, a corresponding species tree may be constructed according to the sequencing technology used by the target sequencer and the species to which the sample to be analyzed belongs, and the base sequence may be analyzed based on the constructed species tree.

[0185] Specifically, when constructing a phylogenetic species tree, the present application can form homologous regions (homologous site alignment) through multiple sequence alignment of the data downloaded from the first sequencer and the second sequencer, and then select the optimal tree construction method to establish a substitution model based on the data characteristics, such as the distance transformation method, maximum parsimony method, maximum likelihood method, and Bayesian method; then establish an evolutionary tree and evaluate the evolutionary tree to perform a multi-dimensional analysis of the base sequence.

[0186] Furthermore, the present application can also transcribe the base sequence of the first sequencer and the base sequence of the second sequencer to form transcriptome data when the target sequencers are the first sequencer and the second sequencer, and perform data comparison on the transcriptome data, and analyze the data length, quality, and integrity to analyze the regulatory mechanism of expression metabolism of the species to which the sample to be analyzed belongs.

[0187] Specifically, when constructing subsequent species evolution and kinship relationships and analyzing the correlation and variation characteristics between species, this application can also use second-generation sequencing technology and third-generation sequencing technology to download transcriptome data, perform transcriptome data comparison, data length, quality, and integrity analysis, as well as perform species database annotation, correlation analysis, cluster analysis, and abundance analysis, etc., so as to analyze the regulatory mechanism of species expression metabolism.

[0188] In one embodiment, when the target sequencer is a first sequencer and a second sequencer, the method may further include:

[0189] S140: When annotating the variation results of the base sequence, or performing species annotation on the assembled base sequence, if the quality values ​​of some sites in the base sequence or the assembled base sequence are worse than the preset quality threshold and have a direct impact on the annotation results, the site mutation or short fragment mutation of the some sites are verified by using a sequencer using first-generation sequencing technology.

[0190] In this embodiment, when annotating the variation results of human base sequences, or performing species annotation on the assembled base sequences of other species, if the quality values ​​of some sites in the base sequence are worse than the preset quality threshold, and the quality values ​​of these sites have a direct impact on the annotation results, for example, directly leading to a decrease in the accuracy of the annotation results, then the site verification can be performed on these sites by performing site mutations or short fragment mutations on a sequencer using first-generation sequencing technology, so as to improve the quality value of the site and thereby improve the accuracy of the annotation results.

[0191] Specifically, during the annotation process, this application comprehensively annotates the variation results through annotation and filtering of bioinformatics analysis, basic information of variations from the second or third generation, disease information, population frequency, software prediction results and pathogenicity reports, and selects pathogenic variations by comprehensively considering biological hazard, genetic consistency and clinical feature consistency. If at this time there are still some sites with poor quality values, which have a direct impact on the annotation results, site mutations or short fragment mutations can be verified through first-generation sequencing results, and then Google literature, public databases, self-developed databases, etc. can be queried according to the ACMG guidelines, CNV5-step judgment rules, etc. to judge the pathogenicity classification (P / LP / VUS / LB / B) of the variation. Finally, according to the agreed report generation rules and template calling rules, automatic report generation is achieved.

[0192] The flow sequencing analysis device provided in the embodiments of the present application is described below. The flow sequencing analysis device described below and the flow sequencing analysis method described above can be referenced to each other.

[0193] In one embodiment, as shown in FIG4 , FIG4 is a schematic diagram of the structure of a flow sequencing analysis device provided in an embodiment of the present application. The present application also provides a flow sequencing analysis device, which may include a data acquisition module 210, a sequencing module 220, and an analysis module 230, specifically including the following:

[0194] The data acquisition module 210 is used to obtain samples to be analyzed and corresponding analysis requirements, as well as the current idle status of each sequencer.

[0195] The sequencing module 220 is used to determine the target sequencer based on the sample characteristics, analysis requirements and current availability of each sequencer of the sample to be analyzed, and to sequence the sample to be analyzed by the target sequencer to obtain a base sequence corresponding to the sample to be analyzed, wherein the base sequence is a binary sequence.

[0196] The analysis module 230 is used to input the base sequence into the memory, call the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer, analyze the base sequence, and generate a sequencing report.

[0197] In the above embodiment, after obtaining the sample to be analyzed and the corresponding analysis requirements and the current idle status of each sequencer, since the sequencing advantages of the first sequencer using the second-generation sequencing technology and the second sequencer using the third-generation sequencing technology are different, the present application can determine the target sequencer based on the sample characteristics of the sample to be analyzed, the analysis requirements and the idle status of each sequencer. The target sequencer can be the first sequencer or the second sequencer, and the first sequencer and the second sequencer can also be used for mixed sequencing. This not only provides users with diverse usage scenarios, but also improves sequencing efficiency and sequencing accuracy to a certain extent; then, the present application can sequence the sample to be analyzed through the target sequencer and obtain the base sequence corresponding to the sample to be analyzed. The base sequence is a binary sequence, that is, the ACGT base can be represented by the binary sequence of 00, 01, 10, and 11. The system is stored and transferred to the memory, and then the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer is directly called in the memory to analyze the base sequence and generate a sequencing report. In this way, the basecall process of sequencing and the subsequent analysis process can be connected through the memory, and the sequencing and analysis processes of the sample to be analyzed are carried by one process, which is easy and quick for operators to get started. After the memory is connected, the analysis efficiency can be improved and I / O congestion can be reduced. Moreover, the base sequence in the binary encoding format shortens the reading and writing time, is more convenient for subsequent analysis process processing, improves the analysis efficiency of the overall process, and has strong adaptability. Under the condition that the existing machine parameters are basically unchanged, through the new encoding form and process processing, it can improve the program operation efficiency while extending the service life of the machine without affecting the accuracy of sequencing analysis.

[0198] In one embodiment, the present application also provides a storage medium storing computer-readable instructions. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the flow sequencing analysis method as described in any one of the above embodiments.

[0199] In one embodiment, the present application further provides a computer device, including: one or more processors, and a memory.

[0200] The memory stores computer-readable instructions, and when the computer-readable instructions are executed by the one or more processors, the steps of the flow sequencing analysis method described in any one of the above embodiments are performed.

[0201] Schematically, as shown in FIG5 , FIG5 is a schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. The computer device 300 can be provided as a server. Referring to FIG5 , the computer device 300 includes a processing component 302, which further includes one or more processors, and a memory resource represented by a memory 301 for storing instructions that can be executed by the processing component 302, such as an application. The application stored in the memory 301 can include one or more modules, each of which corresponds to a set of instructions. In addition, the processing component 302 is configured to execute instructions to perform the flow sequencing analysis method of any of the above embodiments.

[0202] The computer device 300 may further include a power supply component 303 configured to perform power management of the computer device 300, a wired or wireless network interface 304 configured to connect the computer device 300 to a network, and an input / output (I / O) interface 305. The computer device 300 may operate based on an operating system stored in the memory 301, such as Windows Server™, Mac OS X™, Unix™, Linux™, Free BSD™, or the like.

[0203] Those skilled in the art will understand that the structure shown in FIG5 is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0204] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0205] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referenced to each other.

[0206] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A flow sequencing analysis method, characterized in that: The method comprises: Obtain the samples to be analyzed and the corresponding analysis requirements, as well as the current idle status of each sequencer; Determine a target sequencer according to the sample characteristics of the sample to be analyzed, the analysis requirements, and the current idleness of each sequencer, and sequence the sample to be analyzed by the target sequencer to obtain a base sequence corresponding to the sample to be analyzed, wherein the base sequence is a binary sequence; The base sequence is input into the memory, and the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer is called to analyze the base sequence and generate a sequencing report.

2. The flow sequencing analysis method according to claim 1, characterized in that: The current sequencers include a first sequencer using second-generation sequencing technology and / or a second sequencer using third-generation sequencing technology.

3. The flow sequencing analysis method according to claim 2, characterized in that: The step of determining a target sequencer according to the sample characteristics of the sample to be analyzed, analysis requirements, and the current idleness of each sequencer includes: Inputting the sample characteristics and analysis requirements of the sample to be analyzed into a pre-configured target classification model, and obtaining the type of sequencer applicable to the sample to be analyzed output by the target classification model; wherein the target classification model is obtained after training with historical analysis samples containing sample characteristics and analysis requirements as training samples and the type of sequencer applicable to the training samples as sample labels; The target sequencer is determined according to the type of sequencer applicable to the sample to be analyzed and the current idle status of each sequencer.

4. The flow sequencing analysis method according to claim 3, characterized in that: The training process of the target classification model includes: Obtain multiple historical analysis samples including sample characteristics and analysis requirements and actual sequencer types applicable to each historical analysis sample, and divide the multiple historical analysis samples into a training set and a test set; The historical analysis samples in the training set are input into the initial classification model to obtain the initial The predicted sequencer type of the historical analysis sample output by the initial classification model; Training the initial classification model with the goal of making the predicted sequencer type close to the actual sequencer type applicable to the historical analysis samples; When the initial classification model meets the preset training conditions, the historical analysis samples in the test set are used to adjust and optimize the trained initial classification model to obtain the final target classification model.

5. The flow sequencing analysis method according to claim 2, characterized in that: The step of determining a target sequencer according to the sample characteristics of the sample to be analyzed, analysis requirements, and the current idleness of each sequencer includes: The sample characteristics and analysis requirements of the sample to be analyzed are compared with the corresponding thresholds respectively, or the analysis requirements of the sample to be analyzed are compared with the corresponding thresholds alone, and the target sequencer is determined according to the comparison results and the current idle status of each sequencer.

6. The flow sequencing analysis method according to claim 5, characterized in that: The step of comparing the sample characteristics and analysis requirements of the sample to be analyzed with corresponding thresholds respectively, or comparing the analysis requirements of the sample to be analyzed with corresponding thresholds alone, and determining a target sequencer according to the comparison result and the current idleness of each sequencer, includes: If the analysis requirement of the sample to be analyzed is that there is no requirement for sequencing cost or it is lower than a preset cost threshold, the analysis accuracy is greater than a preset accuracy threshold, or there is a detection requirement for a specific function, the first sequencer and the second sequencer are used together as target sequencers, and the sequencing results of the target sequencer are verified by a sequencer using first-generation sequencing technology; If the analysis requirement of the sample to be analyzed is that the sequencing cost is lower than the preset cost threshold and the analysis accuracy is higher than the preset accuracy threshold, determining the target sequencer according to the idle conditions of different types of first sequencers; If the analysis requirement of the sample to be analyzed is that the sequencing cost is lower than the preset cost threshold, the analysis accuracy is higher than the preset accuracy threshold, and the sample characteristic of the sample to be analyzed is that the amount of data off the machine is less than the preset data amount threshold, then according to the accuracy and whether the functions of the first sequencer and the second sequencer meet the requirements, a sequencer with higher accuracy and functions that meet the requirements is selected as the target sequencer; or, if the accuracy and functions of the first sequencer and the second sequencer are the same, according to the availability of the first sequencer and the second sequencer, a sequencer with higher accuracy and functions that meet the requirements is selected as the target sequencer. Determine the target sequencer based on the situation; If the analysis requirement of the sample to be analyzed is that there is no requirement for sequencing cost, the analysis accuracy is less than the preset accuracy threshold, the sequencing time is less than the preset sequencing time, and the analysis environment of the sample to be analyzed is an abnormal environment, then Nanopore in the second sequencer is selected as the target sequencer.

7. The flow sequencing analysis method according to claim 2, characterized in that: The step of sequencing the sample to be analyzed by the target sequencer to obtain a base sequence corresponding to the sample to be analyzed includes: The target sequencer is used to sequence the sample to be analyzed, and the sequencing result of the target sequencer is converted into a binary sequence according to the sequencing method of the target sequencer, so as to obtain a base sequence corresponding to the sample to be analyzed.

8. The flow sequencing analysis method according to claim 7, characterized in that: The method of sequencing the sample to be analyzed by the target sequencer and converting the sequencing result of the target sequencer into a binary sequence according to the sequencing method of the target sequencer to obtain a base sequence corresponding to the sample to be analyzed includes: If the target sequencer is the first sequencer, the sample to be analyzed is sequenced directly by the first sequencer, and after base recognition is performed on the fluorescent signal obtained by sequencing by an optical device, the base recognition result is converted into a binary sequence in a binary coding format to obtain a base sequence corresponding to the sample to be analyzed; Alternatively, the sample to be analyzed is sequenced by the first sequencer, and after the light intensity value of the fluorescence signal obtained by sequencing is detected by a semiconductor chip, the light intensity signal is converted into an electrical signal in a binary coding format to obtain a base sequence corresponding to the sample to be analyzed; If the target sequencer is a second sequencer, the sample to be analyzed is sequenced directly by the second sequencer, and the current signal obtained by sequencing is converted into a binary sequence in a binary coding format to obtain a base sequence corresponding to the sample to be analyzed; Alternatively, the sample to be analyzed is sequenced by the second sequencer, and after the light intensity value of the fluorescent signal obtained by sequencing is detected using a semiconductor chip, the light intensity signal is converted into an electrical signal in a binary coding format to obtain a base sequence corresponding to the sample to be analyzed.

9. The flow sequencing analysis method according to claim 8, characterized in that: The optical device includes a beam splitter and a convex lens; After performing base recognition on the fluorescent signal obtained by sequencing by an optical device, the base recognition result is converted into a binary sequence using a binary coding format, including: A beam of photons corresponding to the fluorescence signal obtained by sequencing is divided into four beams by the beam splitter, and the four beams are filtered respectively, and then the filtered four beams are converted into parallel light by four convex lenses; The parallel light is converted into a binary sequence using a CMOS camera.

10. The flow sequencing analysis method according to claim 8, characterized in that: The method of using a semiconductor chip to detect the light intensity value of the fluorescent signal obtained by sequencing and converting the light intensity signal into an electrical signal in a binary coding format includes: After packaging the upper stack of the semiconductor chip, the packaged semiconductor chip is used to perform intelligent color filter processing on the fluorescence signal obtained by sequencing, so that the fluorescence signal is filtered by the four color filters in the intelligent color filter and then falls on the designated position of each filter in the lower light guide; After collecting the color-filtered fluorescent signal at the lower light guide, the light intensity value of the color-filtered fluorescent signal is detected by the photodiode in the semiconductor chip to obtain the detection result; The detection result is converted into an electrical signal in a binary coding format by a CMOS camera.

11. The flow sequencing analysis method according to claim 2, characterized in that: The calling of an analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer to analyze the base sequence includes: If the species to which the sample to be analyzed belongs is human for which a reference genome exists, then when the target sequencer is a first sequencer, a first analysis method is called to analyze the base sequence; when the target sequencer is a second sequencer, a second analysis method is called to analyze the base sequence; and when the target sequencers are the first sequencer and the second sequencer, a third analysis method is called to analyze the base sequence; If the species to be analyzed belongs to is another species for which there is no reference genome, then when the target sequencer is the first sequencer, the first assembly method is called to assemble the base sequence, and when the target sequencer is the second sequencer, the second assembly method is called to assemble the base sequence. The sequence is assembled, and when the target sequencer is the first sequencer and the second sequencer, the third assembly method is called to assemble the base sequence, and the assembled base sequence is analyzed.

12. The flow sequencing analysis method according to claim 11, characterized in that: When the target sequencer is a second sequencer, calling a second analysis method to analyze the base sequence includes: When the target sequencer is a second sequencer, performing sequence comparison, sorting, deduplication, variation detection, sequence annotation, and interpretation on the base sequence to obtain a sequencing report; Alternatively, the base sequence is spliced ​​using a preset sequence splicing algorithm to obtain variation information corresponding to the base sequence, and the variation information is annotated and interpreted to obtain a sequencing report.

13. The flow sequencing analysis method according to claim 11, characterized in that: When the target sequencers are the first sequencer and the second sequencer, calling the third assembly method to assemble the base sequence, and analyzing the assembled base sequence, including: When the target sequencers are the first sequencer and the second sequencer, determining evaluation results of the user evaluating the multiple pre-provided assembly methods according to different evaluation indicators, and selecting at least one assembly method from the multiple pre-provided assembly methods as the third assembly method according to the evaluation results; The third assembly method is called to assemble the base sequence, and the assembled base sequence is analyzed.

14. The flow sequencing analysis method according to claim 13, characterized in that: The calling the third assembly method to assemble the base sequence and analyzing the assembled base sequence includes: Calling the third assembly method to assemble the base sequence of the first sequencer according to the method of cutting kmer and forming a de Bruijn graph, and splicing the assembled base sequence with the base sequence of the second sequencer to obtain a spliced ​​genome and corresponding variation information; Alternatively, the third assembly method is called to compare the base sequence of the first sequencer to the base sequence of the second sequencer according to the kmer and hash alignment method, and after obtaining the alignment data, the base sequence of the second sequencer is corrected according to the alignment data, and the corrected base sequence is spliced ​​with the base sequence of the first sequencer to obtain the spliced ​​sequence. Genome and corresponding mutation information; Alternatively, the third assembly method is called to pre-assemble the base sequences of the first sequencer into contigs, and then the base sequences of the second sequencer are corrected by using the contigs, and the corrected base sequences are assembled to obtain a spliced ​​genome and corresponding variation information; Alternatively, the third assembly method is called to assemble the base sequence of the first sequencer according to the method of cutting kmer and forming a de Bruijn graph, and the base sequence of the second sequencer is aligned to the assembled de Bruijn graph, and a scaffold is constructed according to the alignment result to obtain a spliced ​​genome and corresponding variation information.

15. The flow sequencing analysis method according to claim 2 or 11, characterized in that: The calling of an analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer to analyze the base sequence also includes: If the target sequencer is the first sequencer or the second sequencer, calling a species tree construction method corresponding to the species to which the sample to be analyzed belongs, constructing a corresponding species tree for the species to which the sample to be analyzed belongs, and analyzing the base sequence according to the constructed species tree; Alternatively, if the target sequencers are the first sequencer and the second sequencer, the base sequence of the first sequencer and the base sequence of the second sequencer are transcribed to form transcriptome data, and the transcriptome data are compared, and the data length, quality, and integrity are analyzed to parse the regulatory mechanism of expression metabolism of the species to which the sample to be analyzed belongs.

16. The flow sequencing analysis method according to claim 11, characterized in that: When the target sequencer is a first sequencer and a second sequencer, the method further includes: When annotating the variation results of the base sequence, or annotating the species of the assembled base sequence, if the quality values ​​of some sites in the base sequence or the assembled base sequence are worse than the preset quality threshold and have a direct impact on the annotation results, the site mutation or short fragment mutation of the some sites are verified by a sequencer using the first-generation sequencing technology.

17. A flow sequencing analysis device, characterized in that: include: The data acquisition module is used to obtain samples to be analyzed and the corresponding analysis requirements, as well as the current idle status of each sequencer; The sequencing module is used to determine the target sequencer according to the sample characteristics of the sample to be analyzed, the analysis requirements and the current idleness of each sequencer, and to sequence the sample through the target sequencer. The sample to be analyzed is sequenced to obtain a base sequence corresponding to the sample to be analyzed, wherein the base sequence is a binary sequence; The analysis module is used to input the base sequence into the memory, call the analysis method corresponding to the species to which the sample to be analyzed belongs and the sequencing technology used by the target sequencer, analyze the base sequence, and generate a sequencing report.

18. A storage medium, characterized in that: The storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the flow sequencing analysis method according to any one of claims 1 to 16.

19. A computer device, characterized in that: include: one or more processors, and memory; The memory stores computer-readable instructions, and when the computer-readable instructions are executed by the one or more processors, the steps of the flow sequencing analysis method according to any one of claims 1 to 16 are performed.

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