RU2792228C1 - Method, device and computer device for gene analysis based on shared memory - Google Patents

Abstract

FIELD: biotechnology.

SUBSTANCE: described is a method for gene analysis based on shared memory, performed by a computer and comprising the steps of: reading sample data and pre-processing sample data, moreover, sample data is data generated or formed after gene sequencing of samples; performing gene analysis of the pre-processed sample data and determining whether a library file required for gene analysis is in the shared gene memory; if found, obtain the required library file from the shared gene memory, converting the desired library file into a gene analysis process of the pre-processed sample data, and performing gene analysis, the sample data contains a plurality of data groups, each data group has a corresponding sample process, each sample process is included in an area of shared gene memory to obtain the required library file. A corresponding device, a computer device, a computer-readable medium, is also described.

EFFECT: method can significantly reduce the I/O time and occupancy for loading a library file from a hard disk, therefore, the efficiency of the analysis can be improved.

12 cl, 11 dwg

Description

The field of technology to which the invention belongs

The present disclosure relates to the field of data processing technology, in particular to a method, apparatus and computer apparatus for gene analysis based on shared memory, and to a computer-readable storage medium.

State of the art

With the gradual implementation of the Human Genome Project and the rapid development of sequencing technology, the cost of sequencing has been greatly reduced, and the speed of sequencing has been greatly increased. The cost of sequencing the entire human genome has dropped to less than $1,000, and the amount of DNA sequencing data has grown exponentially. How to quickly use and present data, then analyze and explain potential problems in gene sequences and uncover the information people need from the vast amount of data has become a pressing problem that must be solved. More and more applications of sequence data generated by whole genome sequencing (WGS) and the constant demand for rapid analysis and processing of large volumes of sequence data have formed a new bottleneck in the data analysis technique, which limits the clinical application of second generation sequencing technology.

There are currently many different kinds of methods and tools available internationally in the field of bioinformatics for analyzing second generation sequencing data. The most commonly used process contains mainly data entry, preprocessing operation, sequence comparison, annotation, variant identification and path analysis. However, it takes a long time to apply the whole process in WGS. In addition, specialized processes requiring sample input, such as sample merging, sample splitting, and so on, must be performed separately, and therefore the operation efficiency is low and the I/O requirement is increased. In addition, during data analysis, index files must be downloaded separately for each stage of analysis and processing. If multiple tasks load the same index file, then solving the tasks consumes more memory and takes longer.

Disclosure of the essence of the invention

From this point of view, the disclosure presents a shared memory based method, apparatus, computer-based gene analysis device, and computer-readable media for solving the technical problem of low operational efficiency caused by the requirement of processes such as merging of input samples in some pipelines, high memory consumption, caused by repetitive loading of index files during prior art data analysis.

Some embodiments of this disclosure provide a shared memory based gene analysis method comprising: reading sample data and preprocessing sample data; performing gene analysis of the pre-processed sample data and determining whether a library file required for gene analysis is in the shared gene memory; if so, obtaining the desired library file from the shared gene memory, transforming the desired library file in a gene analysis process of the pre-processed sample data, and terminating the gene analysis.

In some embodiments, the method further comprises: determining if the required library file satisfies a load condition in the case where the library file required for gene analysis is not in shared gene memory; and downloading the required library file into the shared gene memory, in case the download condition is satisfied.

In some embodiments, determining whether the required library file satisfies the load condition when the required library file for gene analysis is not present in the shared gene memory and whether to load the desired library file into the shared gene memory when the load condition is satisfied comprises : obtaining required library file information and shared gene memory information, where the required library file information contains the space requested by the required library file and the number of archive download requests of the desired library file, and the shared gene memory information contains the remaining space of the shared gene memory; and if the number of archive download requests of the desired library file is greater than the first predetermined number, and the space requested by the desired library file is less than the remaining space of the shared gene memory, loading the desired library file into the shared gene memory.

In some embodiments, the desired library file information comprises a download request rate of the desired library file; the shared gene memory information comprises download request rates of all library files in the shared gene memory; determining whether the required library file satisfies the load condition, and whether to load the required library file into the shared gene memory in the case where the load condition is satisfied, further comprises: a file greater than the remaining space of the shared gene memory, ranking the required library file and all library files in order of priority according to the download request frequency of the required library files and the download request frequencies of all library files, to obtain the priority of the download request frequencies of each library file; if the priority of the download request rates of the required library file is higher than the priority of the library file in the shared gene memory, and if the remaining space of the shared gene memory after deletion of the library file with the lower priority of the download request frequency in the shared gene memory is greater than or equal to the space requested the desired library file, deleting the library file with a lower load request frequency priority in the shared gene memory; and loading the required library file into the shared gene memory.

In some embodiments, the method further comprises: setting a shared gene memory for the library files used in gene analysis, setting the size of the shared gene memory, the number of library files that can be accommodated, the name of each library file, and the size offset of each library file; and loading the library files commonly used in gene analysis into a shared gene memory corresponding to the size of the shared gene memory, the number of library files that can be accommodated, the name of each library file, and the size offset of each library file.

In some embodiments, the gene analysis comprises an alignment analysis, a variation analysis, and an annotation analysis, the method further comprises: performing an alignment analysis, a variation analysis, and an annotation analysis on sample data preprocessed in sequence, wherein, in the case where the preprocessed sample data contains multiple groups of these samples, multiple groups of these samples are simultaneously at the same stage or at different stages of gene analysis.

In some embodiments, the gene analysis further comprises sorting analysis and label-duplication analysis, where after performing an alignment analysis, analysis of variation, and annotation analysis of sample data pre-processed in sequence, the method further comprises: labeling sample data after alignment analysis using a positional tag; and performing, by means of the module, sorting analysis and label-duplication analysis on the labeled sample data.

In some embodiments, the method further comprises connecting some or all of the steps of gene analysis through the use of memory.

In some embodiments, the pre-processing of sample data comprises performing quality control, filtering, and statistical processing on the sample data.

Some embodiments of the disclosure also provide a shared gene memory based gene analysis device, comprising: a data reader configured to read sample data; a data pre-processing module configured to pre-process the sample data; and a gene analysis module configured to perform gene analysis of the pre-processed sample data and determine whether a library file required for gene analysis is in the shared gene memory; and if so, obtaining the desired library file from the shared gene memory, transforming the desired library file in a gene analysis process of the pre-processed sample data, and completing the gene analysis.

Some embodiments of the disclosure further provide a computing device comprising a memory, a processor, and a computer program stored in the memory and executed by the processor. The processor performs the following steps: reading the sample data and pre-processing the sample data; performing gene analysis of the pre-processed sample data and determining whether a library file required for gene analysis is in the shared gene memory; if so, obtaining the desired library file from the shared gene memory, transforming the desired library file in a gene analysis process of the pre-processed sample data, and terminating the gene analysis.

Some embodiments of the disclosure further provide a computer-readable storage medium that stores a computer program, where the computer program, when executed by the processor, performs the steps of: reading sample data of the sample data and pre-processing the sample data; performing gene analysis of the pre-processed sample data and determining whether a library file required for gene analysis is in the shared gene memory; and if so, obtaining the desired library file from the shared gene memory, converting the desired library file in a gene analysis process of the pre-processed sample data, and terminating the gene analysis.

A method, apparatus, computerized gene analysis device based on shared gene memory, and computer-readable storage medium are provided in embodiments of the disclosure. First, the sample data is read, then the sample data is pre-processed, and then the gene analysis of the pre-processed sample data is performed. In gene analysis, it is necessary to determine whether the library file required for gene analysis is in the shared gene memory of the file library; if so, obtain the required library file from the shared gene memory and transform it at gene analysis corresponding to the sample data to complete the corresponding analysis. In a gene analysis method based on shared gene memory, a shared gene memory mechanism is used to establish gene analysis indexes (for example, containing alignment analysis, analysis of variations, annotation analysis, and so on) and then store in a file database (i.e., library files) required for gene analysis in shared gene memory. The library file can be easily converted from shared gene memory during gene analysis performed on these samples. On the one hand, the I/O time and occupancy for loading a library file from the hard disk is significantly reduced. On the other hand, communication of multiple processes during gene analysis is facilitated and repetitive library file loading is avoided.

Brief description of the drawings

In order to more clearly explain the embodiments of the present disclosure or the prior art, a brief introduction will be provided below for the drawings required for use in describing the embodiments or the prior art. Obviously, the drawings explained below are simply embodiments of the present disclosure. Those skilled in the art may also obtain other drawings corresponding to such drawings, provided that no inventive effort is exerted.

Fig. 1 illustrates an embodiment of the application of a shared memory based gene analysis method according to some embodiments of the present disclosure;

Fig. 2 is a flowchart of a shared memory based gene analysis method according to some embodiments of the present disclosure;

Fig. 3 illustrates the operation of shared memory in accordance with some embodiments of the present disclosure;

Fig. 4 is a flow chart of shared memory construction in some embodiments of the present disclosure;

Fig. 5 is a block diagram of shared memory in some embodiments of the present disclosure;

Fig. 6 is a flowchart of a shared memory based gene analysis method according to some embodiments of the present disclosure;

Fig. 7 shows central processing unit (CPU) usage and I/O usage when gene analysis is performed using method A in accordance with some embodiments of the present disclosure;

Fig. 8 shows CPU usage and I/O usage when gene analysis is performed using method B according to some embodiments of the present disclosure;

Fig. 9 shows CPU usage and I/O usage when gene analysis is performed using Method C according to some embodiments of the present disclosure;

Fig. 10 is a block diagram of a shared memory based gene analysis device in accordance with some embodiments of the present.

Fig. 11 is a block diagram of a computing device in accordance with some embodiments of the present disclosure.

Implementation of the invention

Below, the technical solutions of the embodiments of the present disclosure will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments obtained without creative effort by those skilled in the art based on the embodiments of the present disclosure should fall within the protection scope of the present disclosure.

Glossary:

A gene (Mendelian factor) refers to a DNA or RNA sequence that carries genetic information (that is, a gene is a piece of DNA or RNA with genetic effects), also known as a genetic factor, which is the main genetic building block that governs biological traits. A gene expresses the genetic information it carries, directing protein synthesis and thus controlling the traits of individual organisms. Gene sequencing is a new type of gene detection technology that analyzes and determines the entire sequence of genes from blood or saliva to predict the possibility of a variety of diseases, individual behavioral characteristics, and intelligent behavior.

Read: A short sequencing fragment, which is sequencing data generated by a high-throughput sequencer. Whole genome sequencing will generate tens of millions of reads. Then, by splicing these reads together, a complete genome sequence can be obtained.

Alignment Analysis: Reads ordered by NGS are stored in FASTQ files. Although they originally come from an ordered genome, the consistent relationship between different reads in the files is lost after DNA library creation and sequencing. Therefore, there is no positional relationship between two reads that are next to each other in FASTQ files. All of them are short sequences derived randomly from certain positions in the original genome. So first we have to arrange a lot of short sequences, compare them one by one with the reference genome of the variety, find the position of each read on the reference genome, and then arrange them in order. This process is called by comparing sequencing data.

Sorting analysis: Why are BAM files output randomly after BWA comparison? The reason is that these ordered reads in FASTQ files are randomly distributed throughout the genome. The first step of the comparison is to locate the reads one by one on the reference genome according to their order in the FASTQ files and then output them directly. It is not possible at this stage to automatically recognize the sequence of their comparison positions and rebuild the comparison results. Therefore, in the resulting file after comparison, the positional order of the records is chaotic. We need to sort the records for the next step, such as marking-duplicate, which is the reason for the need for sorting.

Marking-duplication: After sorting is completed, deduplication (ie, removal of duplicated PCR sequences) is performed. What is a duplicate sequence? How is it created and why should it be removed? This is due to library building and sequencing in the experimental process. Prior to NGS sequencing, a sequencing library must be created: cut the original DNA sequence by physical (ultrasonic) interruption or use a chemical reagent (enzymatic digestion) and then select sequences in a specific length range for PCR amplification and computer sequencing. Therefore, the duplicated sequence here is actually introduced during the PCR process.

Baseline Quality Score Correction: The sequencing process should (to the extent possible) correct for bias because variant identification is a step that relies heavily on sequencing baseline quality scoring results. This quality score is an important (even the only) indicator to measure how much to adjust the base we have sequenced. This cannot be measured directly, but a very close distribution result can be obtained by statistical means. A known variation found in the aggregate is likely to be somewhat the same. Therefore, we can compare and analyze the result of the comparison directly, exclude all known sites of variation, and then calculate how many bases differ from the bases on the reference genome after comparison for each (reported) quality score result. These other bases are treated as false bases and their quantitative ratio reflects the actual base error rates, which are converted into Phred system scores. This information is output to the calibration table file and is used to re-adjust the base quality score result in the original BAM file. A new BAM file is output using these new quality scoring results.

Variant identification and analysis: The goal of variant identification and analysis should be to accurately detect the set of variants in the genome of each sample (such as a human), that is, those DNA sequences that differ between individuals.

In order to more clearly and clearly define the object, the technical solution and the advantages of the present application, the present application will be further described in detail in conjunction with the drawings and embodiments. It should be understood that the detailed embodiments to be described herein are used only to explain the present application, but are not used to limit the present application.

This method can be applied to terminal 102 shown in FIG. 1. The terminal may be a personal computer, laptop, etc. The terminal 102 is connected to a gene sequencing device 104, which may be a gene sequencer, etc.

When the terminal 102 is connected to the gene sequencing device 104 via a local interface, the gene sequencing device 104 can send post-sequencing sample data to the terminal 102. In addition, the terminal 102 can receive post-sequence sample data from the gene sequencing device 104 via commands.

In some embodiments, as shown in FIG. 2, a shared memory based gene analysis method is provided. By way of illustration, this method is applied to the terminal shown in FIG. 1 as an example, and contains the following steps: S202 - S206.

In step S202, the sample data is read, and the sample data is pre-processed.

Sample data is data generated or formed after gene sequencing of samples. The number of samples may be one or more groups.

In an optional embodiment, the pre-processing of the sample data comprises performing quality control, filtering operations, and statistical processing of the sample data.

Data obtained from gene sequencing is referred to as raw data (i.e., raw reads or raw data). The raw data may contain low quality sequences and spliced sequences that will affect the result of the analysis. Therefore, data processing sequences, such as quality control, filtering operation, and statistical processing, must be performed on the raw data to remove extraneous additions to the raw data and determine whether the sequencing data is suitable for subsequent analysis.

In step S204, a gene analysis of the pre-processed sample data is performed and it is determined whether the library file required for gene analysis is in the shared gene memory.

Usually, after pre-treatment of these samples, it is necessary to perform an appropriate gene analysis of these samples. General analysis contains mainly sequence alignment (i.e., alignment analysis), variant determination (i.e., analysis of variance), annotational statistics (i.e., annotation analysis), and sequential path analysis (such as GO, KEGG analysis, and path analysis). passage of proteins). However, no matter what kind of analysis is performed, it must use an analytical database. For example, a reference genome database is required for alignment analysis, a species genome database (such as a human genome database) is required for variant determination, an annotation database is required for annotation analysis, a pathway database is required for pathway analysis, etc. Every database has a large amount of data. These databases must be loaded when analysis of sample data is performed.

Shared memory is the modern way of communication between processes in System V. Shared memory, as its name implies, allows two unrelated processes to access the same logical memory and is a very efficient way to share and transfer data between two running processes. Memory shared by different processes is usually the same piece of physical memory. Processes can attach the same piece of physical memory to their own address space, and all processes can access addresses in shared memory. If a process writes data to shared memory, the change will immediately affect any other process that can access the same piece of shared memory.

In FIG. 3 schematically shows the principle of shared memory communication. In Linux, each process has its own process control block (PCB) and address space (Addr Space), and has an associated page table that is used to convert the process's virtual addresses to physical addresses and is managed through the memory management block. unit, MMU). Two different virtual addresses can be mapped to the same area in physical space using the page table, and the area they point to is shared memory. In FIG. 3 shows two processes, ProcA and ProcB. When the virtual addresses through the page tables of the two processes are converted to a physical address, there is a shared memory area of the physical address, that is, shared memory, that can be seen by two processes at the same time. Thus, when one process writes and another process reads, inter-process communication can be implemented between the two processes. For shared memory, its implementation uses the principle of reference counting. When a process detaches a shared memory area, the counter is decremented by one. When a process successfully attaches to a shared memory region, the counter is incremented. The shared memory area can only be deleted if the counter becomes zero. When a process terminates, the shared memory area attached to it will automatically detach from it.

In embodiments, a shared gene memory is generated by gene analysis for library files and may store databases commonly used in gene analysis processing. When a database is needed in the analysis of sample data, it can be obtained directly from shared gene memory, which significantly reduces the time to load the database from the disk-load library. In addition, when multiple groups of sample data are analyzed at the same time, the database can be shared among multiple groups of sample data, which reduces repetitive downloads and I/O occupancy.

In an optional embodiment, as shown in FIG. 4, a method for constructing a shared memory is also provided, comprising steps S402-S404.

In step S402, the shared gene memory for the library files used in gene analysis is set, and the size of the shared gene memory, the number of library files that can be allocated, the name of each library file, and the size offset of each library file are set.

In step S404, library files commonly used in gene analysis are loaded into the shared gene memory according to the size of the shared gene memory, the number of library files that can be accommodated, the name of each library file, and the size offset of each library file.

As shown in FIG. 5, in the target system (ie, the hardware device used for gene analysis of sample data), a certain area is selected as shared library files in gene analysis. The appropriate size of the shared gene memory is determined according to the storage space, processing capability, and other characteristics of the end system. The content written or stored in the shared gene memory area mainly contains: building the header of the shared gene memory table in the node's physical memory: 1) first, store the number (n) of the defined shared libraries and the total length (Len) of the shared areas; 2) store the name (eg, Lib1, Lib2) and length offset (offset1, offset2) of each specified library file in shared gene memory; 3) storing the data of each specified library file in the selected area in turn.

Its working principle is as follows: sample data can contain multiple groups of data; each data group has a corresponding sample processing process. Among the sample processing processes P1-PN, each process has its own process control block (PCB) and address space (Addr Space) and has a corresponding page table that is used to convert the virtual addresses of the process to physical addresses and is controlled through the control block. memory (memory management unit, MMU). Two different virtual addresses can map to the same area in physical space using the page table, and the area they point to is shared memory. With the above method, each sample processing process can input a shared memory area to obtain a desired library file in the shared memory area.

In step S206, if yes, the required library file is obtained from the shared gene memory, the required library file is converted to the preprocessed sample data gene analysis process, and the gene analysis is terminated.

In the gene analysis method based on the shared gene memory provided in the embodiments of the disclosure, sample data is first read and then the sample data is preprocessed, and then gene analysis is performed on the preprocessed sample data. In gene analysis, it is necessary to determine whether the library file required for gene analysis is in the shared gene memory of the library files; if so, obtain the desired library file from the shared gene memory and transform in the gene analysis process corresponding to the sample data to complete the corresponding analysis. The gene analysis method based on shared gene memory uses a shared gene memory mechanism to set up indexes for gene analysis (for example, containing alignment analysis, analysis of variations, annotation analysis, and so on) and then store files required for gene analysis in a database (that is, library files) of shared gene memory. The library file can be easily converted from shared gene memory into a gene analysis process performed on sample data. On the one hand, the I/O time and occupancy for loading a library file from the hard disk is greatly reduced. On the other hand, communications among multiple processes in the gene analysis process are simplified and reloading of the library file can be avoided.

In some embodiments, the method further comprises: determining if the required library file satisfies a load condition in the case where the library file required for gene analysis is not in shared gene memory; and loading the required library file into the shared gene memory in case the loading condition is satisfied.

Specifically, if the required library file in the gene analysis is not in the shared gene memory, it is determined whether the required library file satisfies the loading condition. If the load condition is satisfied, the required library file can be loaded into the shared gene memory. On the one hand, it is possible to more quickly and more efficiently load the desired library file into the shared gene memory and then obtain the desired library file from the shared gene memory; on the other hand, it can also make it easier for other sample data processes to use the required library file, avoiding reloading.

In some embodiments, determining whether the required library file satisfies the load condition in the case where the required library file for gene analysis is not in the shared gene memory and whether to load the required library file into the shared gene memory in the case where the load condition is satisfied, contains:

obtaining information about the required library file and information about the shared gene memory, in which the information about the required library file contains the space requested by the required library file and the number of archive download requests of the desired library file, and the information about the shared gene memory contains the remaining space of the shared gene memory; and if the number of archive download requests of the desired library file is greater than the first predetermined number and the space requested by the desired library file is less than the remaining space of the shared gene memory, loading the required library file into the shared gene memory.

The required library file information refers to information related to the required library file, which may include the type of the required library file, the size of the required library file, the space requested by the required library file, the number of archive download requests, and the download request frequency of the required library file, etc. . The shared gene memory information refers to information related to the shared gene memory, mainly containing the size of the shared gene memory, the remaining space of the shared gene memory, and so on.

The first setpoint is a setpoint that can be used to reflect the importance of the library file to some extent. Thus, if the number of archive download requests is greater than the first predetermined number, this indicates that the required library file is needed or frequently used, that is, the required library file is important in gene analysis and can be loaded into shared gene memory to facilitate it. use for other sample data. After determining the importance of the required library file, it is further necessary to determine if the remaining shared gene memory space is sufficient to store the required library file, that is, to determine if the space requested by the required library file is less than the remaining shared gene memory space. If so, then the required library file can be directly loaded into the shared gene memory.

In some embodiments, when the requested library file information further comprises a load request rate of the desired library file, the shared gene memory information comprises load request rates of all library files in the shared gene memory; determining whether the required library file satisfies the load condition, and whether to load the required library file into the shared gene memory in the case where the load condition is satisfied, further comprises: if the number of archive requests to load the required library file is greater than the first predetermined number, and space, requested by the required library file is greater than the remaining shared gene memory space, rank the required library file and all library files in order of priority according to the download request frequency of the required library file and the download request frequencies of all library files, to obtain the priority of the download request frequency of each library file; if the load request rate priority of the required library file is higher than the priority of the library file in the shared gene memory, and if the remaining space of the shared gene memory after deletion of the library file with the lower load request frequency priority in the shared gene memory is greater than or equal to the space requested the desired library file, deleting the library file with a lower load request frequency priority in the shared gene memory; and loading the required library file into the shared gene memory.

Specifically, if it is determined that the space requested for the required library file is larger than the remaining shared gene memory space, this indicates that the remaining shared gene memory space is insufficient to store the required library file; in this case, it is necessary to compare the required library file with the library file already stored in the shared gene memory, remove the library file with a low download request rate corresponding to the library file download request frequency priorities, and then load the desired library file into the shared gene memory.

In embodiments, the required library file and the library files stored in the shared gene memory are ranked in order of priority primarily according to the frequency of each library file download request. If the download request frequency priority of the desired library file is higher than the priority of the library file in the shared gene memory, the library file in the shared gene memory is deleted to load the required library file into the shared gene memory. The above process takes a comprehensive look at the sizes of all library files. It is only necessary to ensure that the memory occupied by the remote library file is sufficient to store the required library file.

Thus, when the desired library file is not in the shared gene memory during the gene analysis process, the library file can be first loaded into the shared gene memory to improve the efficiency of subsequent computation.

In some embodiments, the gene analysis comprises an alignment analysis, a variation analysis, and an annotation analysis; the method further comprises the steps of: performing an alignment analysis, an analysis of variations, and an annotation analysis of the sample data pre-processed in sequence, wherein in the case where the pre-processed sample data contains multiple groups of sample data, the multiple groups of sample data are simultaneously on the same and the same stage or at different stages of gene analysis.

In embodiments, the gene analysis method comprises alignment analysis, variation analysis, and annotation analysis. However, in the process of gene analysis, there is usually a sequence requirement, that is, an alignment analysis is usually performed first, followed by an analysis of variance and then annotation analysis. However, when there are multiple sets of sample data, each set of sample data may be at the same stage or at different stages of gene analysis. For example, sample 1 data may be in an alignment analysis step, sample 2 data may be in an analysis of variance step, and sample 3 data may be in an annotational analysis step. It is also possible for sample data 1, sample data 2, and sample data 3 to be in the alignment analysis, analysis of variations, or annotation analysis at the same time. Multiple groups of sample data can be processed at the same time using a method that can further increase the speed of data processing.

In some embodiments, the gene analysis further comprises a sorting analysis and a label-duplication analysis, in which, after performing an alignment analysis, a variation analysis, and an annotation analysis of the sample data pre-processed in sequence, the method further comprises the steps of: labeling the sample data after the alignment analysis using positional tags; and performing, by means of the module, a sorting analysis and a label-duplication analysis on the labeled sample data.

Specifically, the gene analysis further comprises a sequencing analysis and a label-duplication analysis; labeling sample data after alignment analysis with positional tags is to add a tag associated with the position to the file after comparison, so that sequencing analysis and label-duplication analysis can be performed by the module, in both sequencing analysis and labeling analysis -duplication, a more efficient multi-threaded sorting can be obtained.

In some embodiments, the method further comprises connecting some or all of the steps of the gene analysis using memory.

Specifically, several steps or all of the steps in the comparison, sorting, marking-duplicate and variant determination processes in the gene analysis process can be linked by memory. The sam/bam files output intermediately can be reduced by appending each stage with memory, which reduces I/O usage.

For ease of understanding, a detailed embodiment is given below. In FIG. 6 shows the entire gene analysis process and the process in the shared gene memory area. The gene analysis process proceeds as follows: after the introduction of the samples, the data of each of the samples is pre-processed and then it is determined whether the library file required for the alignment analysis is loaded into the shared memory area; if yes, the alignment analysis is started, or otherwise, the library file is loaded from the hard drive to perform the alignment analysis; the alignment analysis process is synthesized as a flexible step by memory coupling and algorithm optimization; then, variant determination is performed and it is determined whether an annotation information library file has been loaded into the shared gene memory; if so, annotation statistics are run, or otherwise, the library file is loaded from the hard drive for annotation statistics; the analytical process ends.

The process in the shared gene memory area is as follows: if there is a request for library information lib-x (ie, the required library file), determining whether the required library file is in the shared gene memory area; if so, the library data is feedback and the process ends; if the required library file is not in the shared area of the gene memory, determining whether to load the required library file in the load method Q; if so, the required library file is loaded into the shared area of gene memory, the library data is output, and the process ends; if the requested library file is not to be loaded using the Q load method, no information is output and the process ends.

The specific steps of loading method Q are as follows: 1) determining the type and size of the required library file; 2) get the recording file; 3) reading the total memory size of the node, the size of the shared memory area, the number of archive download requests of each library type (f_type) and the total number of archive download requests of all library types (f_total) from the record file; 4) the node memory size is updated from the hard disk to prevent changing the node memory size; 5) for the type of required library file, the number of archive download requests for this type of library is increased by 1 (f_type+1); 6) the total number of archive download requests for all types of libraries is increased by 1 (f_total+1); 7) determine if there is enough remaining space to load the library; 8) query frequencies (f_type/f_total) of all types of libraries in the record file are ranked in descending order and output a ranked linked list; 9) determining if the required library file has been loaded; if the required library file has been loaded, output the index of the library; if the required library file has not been loaded and the number of download archive requests of this type of library is greater than 10, determining the priority and position in order of this type of library in all unloaded libraries; 10) if the priority of this library type is greater than the priority of the loaded library, the system predicts whether the sum of the sizes of the loaded libraries ordered after that library type in the type_list satisfies the memory size condition W for loading that library type; if so, these loaded libraries are unloaded in reverse order until condition W is satisfied; otherwise, no process is executed; 11) if the load condition is satisfied, the size record of the shared memory area is updated; 12) Otherwise, when the library has not been loaded because there is not enough memory to load, the library is marked and updated in the record file.

The recording file format is as follows:

M: 63492649171200

Len: 13492649171200

f_total: 100

Type Size Loaded Number of archive download requests f_type type_flag Libx 10000000000000 Yes 75 0 Liby 3492649171200 Yes 12 0 Libw 40000000000000 No 10 1 libz 5000000 No 3 0

type_flag indicates the reason for not loading, where 1 indicates that the loading priority of this type of library was considered first and it was not loaded due to insufficient memory, and the type_flag of the loaded library is 0.

In addition, the pseudocode of the Q loading method is as follows.

RequestShareMem(type, size) //type: type of library to share, size: size of library to share

File = RecordFile // record file

ReadFromFile(M, Len, f_type, f_total) //read from write file (M: total node memory size; Len: current size of shared memory area; f_type: number of archive requests to load this type of library; f_total: total number of archive requests loading all types of libraries;

Update (M) //update the node's memory size from the hard disk to prevent the node's memory size from changing;

f_type = f_type + 1 //update f_type

f_total = f_total + 1 //update f_total

W = M*0.5 - Len - size> 0 //condition W: determine if there is remaining space to load, 0.5 is an adjustable factor, currently 50% of the total memory is being used

type_list = SortAllTypeInFile() //rank the request frequencies (f_type/f_total) of all library types in the record file in descending order, and output the ranked linked list;

if AlreadyLoaded(type) then

id = GetShareMemId(type) // if the required library file has been loaded, print the library index

else if f_type > 10 //the number of archive download requests for this type of library is greater than 10

if IsPrior (type_list, type) //determine if this is the first priority: first in order before all other unloaded libraries whose type_flag is 0

if type_flag = 1

UnloadShareMem (type_list, type), // if the sum of sizes of loaded libraries ordered after this type of library in type_list satisfies condition W, unload these loaded libraries in reverse order until condition W is satisfied; otherwise, no process is running

if W

id = LoadShareMem(type, size)

Len = Len + size // update the size of the shared memory area

type_flag = 0

else

type_flag = 1 // mark that there is not enough memory, update the entry

id = 0

else

id = 0 //do not display information

UpdateFile(m, len, f_type, f_total, type_flag) // update record file

return id //output the index of the shared memory area, "0" represents no information

end

Some embodiments to show the results:

In order to test the effectiveness of the shared memory based gene analysis method in the embodiments of the disclosure, the three gene analysis methods, namely, method A (software without optimization (that is, all gene analysis steps are not connected using memory, and the steps are independent apart) + without using shared gene memory), method B (software with optimization (i.e., all stages of gene analysis are connected using memory) + without using shared gene memory) and method C (software with optimization ( i.e., all gene analysis steps are connected using memory) + using shared gene memory) are given to compare CPU usage and I/O busy time for different methods. The results are shown in FIG. 7-9, where in Fig. 7 shows the analysis result of Method A, FIG. 8 shows the analysis result of Method B and FIG. 9 shows the analysis result of method C.

In FIG. 7, it can be seen that the running time of the analysis part of Method A before acceleration (that is, each step of reading sample data and the pre-processing step before alignment analysis works independently and the comparison is processed directly without using shared gene memory) is 2.83 hours and using The CPU varies greatly. The execution time of the comparison section and the annotation section before acceleration (that is, the comparison and annotation are processed directly without using shared gene memory) is 2.61 hours, the CPU usage is high, and the I/O usage per second (that is, the number of transfers output to physical disk per second) is high, indicating high I/O usage and a high chance of blocking.

As can be seen in FIG. 8, the running time of the analysis section of Method B after acceleration (that is, the sample data reading step and the pre-processing step before alignment analysis are connected using memory, and the comparison is performed using shared gene memory) is 1.75 hours, and the CPU usage varies. less than method A. Working time of library comparison section before using shared gene memory (i.e., comparison is performed directly without using shared gene memory) is 2.38 hours, CPU usage is high, and I/O usage per second (that is, the number of transfers to the physical disk per second) is high, indicating that the I/O usage is high and the chance of blocking is high.

As can be seen in FIG. 9, the working time of the analysis section of method C after acceleration (that is, the sample data reading step and the pre-processing step before alignment analysis are connected by memory and comparison is performed using shared gene memory) is 1.75 hours, and the CPU usage varies less than in method A (this section is the same as in method B). The execution time of the library comparison section after using the shared gene memory (that is, the comparison is performed using the shared gene memory) is 0.82 hours, the CPU usage is high, and the I/O usage per second (that is, the number of transfers output per physical disk per second) is low, indicating that I/O usage is low and the chance of blocking is low.

Therefore, method C is used for gene analysis, that is, the steps of gene analysis are connected by memory. The way of adapting the shared gene memory in comparison, annotation and other processes can significantly reduce the time used for gene analysis and reduce the rate of I/O usage, that is, reduce I/O blocking.

It should be understood that although the steps in the flowcharts in FIG. 2, 4 and 6 are shown in the order indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless explicitly stated here, the execution of these steps is not limited to a strict order, and these steps may be executed in other orders. In addition, at least some of the steps in FIG. 2, 4 and 6 may contain multiple sub-steps or multiple steps. These sub-steps or steps are not necessarily performed simultaneously, but may alternatively be performed in conjunction with other steps or at least some of the sub-steps or steps of other steps.

In some embodiments, as shown in FIG. 10, a shared memory based gene analysis device is provided, comprising: a data reading module 102, a data preprocessing module 104, and a gene analysis module 106.

A data reading module 102 configured to read sample data.

A pre-processing module 104 configured to pre-process sample data.

A gene analysis module 106, configured to perform gene analysis of pre-processed sample data and determine whether a library file required for gene analysis is in a shared gene memory; if yes, then obtain the desired library file from the shared gene memory, transform the desired library file in the process of gene analysis of the pre-processed workings data and complete the gene analysis.

In some embodiments, the shared memory gene analysis device comprises: a library file loading module configured to determine if a desired library file satisfies a load condition in the event that the library file required for gene analysis is not in the shared gene memory; and loading the required library file into the shared gene memory, in case the loading condition is satisfied.

In some embodiments, the library file loading module comprises a module for obtaining library information and memory information.

A module for obtaining library information and memory information, configured to obtain information about the required library file and information about the shared gene memory, where the information about the required library file contains the space requested by the specified library file, and the number of archive download requests of the required library file, and the shared gene memory information contains the remaining space of the shared gene memory.

A library file loading module configured to load a desired library file into shared gene memory if the number of archive requests for loading the required library file is greater than the first required number and the space requested by the desired library file is less than the remaining space of the shared gene memory.

In some embodiments, the required library file information further comprises a requested library file download request rate; the shared gene memory information further comprises download request rates of all library files in the shared gene memory; and the library file loading module further comprises a priority ranking module and a library file deleting module.

A priority sorting module, configured to rank the desired library file and all library files in order of priority according to the download request frequency of the desired library file and the download request frequencies of all library files, to obtain the priority of the download request frequency of each library file if the number of archive requests downloads of the desired library file is greater than the first predetermined amount, and the space requested by the predetermined library file is greater than the remaining space of the shared gene memory.

A library file deletion module, configured to delete a library file with a lower download request frequency priority in the shared gene memory if the download request frequency priority of the desired library file is higher than the library file priority in the shared gene memory, and if the remaining space is shared gene memory after deleting a library file with a lower priority load request frequency in shared gene memory greater than or equal to the space requested by the given library file.

A library file loading module, further configured to load the required library file into the shared gene memory.

In some embodiments, the device further comprises: a shared gene memory setting module configured to set a shared gene memory for library files used in gene analysis, setting the size of the shared gene memory, the number of library files that can be placed, the name of each library file and the size offset of each library file.

A library file loading module further configured to load library files commonly used in gene analysis into a shared gene memory corresponding to the size of the shared gene memory, the number of library files that can be accommodated, the name of each library file, and the size offset of each library file .

In some embodiments, the gene analysis comprises an alignment analysis, a variation analysis, and an annotation analysis.

Gene analysis module 106 is configured to perform alignment analysis, analysis of variance, and annotation analysis of sample data pre-processed in sequence, where in the case where the pre-processed sample data contains multiple groups of sample data, multiple groups of sample data are simultaneously on the same stage or at different stages of gene analysis.

In some embodiments, the gene analysis further comprises a sorting and label-duplicate assay, and the device further comprises: a sorting and label-duplicate module configured to label these samples after the alignment analysis with a positional tag; and performing a sorting analysis and a label-duplication analysis by the module on the labeled sample data.

In some embodiments, the device further comprises a memory connection module configured to connect several or all of the gene analysis steps using the memory.

In some embodiments, the pre-processing module 104 is further a quality control, filtering, and statistical processing of the sample data module, and performs a quality control, filtering, and statistical processing of the sample data.

For a specific definition of a shared memory based gene analysis device, refer to the definition of the shared memory based gene analysis method described above, which will not be repeated here. All or some of the modules of the shared memory gene analysis device may be implemented in software, hardware, or a combination thereof. The above modules may be built into or independent of the processor of the computing device in the form of hardware, or stored in memory in the computer device in the form of software, to facilitate the processor to call and perform the respective operations of the above modules.

In some embodiments, a computing device is provided, which may be a server, and its internal structure may be as shown in FIG. 11. The computer device contains a processor, memory, network interface and database connected via a system bus. The processor of the computing device is used to provide computing and control capabilities. The memory of the computing device comprises a non-volatile storage medium and a memory device. The non-volatile storage medium stores an operating system, a computer program, and a database. The memory device provides an operating environment for an operating system and a computer program on a non-volatile storage medium. The database of the computer device is used to store data of the resistance equivalent model and equivalent sub-models, as well as the equivalent resistance, working resistance and contact resistance obtained during the calculation. The network interface of the computer device is used to communicate with external terminals through a network connection. A computer program is executed by a processor to implement a shared memory based gene analysis method.

Those skilled in the art may appreciate that the structure shown in FIG. 11 is a block diagram of only some of the structures associated with the schema of this application and does not constitute a limitation on the computing device to which the schema of this application applies. A particular computing device may contain more or fewer components than shown in the drawing, or may combine several components or have other arrangements of elements.

In some embodiments, a computing device is provided, comprising a processor, a memory, and a computer program stored in the memory and executed by the processor, which, when executing the computer program, performs the steps of: reading sample data and preprocessing the sample data; performing gene analysis of the pre-processed sample data, and determining whether a library file required for gene analysis is in the shared gene memory; if so, obtaining the desired library file from the shared gene memory, converting the desired library file in a gene analysis process of the pre-processed sample data, and terminating the gene analysis.

In some embodiments, the processor, when executing a computer program, further implements the following steps of: determining if a required library file satisfies a load condition in case the library file required for gene analysis is not in shared gene memory; and loading the required library file into the shared gene memory in case the loading condition is satisfied.

In some embodiments, determining whether the required library file satisfies the load condition in the case where the library file required for gene analysis is not in shared gene memory, and whether to load the required library file into shared gene memory when the load condition is satisfied , contains the step of: obtaining information about the required library file and information about the shared gene memory, where the information about the required library file contains the space requested by the required library file, and the number of archive download requests of the required library file, and information about the shared gene memory contains the remaining space of the shared gene memory; and if the number of archive download requests of the desired library file is greater than the first predetermined number and the space requested by the desired library file is less than the remaining space of the shared gene memory, loading the desired library file into the shared gene memory.

In some embodiments, the requested library file information further comprises a requested library file load request rate; the shared memory information comprises load request rates of all library files in the shared gene memory; determining whether the required library file satisfies the load condition and whether to load the required library file into the shared gene memory, in the case where the load condition is satisfied, further comprises: if the number of download archive requests of the desired library file is greater than the first predetermined number and requested by the required library file is greater than the remaining space of the shared gene memory, rank the required library file and all library files in order of priority according to the download request frequency of the required library file and the download request frequencies of all library files, to obtain the download frequency priority of each library file ; if the load request rate priority of the required library file is higher than the priority of the library file in the shared gene memory, and if the remaining space of the shared gene memory after deletion of the library file with the lower load request frequency priority in the shared gene memory is greater than or equal to the space requested a given library file, deleting a library file with a lower load request frequency priority in the shared gene memory; and if the number of archive download requests of the desired library file is greater than the first predetermined number, and the space requested by the desired library file is less than the remaining space of the shared gene memory, loading the required library file into the shared gene memory.

In some embodiments, the requested library file information further comprises a requested library file download request rate, the shared gene memory information further comprises download request rates of all library files; determining whether the required library file satisfies the load condition and whether to load the required library file into the shared gene memory, in the case where the load condition is satisfied, further comprises: a file greater than the remaining space of the shared gene memory, ranking the required library file and all library files in order of priority according to the download request frequency of the required library file and the download request frequencies of all library files, to obtain the priority of the download request frequency of each library file; if the load request rate priority of the required library file is higher than the priority of the library file in the shared gene memory and if the remaining space of the shared gene memory after deletion of the library file with the lower load request frequency priority in the shared gene memory is greater than or equal to the space requested by the requested the library file, deleting the library file with a lower load request frequency priority in the shared gene memory; and loading the required library file into the shared gene memory.

In some embodiments, the processor, when executing a computer program, further implements the following steps of: setting shared gene memory for library files used in gene analysis, setting size of shared gene memory, number of library files that can be accommodated, name of each library file and size offset of each library file; and loading the library files commonly used in gene analysis into the shared gene memory according to the size of the shared gene memory, the number of library files that can be accommodated, the name of each library file, and the size offset of each library file.

In some embodiments, the gene analysis comprises an alignment analysis, an analysis of variance, and an annotation analysis, and the processor, when executing the computer program, further implements the next step, which performs an alignment analysis, an analysis of variance, and an annotation analysis of the preprocessed sample data in a sequence where, in the case of when the pre-processed sample data contains multiple groups of sample data, the multiple groups of sample data are simultaneously in the same stage or in different stages of gene analysis.

In some embodiments, the gene analysis further comprises sorting analysis and label-duplication analysis, where after performing an alignment analysis, analysis of variation, and annotation analysis of the sample data pre-processed in sequence, the processor, when executing a computer program, further implements the following steps, in which: labeling the sample data after alignment analysis with a positional tag; and performing sorting analysis and marking-duplication analysis on these samples by means of the module.

In some embodiments, the processor, when executing a computer program, further implements the next step, which connects some or all of the gene analysis steps by using memory.

In some embodiments, the pre-processing of the sample data comprises performing a quality control, a filtering operation, and statistical processing of the sample data.

Some embodiments provide a computer-readable storage medium that stores a computer program that, when executed by a processor, performs the steps of: reading sample data and pre-processing the sample data; performing gene analysis of the pre-processed sample data, and determining whether a library file required for gene analysis is in the shared gene memory; if yes, then obtain the desired library file from the shared gene memory, transform the desired library file in the process of gene analysis of the pre-processed sample data, and complete the gene analysis.

In some embodiments, the processor, when executing a computer program, further implements the following steps of: determining if a required library file satisfies a load condition in the case where the library file required for gene analysis is not in shared gene memory; and loading the required library file into the shared gene memory in case the load condition is satisfied.

In some embodiments, determining whether the required library file satisfies the load condition in the case where the library file required for gene analysis is not in shared gene memory, and whether to load the required library file into shared gene memory in the case where the load condition is satisfied, contains: obtaining information about the required library file and information about the shared gene memory, where the information about the required library file contains the space requested by the specified library file and the number of archive download requests of the desired library file, and the information about the shared gene memory contains the remaining space shared used gene memory; and if the number of archive download requests of the desired library file is greater than the first predetermined number and the space requested by the predetermined library file is less than the remaining space of the shared gene memory, loading the desired library file into the shared gene memory.

In some embodiments, the required library file information further comprises a requested library file download request rate, the shared gene memory information further comprises download request rates of all library files in the shared gene memory; determining whether the required library file satisfies the load condition and whether to load the required library file into the shared gene memory, in the case where the load condition is satisfied, further comprises: if the number of archive download requests of the desired library file is greater than the first specified number and the space requested by the specified file the libraries greater than the remaining shared gene memory space rank the required library file and all library files in order of priority according to the download request frequency of the required library file and the download request frequencies of all library files to obtain the priority of the download request frequency of each library file; if the download request rate priority of the requested library file is greater than the priority of the library file in the shared gene memory, and if the remaining shared gene storage space after deleting the library file with the lower download request frequency priority in the shared gene memory is greater than or equal to the space requested by the requested library file delete a library file with a lower load request frequency priority in the shared gene memory; and if the number of archive download requests of the desired library file is greater than the first predetermined number and the space requested by the desired library file is less than the remaining space of the shared gene memory, loading the required library file into the shared gene memory.

In some embodiments, the required library file information further comprises a requested library file download request rate, the shared gene memory information further comprises download request rates of all library files in the shared gene memory; determining whether the required library file satisfies the load condition and whether to load the required library file into shared gene memory, in the case where the load condition is met, further comprises: a file greater than the remaining space of the shared gene memory, ranking the required library file and all library files in order of priority according to the download request frequency of the required library file and the download request frequencies of all library files, to obtain the priority of the download request frequency of each library file; if the load request rate priority of the required library file is higher than the priority of the library file in the shared gene memory, and if the remaining space of the shared gene memory after deletion of the library file with the lower load request frequency priority in the shared gene memory is greater than or equal to the space requested a desired given library file, deleting a library file with a lower load request frequency priority in the shared gene memory; and loading the required library file into the shared gene memory.

In some embodiments, the computer program, when executed by the processor, further implements the steps of: setting shared gene memory for library files used in gene analysis, setting size of shared gene memory, number of library files that can be accommodated, name of each library file and size offset of each library file; and loading the library files commonly used in gene analysis into the shared gene memory according to the size of the shared gene memory, the number of library files that can be accommodated, the name of each library file, and the size offset of each library file.

In some embodiments, the gene analysis comprises an alignment analysis, an analysis of variance, and an annotation analysis, and the computer program, when executed by the processor, further implements the following step of: performing an alignment analysis, an analysis of variance, and an annotation analysis of the sample data pre-processed in sequence, where in in the case where the pre-processed sample data contains multiple groups of sample data, the multiple groups of sample data are simultaneously in the same stage or different stages of gene analysis.

In some embodiments, the gene analysis further comprises sorting analysis and label-duplication analysis, where after performing an alignment analysis, analysis of variation, and annotation analysis of the sample data pre-processed in sequence, the computer program, when executed by a processor, further implements the following steps, wherein: labeling the sample data after alignment analysis with a positional tag; and performing, by means of the module, a sorting analysis and a label-duplication analysis on the labeled sample data.

In some embodiments, the computer program, when executed by the processor, further implements the next step in which some or all of the gene analysis steps are connected using memory.

In some embodiments, the pre-processing of the sample data comprises performing a quality control, a filtering operation, and statistical processing of the sample data.

As will be appreciated by those skilled in the art, all or part of the method steps in the above embodiments may be executed by hardware or by a program instructing the hardware, wherein the program may be stored on a computer-readable, non-volatile storage medium; a program that, when executed, can perform the steps of the embodiments of the above methods. Any reference to memory, storage device, database or other media used in the embodiments provided in this application may contain non-volatile and/or volatile memory. The non-volatile memory may comprise read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. The volatile memory may comprise random access memory (RAM) or external cache memory. By way of illustration, and not limitation, RAM is available in various forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous linked DRAM (SLDRAM), direct Rambus RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM) and dynamic Rambus RAM (RDRAM), etc.

The technical features of the above embodiments may be combined arbitrarily. To make the description concise, all possible combinations of various technical features are not described in the embodiments, but should be considered to be present within the protection scope of the present description, as long as there is no conflict in these combinations of technical features.

The above embodiments merely represent a few embodiments of the present application. However, their relatively specific and detailed descriptions cannot therefore be construed as limiting the scope of protection of the present application. It should be pointed out that a person skilled in the art is capable of making various modifications and improvements without departing from the concept of the present application. Such modifications and improvements are to be considered as falling within the protection scope of the present application. Therefore, the scope of protection of the present application should be determined by the terms of the claims.

Claims (31)

1. A method for gene analysis based on shared memory, performed by a computer and comprising the steps of: reading the sample data and pre-processing the sample data, wherein the sample data is data generated or generated after gene sequencing of the samples; performing gene analysis of the pre-processed sample data and determining whether a library file required for gene analysis is in the shared gene memory; if found, obtain the desired library file from the shared gene memory, convert the desired library file into a gene analysis process of pre-processed sample data, and perform gene analysis, wherein the sample data contains a plurality of data groups, each data group having a corresponding sample processing process, and each sample processing process enters the shared gene memory area to obtain the required library file. 2. The shared memory gene analysis method of claim 1, further comprising: determining whether the required library file satisfies the loading condition in the case where the required library file in the gene analysis is not in the shared gene memory; And downloading the required library file into the shared gene memory when the download condition is satisfied. 3. The shared memory gene analysis method of claim 2, wherein, in the steps of determining whether the required library file satisfies a load condition, in the case where the gene analysis required library file is not in the shared gene memory, and load the required library file into the shared gene memory when the load condition is satisfied: obtaining information about the required library file and information about the shared gene memory, and information about the required library file contains the amount of memory required by the required library file, and the number of archive download requests of the required library file, and the information about the shared gene memory contains the remaining amount of memory in shared gene memory; And if the number of archive download requests is greater than the first predetermined number and the amount of memory required by the required library file is less than the remaining amount of memory in the shared gene memory, loading the required library file into the shared gene memory. 4. The shared memory gene analysis method of claim 4, wherein the requested library file information further comprises a download request rate of the required library file, the shared gene memory information comprises download request rates of all library files; wherein in the steps of determining whether the required library file satisfies the load condition, and loading the required library file into the shared gene memory in the case where the load condition is satisfied, further: if the number of archive download requests is greater than the first predetermined number and the amount of memory required by the required library file is greater than the remaining memory size of the shared gene memory, ranking the required library file and all library files in order of priority according to the frequency of the requested library file's download request, and download request rates of all library files to prioritize the download request rate of each library file; if the download request rate priority of the desired library file is higher than the priority of the library file in the shared gene memory, and if the remaining memory in the shared gene memory after deleting the library file with the lower download request frequency priority in the shared gene memory is greater than or equal to of the memory required by the required library file, removing the library file with a lower load request frequency priority from the shared gene memory; And loading the required library file into the shared gene memory. 5. The method of gene analysis based on shared gene memory, according to any one of paragraphs. 1-4, further comprising the steps of: setting a shared gene memory for the library files used in gene analysis, setting the size of the shared gene memory, the number of library files that can be allocated, the name of each library file, and the size offset of each library file; And loading library files commonly used in gene analysis into the shared gene memory according to the size of the shared gene memory, the number of library files that can be accommodated, the name of each library file, and the size offset of each library file. 6. The shared memory gene analysis method of claim 1, wherein the gene analysis comprises alignment analysis, variation analysis, and annotation analysis, the method further comprising: perform alignment analysis, variational analysis and annotation analysis of sample data pre-processed in sequence, wherein in the case where the pre-processed sample data contains a plurality of sample data groups, said plurality of sample data groups are simultaneously at the same stage or at different stages gene analysis. 7. The shared memory gene analysis method of claim 6, wherein the gene analysis further comprises a sorting analysis and a marking-duplication analysis, wherein after performing an alignment analysis, a variation analysis, and an annotation analysis of the sample data pre-processed in sequence , the method further comprises the steps of: labeling the sample data after alignment analysis with a positional tag; and performing sorting analysis and labeling-duplication analysis of the labeled sample data. 8. The shared memory gene analysis method of claim 7, further comprising: connect some or all of the steps of gene analysis using memory. 9. The method of gene analysis based on shared memory, according to any one of paragraphs. 6-8, in which at the stage of preliminary preparation of these samples: perform quality control, filtering operation and statistical processing of sample data. 10. Device for gene analysis based on shared memory, containing: a data reading module configured to read the sample data, the sample data being data generated or formed after gene sequencing of the samples; a data pre-processing module configured to pre-process the sample data; And a gene analysis module, configured to genetically analyze the pre-processed sample data and determine whether a library file required for gene analysis is in a shared gene memory; if found, obtaining the desired library file from the shared gene memory, converting the desired library file into a gene analysis process of the pre-processed sample data, and performing gene analysis, the sample data comprising a plurality of data groups, each data group having a corresponding sample processing process, wherein each sample processing process enters the shared gene memory area to obtain the required library file. 11. A computer device comprising: a memory, a processor and a computer program stored in the memory and executed on the processor, wherein the processor, when executing the computer program, implements the steps of the method according to any one of paragraphs. 1-9. 12. A computer-readable medium on which a computer program is stored, wherein the computer program, when executed by the processor, implements the steps of the method according to any one of claims. 1-9.

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