CN107480466A - Genomic data storage method and electronic equipment - Google Patents

Abstract

The invention discloses a genome data storage method, comprising: obtaining gene sequence comparison information during the genome comparison process, and creating gene sequence statistical information; storing the gene sequence comparison information in a disk, and Store the corresponding index in memory at the comparison position of the comparison information in the genome; the index is the storage position of the gene sequence comparison information in the disk; classify the genome statistical information to obtain the first statistical information and the second statistical information; the first statistical information is stored in the memory, and the first statistical information is the statistical information whose access frequency is higher than the preset frequency in the variation detection process; the second statistical information is stored in the disk, and the second statistical information is The statistical information is statistical information that cannot be stored in memory and/or statistical information whose access frequency is lower than a preset frequency during the mutation detection process. The invention also discloses an electronic device adopting the genome data storage method.

Description

Genome data storage method and electronic device

technical field

The invention relates to the technical field of data processing, in particular to a genomic data storage method and electronic equipment.

Background technique

The calculation process of genomic variation detection can generally be divided into steps such as comparison, sorting, deduplication, re-alignment, variation detection, and filtering. Among them, the main steps need to use the BAM file (the full name of SAM is sequence alignment map, sequence alignment map. And the BAM file is the file in the binary format of the SAM file (B is taken from binary)) as the output file to write to the hard disk, in the next The step is to read it from the hard disk to the memory, and then proceed to the next step.

In the process of realizing the present invention, the inventor finds that the prior art has the following problems:

In the analysis of human whole genome data, the original data is generally about 100GB, and the main analysis steps in the middle need to read and write files of hundreds of GB. The entire calculation process consumes a lot of I/O resources and the program efficiency is low.

The inventors found that the main causes of this problem are:

1. The intermediate file is too large to be directly put into memory.

64GB memory is a typical machine configuration for common bioinformatics analysis. For human whole genome analysis data, the intermediate results are generally around 100GB, which cannot be directly stored in memory, and the mutation detection process itself needs to load reference sequences and index files into memory, resulting in further reduction in the space for intermediate results.

2. The format of the intermediate file cannot be directly used for calculation.

The general intermediate file format is SAM/BAM format, which is a row record format, that is, each row stores a record, and it cannot be directly used for calculation even if it is directly put into memory. The data required for mutation detection is mainly statistical information on the alignment of each site, including the distribution of the number of various bases at each site, the sequence and frequency of insertion-deletion (InDel), and the softness in the alignment. Cut (soft clipping) sequence and other information.

Contents of the invention

In view of this, the purpose of the present invention is to provide a genome data storage method and electronic equipment, which can solve the problem of low efficiency caused by frequent input and output of a large number of binary files in the genome variation detection process.

Based on the above purpose, the genome data storage method provided by the present invention includes:

During the comparison process, obtain gene sequence comparison information and create gene sequence statistical information;

storing the gene sequence comparison information in the disk, and storing the corresponding index in the memory according to the comparison position of the gene sequence comparison information in the genome; the index is the storage of the gene sequence comparison information in the disk Location;

classifying the genome statistical information to obtain first statistical information and second statistical information;

Storing the first statistical information in the memory, the first statistical information is the statistical information whose access frequency is higher than the preset frequency during the mutation detection process;

The second statistical information is stored in the disk, and the second statistical information is statistical information that cannot be stored in memory and/or statistical information whose access frequency is lower than a preset frequency during the mutation detection process.

Optionally, the first statistical information includes base weighted quality value statistical information, positive and negative strand statistical information, indel statistical information and soft clipping statistical information.

Optionally, for a site where no indel or soft clipping occurs and at most 2 base types appear, the first statistical information of the site is stored in the first data structure;

The first data structure includes:

The first head used to indicate the base type;

A first quality value storage unit for representing base-weighted quality values;

A first positive chain number storage unit for representing the number of positive chains;

A first negative chain number storage unit for indicating the number of negative chains.

Optionally, for a site with indels and 3-4 base types, the first statistical information of the site is stored in the first data structure and the second data structure;

The second data structure includes:

Base-weighted quality value statistics and positive and negative strand statistics for each of the four base types; the storage structure of base-weighted quality value statistics and positive and negative strand statistics for each base type specifically includes: a second quality value storage unit for base weighted quality values, a second positive chain number storage unit for representing the number of positive chains, and a second negative chain number storage unit for representing the number of negative chains;

The first insertion statistical information specifically includes: a first insertion sequence storage unit used to represent the insertion sequence, and a first low-quality insertion number storage unit used to represent the number of low-quality insertions;

The first deletion statistical information specifically includes: a first deletion length storage unit used to indicate the deletion length, a first high-quality deletion number storage unit used to indicate the number of high-quality deletions, and a first lowest deletion number storage unit used to indicate the number of low-quality deletions. Mass missing number storage unit;

The first data structure includes:

the second header filled with 11;

The first insertion information storage unit used to indicate whether there is an insertion, specifically includes: a first insertion information sub-storage unit used to indicate whether there is an insertion, an insertion length sub-storage unit used to indicate the insertion length, and a sub-storage unit used to indicate low-quality insertion Quantity of low-quality insertion into digital sub-storage;

The first missing information storage unit used to indicate whether there is a missing, specifically includes: a first missing information sub-storage unit used to indicate whether there is a missing;

A pointer to the corresponding second data structure storage location.

Optionally, for a site with more than one indel and an insertion length greater than 12 bases, the first statistical information of the site is stored in the first data structure and the third data structure, and for such a site Create a memory pool in the memory for storage of the first statistical information;

The third data structure includes:

Base-weighted quality value statistics and positive and negative strand statistics for each of the four base types; the storage structure of base-weighted quality value statistics and positive and negative strand statistics for each base type specifically includes: a third quality value storage unit for base weighted quality values, a third positive chain number storage unit for representing the number of positive chains, and a third negative chain number storage unit for representing the number of negative chains;

The second insertion statistical information specifically includes: an insertion length storage unit used to indicate the insertion length, a second insertion sequence storage unit used to indicate the insertion sequence, a second low-quality insertion number storage unit used to indicate the number of low-quality insertions, and, a high-quality insertion number storage unit for representing the number of high-quality insertions;

The second deletion statistical information specifically includes: a second deletion length storage unit used to indicate the deletion length, a second high-quality deletion number storage unit used to indicate the number of high-quality deletions, and a second-lowest deletion number storage unit used to indicate the number of low-quality deletions Mass missing number storage unit;

The first data structure includes:

a third header filled with 11;

The second insertion information storage unit for indicating whether there is an insertion, specifically includes: a second insertion information sub-storage unit for indicating whether there is an insertion, a first memory pool information sub-storage unit for indicating whether a memory pool is used, a first occupancy length sub-storage for representing an occupancy length in the memory pool;

The second missing information storage unit for indicating whether there is a missing, specifically includes: a second missing information sub-storage for indicating whether there is a missing, a second memory pool information sub-storage for indicating whether a memory pool is used, A second occupancy length sub-storage for representing the occupancy length in the memory pool.

Optionally, for the soft clipping statistical information, a dynamic array is used to record, and each record includes:

a soft-splice location store for representing where the soft-splice is located on the genome;

a soft clipping left number store for representing the number of times soft clipping occurs to the left of the corresponding site;

Soft clipping right number storage for indicating the number of times soft clipping occurs to the right of the corresponding site.

Optionally, the index includes a paired-end comparison information index and a single-end comparison information index;

For the double-end comparison information index, the double-end comparison array structure is used for storage, and the double-end comparison array structure includes:

a first ID storage unit for representing the ID of the gene sequence;

A first alignment position storage unit used to indicate the position of the gene sequence aligned to the genome;

an insert length storage unit representing an insert length of a gene sequence;

A first alignment quality value storage unit for representing the alignment quality value of the gene sequence;

A first average quality value storage unit for representing the average quality value of the gene sequence;

For the single-end comparison information index, the single-end comparison array structure is used for storage, and the single-end comparison array structure includes:

a second ID storage unit for the ID representing the gene sequence;

A second comparison position storage unit used to indicate the position of the gene sequence compared to the genome;

A second alignment quality value storage unit for representing the alignment quality value of the gene sequence;

A second average quality value storage unit for representing the average quality value of the gene sequence;

Wherein, for each gene sequence used for comparison, its corresponding index is arranged in order according to the comparison position of the gene sequence on the genome.

Optionally, the gene sequence comparison information is stored in a disk, specifically including:

Therefore, the gene sequence comparison information is divided into 512 files and stored on the disk. Each file stores the gene sequence comparison information of a certain genome interval. The storage data structure of each gene sequence comparison information includes:

a sequence length storage unit for representing the sequence length of the gene sequence;

A sequence store for representing the gene sequence itself;

a quality value storage unit for representing the quality value of the gene sequence;

A start position storage unit used to represent the start position of the alignment algorithm when the gene sequence is compared;

The positive and negative strand storage part used to represent the positive and negative strand information of the gene sequence during alignment;

A region length storage part used to indicate the length of the genome region selected during gene sequence alignment;

The left position storage part used to represent the left riveting position of the gene sequence during alignment;

A right position storage unit used to indicate the position of the right riveted position of the gene sequence during alignment.

Optionally, the method also includes:

During the deduplication process, subtracting the interference caused by repetitive sequences in the genome statistical information;

and / or,

During the re-alignment process, the gene sequence of the re-alignment region of the genome is extracted, and after the gene sequence of the re-alignment region is re-aligned, the genome statistical information of the gene sequence of the re-alignment region is adjusted.

As can be seen from the above, the genome data storage method and electronic equipment provided by the present invention have designed an exquisite data storage structure for the characteristics of the intermediate files in the whole process of mutation detection, and keep some of the main intermediate data in the memory. Here, these data can be directly called from the memory, so that each step of the whole process of mutation detection does not need a large number of disk I/O reads and writes, which significantly improves the efficiency of the entire mutation detection and analysis process.

Description of drawings

Fig. 1 is a schematic flow chart of an embodiment of the genomic data storage method provided by the present invention;

Figure 1a is a schematic diagram of the first data structure when there are no indels and soft cuts, and at most two base types appear;

Fig. 1b is a schematic diagram of the second data structure when an insertion-deletion (InDel) occurs and there are 3-4 base types;

Fig. 1c is a schematic diagram of the first data structure when an insertion-deletion (InDel) occurs and there are 3-4 base types;

Figure 1d is a schematic diagram of the third data structure when there is more than one indel, and the insertion length is greater than 12 bases;

Figure 1e is a schematic diagram of the first data structure when there is more than one indel, and the insertion length is greater than 12 bases;

Figure 1f is a schematic diagram of the dynamic array when a dynamic array is used to record the soft clipping statistics;

Figure 1g is a schematic diagram of the index;

Figure 1h is a schematic diagram of the storage data structure of the alignment information of each gene sequence;

Figure 2 is a schematic flow diagram of an embodiment of the genome sequence comparison method provided by the present invention;

Fig. 3 is a structural schematic diagram of an embodiment of the genome data storage device provided by the present invention;

FIG. 4 is a schematic structural diagram of an embodiment of an electronic device provided by the present invention.

detailed description

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

It should be noted that all the expressions using "first" and "second" in the embodiments of the present invention are to distinguish two entities with the same name but different parameters or parameters that are not the same. It can be seen that "first" and "second " is only for the convenience of expression, and should not be understood as a limitation to the embodiments of the present invention, and will not be described one by one in the subsequent embodiments.

Based on the above purpose, the first aspect of the embodiments of the present invention proposes an embodiment of a genomic data storage method, which can solve the problem of low efficiency caused by frequent input and output of a large number of binary files in the process of genomic variation detection. As shown in FIG. 1 , it is a schematic flowchart of an embodiment of the genome data storage method provided by the present invention.

The genome data storage method includes:

Step 101: During the comparison process, obtain gene sequence comparison information, and create gene sequence statistical information; the gene sequence comparison information is the gene sequence comparison result information generated during the genome comparison process, according to the gene sequence comparison For the result information, the statistical information of the gene sequence can be extracted from it;

Step 102: storing the gene sequence comparison information in the disk, and storing the corresponding index in the memory according to the comparison position of the gene sequence comparison information in the genome; the index is the gene sequence comparison information in the disk storage location in

Step 103: classifying the gene sequence statistical information to obtain first statistical information and second statistical information;

Step 104: Store the first statistical information in the memory, the first statistical information is the statistical information whose access frequency is higher than the preset frequency during the variation detection process;

Step 105: Store the second statistical information in a disk, where the second statistical information is statistical information that cannot be stored in memory and/or statistical information whose access frequency is lower than a preset frequency during mutation detection.

It can be seen from the above embodiments that the genome data storage method provided by the embodiment of the present invention is aimed at storing intermediate files in the whole process of mutation detection (including steps such as comparison, sorting, deduplication, re-comparison, mutation detection, and filtering). Features: Design an exquisite data storage structure, keep some of the main intermediate data in the memory, and these data can be directly called from the memory, so that each step of the whole process of mutation detection does not need a lot of disk I/O reading Write, significantly improving the efficiency of the entire variant detection analysis process.

In some optional implementation manners, the first statistical information includes base-weighted quality value statistical information, positive and negative strand statistical information, indel statistical information, and soft-cut statistical information; specifically includes:

The base-weighted quality value statistical information (Weighted Count):

Since each base aligned to the reference gene sequence has a quality value between 0-40, the weight assigned is shown in the following table:

Base Quality Scores Parameter* Weight 0–10 [0–Weight0] 0 11–13 (Weight0–Weight1) 1 14–17 (Weight1–Weight2) 2 18–20 (Weight2–Weight3) 3 21–40 (Weight3–40) 4

Add up the weights of all the same bases aligned to the same position to obtain the weight sum of the quality value of this base type;

The positive and negative strand statistical information (Strand Count): statistics of the number of gene sequences aligned to the same position in forward and reverse directions;

The insertion-deletion statistical information and insertion sequence information (InDel Count): the number of insertion-deletion sequences at a certain position in the genome and the cumulative number of occurrences in the comparison gene sequence;

The soft clip statistics (Soft Clip Count): the number of occurrences of soft clips at a certain position in the genome in the aligned gene sequence.

In some optional implementations, considering the simplest case, for a site where there are no indels and soft cuts, and there are at most 2 types of base types, the first statistical information of the site adopts the first data structure Storage; Optionally, the first data structure is a data structure Counter (container) of 8 bytes, and an 8 bytes data structure Counter is used to store the information of a site, and the entire human genome includes approximately 3G sites, so the memory needs about 24GB;

The first data structure, as shown in Figure 1a, the statistical information (base1information and base2information) of two bases is stored in the same 4bytes data structure, including:

The first header used to indicate the base type; optionally, the first header (base) uses 2 bits to indicate the base type, and bases A, C, G, and T use 00, 01, 10, and 11 respectively To represent;

A first quality value storage unit used to represent base-weighted quality values; optionally, the first quality value storage unit (weighted count) uses 14 bits to represent the sum of weighted quality values, with a maximum value of 16383;

The first positive chain number storage unit used to represent the number of positive chains; optionally, the first positive chain number storage unit (+vestrand count) uses 1 byte (8 bits) to represent the number of positive chains, and the maximum value is 255;

The first negative chain number storage unit used to represent the number of negative chains; optionally, the first negative chain number storage unit (-vestrand count) uses 1 byte (8 bits) to represent the number of negative chains, and the maximum value is 255.

In some optional embodiments, for sites where indels (InDel) occur and 3-4 base types have occurred, the first statistical information of the site is stored using the first data structure and the second data structure ; Optionally, a 32bytes data structure OverflowCounter (overflow container) is used to store the information of a site, and the statistical information of the base ACGT (base AZinformation, base C information, base G information and base Tinformation) is represented by 6bytes respectively , the insertion information (Insertion Info.) and the deletion information (DeletionInfo.) are represented by 4 bytes each; according to experience, there are about 200M such sites in the 30X whole genome data;

The second data structure, as shown in Figure 1b, includes:

Base-weighted quality value statistics and positive and negative strand statistics for each of the four base types; the storage structure of base-weighted quality value statistics and positive and negative strand statistics for each base type specifically includes: The second quality value storage part of the base weighted quality value (weighted count, optional, use 2bytes to represent the weighted quality value sum, the maximum value is 65535), used to represent the second positive chain number storage part of the positive chain number (+ve strand count, optional, use 2bytes to indicate the number of positive strands, the maximum value is 65535), and the second negative strand number storage unit used to indicate the number of negative strands (-ve strand count, optional, use 2bytes to indicate negative number of chains, the maximum value is 65535);

The first insertion statistical information specifically includes: the first insertion sequence storage part (Insertion Pattern, optional, expressed in 3 bytes, where the longest can represent 12 bases) used to represent the inserted sequence, used to represent low-quality insertions The number of the first low-quality insertion number storage unit (LQ count, optional, expressed in 1 byte, the maximum value is 255);

The first deletion statistical information specifically includes: the first deletion length storage part (Del.Len, optional, expressed in 1 byte, maximum value 255) used to indicate the length of the deletion, used to indicate the first highest number of high-quality deletions Quality deletion number storage unit (HQ count, optional, expressed in 1 byte, maximum value 255), used to represent the first low-quality deletion number storage unit of the number of low-quality deletions (LQ count, optional, expressed in 1 byte, The maximum value is 255); optional, including 1byte unused space;

When using OverflowCounter, the storage content of the corresponding first data structure will change, and the first data structure, as shown in Figure 1c, includes:

The second header filled with 11; originally used to store base1information and base2information base type data, will be filled with "11" to indicate that OverflowCounter is used;

A first insertion information storage unit (Insertion Information) used to indicate whether there is an insertion. Optionally, 14 bits are used to store the insertion information, specifically including: a first insertion information sub-storage unit (1 bit) used to indicate whether there is an insertion, The insertion length sub-storage section used to indicate the insertion length (Ins.Len. is represented by 4 bits), the low-quality insertion number sub-storage section (LQ count, represented by 8 bits) used to represent the low-quality insertion quantity; optional, 1 bit setting is 0;

The first deletion information storage unit (Deletion Information) used to indicate whether there is a deletion. Optionally, 14 bits are used to store the deletion information, and 1 bit is used to indicate whether there is a deletion (the first deletion information sub-storage unit), and 1 bit is set to 0, 12bits are not used (Unused);

A pointer (array index pointing today dynamic array of overflow counter) used to point to the storage location of the corresponding second data structure. Optionally, 4 bytes are used to store a pointer to the location of the OverflowCounter data.

In some optional embodiments, for a site with more than one indel and an insertion length greater than 12 bases, the first statistical information of the site is stored in the first data structure and the third data structure, and for The first statistical information of such a site is to create a memory pool (Memory Pool, which specially opens up a piece of memory) in the memory for storage, and the statistical information of the base ACGT (base A information, base C information, base G information and base T information) information) are represented by 6 bytes respectively, and the pointers for inserting and missing information are recorded in OverflowCounter, as shown in Figure 1d;

The third data structure, as shown in Figure 1d, includes:

Base-weighted quality value statistics and positive and negative strand statistics for each of the four base types; the storage structure of base-weighted quality value statistics and positive and negative strand statistics for each base type specifically includes: The third quality value storage part of the base weighted quality value (weighted count, optional, use 2bytes to represent the weighted quality value sum, the maximum value is 65535), and the third positive chain number storage part (+ve strand count, optional, use 2bytes to indicate the number of positive strands, the maximum value is 65535), and the third negative strand number storage unit used to indicate the number of negative strands (-ve strand count, optional, use 2bytes to indicate negative number of chains, the maximum value is 65535);

The second insertion statistical information (Insertion Ptr), optional, expressed in 4bytes, specifically includes: an insertion length storage unit used to indicate the insertion length (Insertion length, optional, using 1byte to indicate the insertion length), used to indicate The second insertion sequence storage part of the insertion sequence (Insertion pattern, the length is variable, and each 2bits represents a base), which is used to represent the second low-quality insertion number storage part of the low-quality insertion quantity (LQ count, optional, using 1byte Indicates the number of low-quality inserts), and the high-quality insert number storage unit used to indicate the number of high-quality inserts (HQcount, optional, use 1byte to indicate the number of high-quality inserts);

The second deletion statistical information (Deletion Ptr), optional, expressed in 4 bytes, specifically includes: a second deletion length storage unit (Deletion length, optional, using 1 byte to indicate the deletion length) for indicating the length of the deletion, expressed in For the second high-quality deletion number storage unit (HQ count, optional, use 1 byte to indicate the number of high-quality deletions) representing the number of high-quality deletions, and for the second low-quality deletion number storage unit (LQ count) for representing the number of low-quality deletions count, optional, use 1byte to represent the number of low quality missing);

At the same time, the information record changes in Counter are shown in Figure 1e, the first data structure includes:

The third header filled with 11; originally used to store base1information and base2information base type data, will be filled with "11" to indicate the use of OverflowCounter;

The second insertion information storage unit (Insertion Information) used to indicate whether there is an insertion, optionally, expressed in 14 bits, specifically includes: a second insertion information sub-storage unit (1 bit) used to indicate whether there is an insertion, used to indicate Whether the first memory pool information sub-storage part (1bit) of the memory pool is used, and the first occupied length sub-storage part (12bits) for indicating the occupied length in the memory pool;

The second deletion information storage unit (Deletion Information) used to indicate whether there is a deletion, optionally, expressed in 14 bits, specifically includes: a second deletion information sub-storage unit (1 bit) used to indicate whether there is a deletion, used to indicate The second memory pool information sub-storage part (1 bit) of whether the memory pool is used, and the second occupied length sub-storage part (12 bits) used to indicate the occupied length in the memory pool.

According to experience, soft clipping (soft clipping) will only occur at few genomic positions, so there is no need to allocate a separate storage space for each position. Therefore, in some optional implementation manners, a dynamic array is used to record the soft clipping statistical information, as shown in Figure 1f, the format of each record is {position, left counts, right counts}, occupying 12 bytes , including:

The soft shear position storage unit (position) used to indicate the position of the soft shear on the genome occupies 4 bytes;

The soft shearing left count storage unit (leftcounts), which is used to indicate the number of times that soft shearing occurs on the left side of the corresponding site, occupies 4 bytes;

The soft clipping right count storage unit (rightcounts), which is used to indicate the number of times that the soft clipping occurs on the right side of the corresponding site, occupies 4 bytes.

In some optional implementations, as shown in Figure 1g, the index includes a double-end comparison (Pair End) information index and a single-end comparison (Single End) information index;

For the paired-end alignment information index, a pair-end alignment array structure is used for storage, and the pair-end alignment array structure (PairEndAlignmentInfo, occupying 12 bytes) includes:

The first ID storage unit (ReadID) used to represent the ID of the gene sequence occupies 4 bytes;

The first alignment position storage unit (AlignedPosition) used to represent the position of the gene sequence alignment on the genome, occupying 4 bytes;

The insert length storage unit (Insert Size) used to indicate the insert length of the gene sequence occupies 2 bytes;

The first alignment quality value storage part (MAPQ) used to represent the alignment quality value of the gene sequence occupies 1 byte;

The first average quality value storage unit (Average BaseQuality) used to represent the average quality value of the gene sequence occupies 1 byte;

For the single-end alignment information index, the single-end alignment array structure is used for storage, and the single-end alignment array structure (SingleEndAlignmentInfo, occupying 10 bytes) includes:

The second ID storage unit (ReadID) used to represent the ID of the gene sequence occupies 4 bytes;

The second alignment position storage unit (AlignedPosition) used to represent the position of the gene sequence alignment on the genome, occupying 4 bytes;

The second alignment quality value storage part (MAPQ) used to represent the alignment quality value of the gene sequence occupies 1 byte;

The second average quality value storage unit (Average BaseQuality) used to represent the average quality value of the gene sequence occupies 1 byte;

Wherein, for each gene sequence used for comparison, its corresponding index is arranged in order according to the comparison position of the gene sequence on the genome.

Because the read sequence in the variation detection process is very random, in some optional implementations, the gene sequence comparison information is stored on disk, specifically including:

Therefore, the gene sequence comparison information is divided into 512 files (buckets) and stored on the disk, and each file stores the gene sequence comparison information of a certain genome interval, as shown in Figure 1h, the storage data structure of each gene sequence comparison information include:

The sequence length storage unit (Read Length) used to represent the sequence length of the gene sequence occupies 2 bytes;

The sequence storage part (Packed Read) used to represent the gene sequence itself, the length is variable, using 2bits to represent a base;

The quality value storage part (Base Qualities) used to represent the quality value of the gene sequence, the length is variable;

The start position storage unit (DP StartPos.), which is used to indicate the start position of the comparison algorithm when the gene sequence is compared, occupies 4 bytes;

The positive and negative strand storage unit (Strand) used to represent the positive and negative strand information of the gene sequence during comparison, occupying 1 bit;

The region length storage part (DPref.length) used to indicate the length of the genomic region selected during the comparison of gene sequences occupies 15 bits;

The left position storage part (Left Anchor), which is used to indicate the left fixed position of the gene sequence during comparison, occupies 4 bytes;

The right anchor storage unit (Right anchor), which is used to indicate the position of the right riveted position of the gene sequence during alignment, occupies 4 bytes.

In addition to the steps of creating statistical data and indexes during the comparison process in the foregoing embodiments, in some optional implementation manners, the method further includes:

In the de-duplication process, subtract the interference caused by the repetitive sequence in the genome statistical information;

and / or,

In the realignment process, extracting the gene sequence of the realignment region of the genome, and after re-comparing the gene sequence of the realignment region, adjusting the genome statistical information of the gene sequence of the realignment region;

These statistics are used directly during variant detection to calculate probabilities for various genotypes.

Through the genome data storage method provided by the embodiment of the present invention, the entire analysis process does not need to repeatedly output a large number of binary files. After the overall algorithm optimization, the analysis of a whole genome data can be completed within 4 hours, while the general analysis process requires dozens of It takes hours to complete; it greatly reduces the I/O process in the process of mutation detection and analysis, and greatly improves the analysis efficiency of the program.

In order to facilitate the understanding of the aforementioned technical solutions, an example of a genome sequence alignment method is briefly introduced here to explain the genome alignment process in step 101 in the aforementioned examples. As shown in FIG. 2 , it is a schematic flowchart of an embodiment of the genome sequence comparison method provided by the present invention.

The genome sequence comparison method comprises the following steps:

Step 201: Obtain a reference genome sequence and a genome sequence file to be compared. The file acquisition method here can be the conventional acquisition method. Wherein, the format of the genome sequence file to be compared may be a FASTQ file.

The genome sequence comparison method divides the sequence comparison into 3 levels; each time a part of the sequence is read from the input genome sequence file to be compared, and then the 1st level, 2nd level, and 3rd level are sequentially performed. Alignment algorithm, the sequences that have not been compared in the previous level enter the comparison algorithm of the next level to continue the comparison; specifically, the following steps are included.

Step 202: Read the partial genome sequence from the genome sequence file to be compared.

Step 203: According to the bidirectional BWT comparison algorithm (level 1: bidirectional BWT comparison algorithm, bidirectional BWT: Bi-directional Burrows–Wheeler Transform, bidirectional Burrows–Wheeler Transform), compare the partial genome sequence with the reference genome sequence Compare. Wherein, the two-way BWT alignment algorithm handles the alignment of reads that allows up to 4 base errors. Reads, read length, is the sequencing sequence obtained in high-throughput sequencing, and each read is a base sequence. In the process of bioinformatics analysis, by comparing each read to the reference genome, the difference between the sequenced sequence and the reference genome can be obtained, so as to discover the variation.

Optionally, the method of comparing genome sequences according to the two-way BWT comparison algorithm may specifically include the following steps:

Segment the reads using the dovecote principle, allowing 0-2 base errors for each segment;

Then use the two-way BWT comparison algorithm to search and compare, including:

Establishing the BWT of the reference genome sequence, the suffix array and the BWT of the reverse order of the reference genome sequence;

Use backward search (backward) and forward search (forward) to search reads or each fragment of reads from right to left and from left to right for its position on the reference genome sequence.

The efficiency of the two-way BWT alignment is relatively low when dealing with multiple base mismatches. In the case of allowing a maximum of 4 base mismatches, the reads are segmented according to the pigeonhole principle, and each segment allows 0-2 base mismatches, so that bidirectional BWT is used to handle up to 2 base mismatches. , the efficiency is greatly increased.

The common comparison software BWA uses backward search after establishing the BWT of the reference sequence and the corresponding index and SA (suffix array), that is, searches the position of the reads or each fragment of the reads from right to left on the genome. In addition to establishing the traditional BWT index (denoted as B), the bidirectional BWT used in this patent also establishes a BWT index (denoted as B') for the reverse sequence of the reference sequence. Using B, B', SA, searching the position of reads or seeds on the genome in two directions backward and forward, the efficiency of sequence alignment is significantly improved.

Step 204: Whether there is at least one pair of reads in the partial genome sequence and only one read is aligned (that is, in the partial genome sequence, at least one pair of reads is only one read is aligned); if , go to step 208; if no, go to step 205.

Step 205: According to the single-end dynamic programming alignment algorithm (level 2), each pair of reads on which there is only one read alignment in the partial genome sequence is compared with the reference genome sequence again. After the above-mentioned first-level two-way BWT alignment algorithm, in a pair of reads (A, A'), one (A or A') is aligned to the reference genome sequence, and the other (A' or A) is not. If there is no comparison to the reference genome sequence, the second-level alignment algorithm will be used to continue the alignment.

Optionally, the method of comparing genome sequences according to the single-end dynamic programming comparison algorithm may specifically include the following steps:

Determine that one read (A or A') in a pair of reads (A, A') is aligned to a specific position (pos position) on the reference genome sequence; the data reads obtained by paired-end sequencing are paired, assuming One read (A or A') of a pair of reads (A, A') is aligned to the pos position on the reference genome sequence, and the theoretical alignment position of the other read (A' or A) is around the pos position A certain area is the candidate area (candidate region);

Therefore, according to the preset position range threshold, select a specific range around the specific position (pos position); the preset position range threshold can be selected according to actual needs, for example, set with reference to the error tolerance range; specifically, in double In end-to-end sequencing, a pair of reads are compared to the genome, then the distance between the two reads and the sum of the lengths of the two reads is equal to the length of the sequencing fragment (fragment), and the position of the candidate region is determined according to this principle. For example, if the sequencing fragment is 500bp and each read is 150bp, then after alignment to the genome, the theoretical distance between the two reads is 200bp. Because the sequencing fragments are of different lengths, the theoretical distance is about 100bp-200bp;

Within the specified range, use a dynamic programming algorithm to align the other (A' or A) in a pair of reads that is not aligned; step 206: whether there is at least a pair of reads in the partial genome sequence Both reads are not aligned (that is, in the partial genome sequence, each read of at least one pair of reads is not aligned); if so, go to step 108; if not, go to step 207.

Step 207: According to the paired-end dynamic programming alignment algorithm (level 3), each pair of reads in the partial genome sequence that is not aligned with the two reads is re-aligned with the reference genome sequence. In a pair of reads (A, A'), after the first-level two-way BWT comparison algorithm and the second-level single-end dynamic programming comparison algorithm, A and A in a certain pair of reads (A, A') None of A' has been aligned with the reference genome sequence, and the third-level alignment algorithm will be used to continue the alignment.

Optionally, the method of comparing genome sequences according to the paired-end dynamic programming comparison algorithm may specifically include the following steps:

Construct seeds (seeds, substrings of a read) for each of a pair of reads (A and A');

Specifically, each read of a pair of reads (A, A') is divided into many small segments, and seeds (seeds, substrings of a read) are constructed; when a pair of reads is compared to the genome, the distance between the two reads Within a certain range, so the distance between the two read seeds should also be within a certain range;

Align each seed to the reference genome sequence;

Specifically, the paired (that is, the distance between the two seeds meets the requirements) regions for the alignment of the seeds are retrieved, and the candidate alignment regions for the pair of reads are determined. Then use the dynamic programming algorithm to compare the reads to the candidate regions.

If in a certain region of the reference genome sequence, two (A and A') of the reads have corresponding seed alignments respectively, then this region is a candidate region for the final alignment position;

Use the dynamic programming algorithm to compare two (A and A') of the reads in the candidate region; after the comparison is completed, enter step 208; Genome sequence file; if no, return to step 102; if yes, enter step 109.

Step 209: output the comparison result. Optionally, the BAM file is the output file of the genome sequence alignment. BAM is the format for saving the genome sequence alignment results, and records the position of the genome sequence in the reference genome sequence and the detailed sequence alignment.

As can be seen from the above examples, the genome sequence comparison method provided by the present invention, by setting a multi-level comparison algorithm, uses the next level of comparison algorithm to continue to compare the parts that cannot be matched after the previous level of algorithm comparison is completed. Comparison, so that the complexity of the algorithm matches the complexity of the data, and optimize each level of the algorithm, and then achieve the optimization of the overall algorithm speed. Using the genome sequence comparison method provided by the present invention, under the premise of the same resources and ensuring the accuracy of the comparison, the comparison time of a person's whole genome sequence can be shortened to about 4 hours, compared with the comparison time of the prior art There is a significant shortening, which improves the efficiency of data analysis.

Based on the above purpose, the second aspect of the embodiment of the present invention proposes an embodiment of a genome data storage device, which can solve the problem of low efficiency caused by frequent input and output of a large number of binary files in the process of genome variation detection. As shown in FIG. 3 , it is a schematic structural diagram of an embodiment of the genome data storage device provided by the present invention.

The genome data storage device includes:

Creating module 301, used for obtaining gene sequence comparison information and creating gene sequence statistical information during the genome comparison process;

The comparison information storage module 302 is used to store the gene sequence comparison information in the disk, and store the corresponding index in the memory according to the comparison position of the gene sequence comparison information in the genome; The storage location of the sequence alignment information in the disk;

Statistical information classification module 303, configured to classify the genome statistical information to obtain first statistical information and second statistical information;

The statistical information storage module 304 is configured to store the first statistical information in the memory, the first statistical information is the statistical information whose access frequency is higher than the preset frequency during the mutation detection process; and store the second statistical information in the disk, The second statistical information is statistical information that cannot be stored in memory and/or statistical information whose access frequency is lower than a preset frequency during the mutation detection process.

In some optional implementation manners, the first statistical information includes base-weighted quality value statistical information, positive and negative strand statistical information, indel statistical information, and soft-cut statistical information.

In some optional embodiments, for a site where there are no indels and soft cuts, and at most two base types appear, the first statistical information of the site is stored in the first data structure;

The first data structure includes:

The first head used to indicate the base type;

A first quality value storage unit for representing base-weighted quality values;

A first positive chain number storage unit for representing the number of positive chains;

A first negative chain number storage unit for indicating the number of negative chains.

In some optional embodiments, for a site where an indel occurs and 3-4 base types appear, the first statistical information of the site is stored using the first data structure and the second data structure;

The second data structure includes:

Base-weighted quality value statistics and positive and negative strand statistics for each of the four base types; the storage structure of base-weighted quality value statistics and positive and negative strand statistics for each base type specifically includes: a second quality value storage unit for base weighted quality values, a second positive chain number storage unit for representing the number of positive chains, and a second negative chain number storage unit for representing the number of negative chains;

The first insertion statistical information specifically includes: a first insertion sequence storage unit used to represent the insertion sequence, and a first low-quality insertion number storage unit used to represent the number of low-quality insertions;

The first deletion statistical information specifically includes: a first deletion length storage unit used to indicate the deletion length, a first high-quality deletion number storage unit used to indicate the number of high-quality deletions, and a first lowest deletion number storage unit used to indicate the number of low-quality deletions. Mass missing number storage unit;

The first data structure includes:

the second header filled with 11;

The first insertion information storage unit used to indicate whether there is an insertion, specifically includes: a first insertion information sub-storage unit used to indicate whether there is an insertion, an insertion length sub-storage unit used to indicate the insertion length, and a sub-storage unit used to indicate low-quality insertion Quantity of low-quality insertion into digital sub-storage;

A first missing information storage unit for indicating whether there is a missing;

A pointer to the corresponding second data structure storage location.

In some optional embodiments, for a site with more than one indel and an insertion length greater than 12 bases, the first statistical information of the site is stored in the first data structure and the third data structure, and for For the first statistical information of such a site, a memory pool is created in memory for storage;

The third data structure includes:

Base-weighted quality value statistics and positive and negative strand statistics for each of the four base types; the storage structure of base-weighted quality value statistics and positive and negative strand statistics for each base type specifically includes: a third quality value storage unit for base weighted quality values, a third positive chain number storage unit for representing the number of positive chains, and a third negative chain number storage unit for representing the number of negative chains;

The second insertion statistical information specifically includes: an insertion length storage unit used to indicate the insertion length, a second insertion sequence storage unit used to indicate the insertion sequence, a second low-quality insertion number storage unit used to indicate the number of low-quality insertions, and, a high-quality insertion number storage unit for representing the number of high-quality insertions;

The second deletion statistical information specifically includes: a second deletion length storage unit used to indicate the deletion length, a second high-quality deletion number storage unit used to indicate the number of high-quality deletions, and a second-lowest deletion number storage unit used to indicate the number of low-quality deletions Mass missing number storage unit;

The first data structure includes:

a third header filled with 11;

The second insertion information storage unit for indicating whether there is an insertion, specifically includes: a second insertion information sub-storage unit for indicating whether there is an insertion, a first memory pool information sub-storage unit for indicating whether a memory pool is used, A first occupancy length sub-storage for representing an occupancy length in the memory pool;

The second missing information storage unit for indicating whether there is a missing, specifically includes: a second missing information sub-storage for indicating whether there is a missing, a second memory pool information sub-storage for indicating whether a memory pool is used, A second occupied length sub-storage for representing the occupied length in the memory pool.

In some optional implementation manners, for the soft clipping statistical information, a dynamic array is used to record, and each record includes:

a soft-splice location store for representing where the soft-splice is located on the genome;

a soft clipping left number store for representing the number of times soft clipping occurs to the left of the corresponding site;

Soft clipping right number storage for indicating the number of times soft clipping occurs to the right of the corresponding site.

In some optional embodiments, the index includes a paired-end alignment information index and a single-end alignment information index;

For the double-end comparison information index, the double-end comparison array structure is used for storage, and the double-end comparison array structure includes:

a first ID storage unit for representing the ID of the gene sequence;

A first alignment position storage unit used to indicate the position of the gene sequence aligned to the genome;

an insert length storage unit representing an insert length of a gene sequence;

A first alignment quality value storage unit for representing the alignment quality value of the gene sequence;

A first average quality value storage unit for representing the average quality value of the gene sequence;

For the single-end comparison information index, the single-end comparison array structure is used for storage, and the single-end comparison array structure includes:

a second ID storage unit for the ID representing the gene sequence;

A second comparison position storage unit used to indicate the position of the gene sequence compared to the genome;

A second alignment quality value storage unit for representing the alignment quality value of the gene sequence;

A second average quality value storage unit for representing the average quality value of the gene sequence;

Wherein, for each gene sequence used for comparison, its corresponding index is arranged in order according to the comparison position of the gene sequence on the genome.

In some optional embodiments, the gene sequence comparison information is stored in a disk, specifically including:

Therefore, the gene sequence comparison information is divided into 512 files and stored on the disk. Each file stores the gene sequence comparison information of a certain genome interval. The storage data structure of each gene sequence comparison information includes:

a sequence length storage unit for representing the sequence length of the gene sequence;

A sequence store for representing the gene sequence itself;

a quality value storage unit for representing the quality value of the gene sequence;

A start position storage unit used to represent the start position of the alignment algorithm when the gene sequence is compared;

The positive and negative strand storage part used to represent the positive and negative strand information of the gene sequence during alignment;

A region length storage part used to indicate the length of the genome region selected during gene sequence alignment;

The left position storage part used to represent the left riveting position of the gene sequence during alignment;

A right position storage unit used to indicate the position of the right riveted position of the gene sequence during alignment.

Based on the above purpose, the third aspect of the embodiments of the present invention proposes an embodiment of an apparatus for implementing the genome data storage method. As shown in FIG. 4 , it is a schematic diagram of the hardware structure of an embodiment of the device for implementing the genome data storage method provided by the present invention.

As shown in Figure 4, the device includes:

One or more processors 401 and memory 402, one processor 401 is taken as an example in FIG. 4 .

The device for executing the genome data storage method may further include: an input device 403 and an output device 404 .

The processor 401, the memory 402, the input device 403, and the output device 404 may be connected via a bus or in other ways. In FIG. 4, connection via a bus is taken as an example.

The memory 402, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs and modules, such as the genome data storage method in the embodiment of the present application corresponds to program instructions/modules (for example, the creation module 301, comparison information storage module 302, statistical information classification module 303, and statistical information storage module 304 shown in FIG. 3). The processor 401 executes various functional applications and data processing of the server by running non-volatile software programs, instructions and modules stored in the memory 402, that is, implements the genomic data storage method of the above method embodiment.

The memory 402 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application program required by at least one function; the data storage area may store data created according to the use of the genome data storage device, and the like. In addition, the memory 402 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the storage 402 may optionally include storages that are set remotely relative to the processor 401, and these remote storages may be connected to the member user behavior monitoring device through a network. Examples of the aforementioned networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The input device 403 can receive input numbers or character information, and generate key signal input related to user settings and function control of the genome data storage device. The output device 404 may include a display device such as a display screen.

The one or more modules are stored in the memory 402, and when executed by the one or more processors 401, perform the genome data storage method in any of the above method embodiments. The technical effect of the embodiment of the device for implementing the genomic data storage method is the same as or similar to that of any method embodiment described above.

The embodiment of the present application also provides a non-transitory computer storage medium, the computer storage medium stores computer-executable instructions, and the computer-executable instructions can execute the processing method of list item operation in any of the above method embodiments. The technical effect of the embodiment of the non-transitory computer storage medium is the same as or similar to that of any method embodiment described above.

Finally, it should be noted that those skilled in the art can understand that the implementation of all or part of the processes in the methods of the above embodiments can be completed by instructing related hardware through computer programs, and the programs can be stored in computer-readable storage media When the program is executed, it may include the processes of the embodiments of the above-mentioned methods. Wherein, the storage medium may be a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM) or a random access memory (Random Access Memory, RAM), etc. The technical effect of the computer program embodiment is the same or similar to that of any method embodiment described above.

Those of ordinary skill in the art should understand that: the discussion of any of the above embodiments is exemplary only, and is not intended to imply that the scope of the present disclosure (including claims) is limited to these examples; under the idea of the present invention, the above embodiments or Combinations between technical features in different embodiments are also possible, steps may be carried out in any order, and there are many other variations of the different aspects of the invention as described above, which are not presented in detail for the sake of brevity.

In addition, well-known power/ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided figures, for simplicity of illustration and discussion, and so as not to obscure the present invention. . Furthermore, devices may be shown in block diagram form in order to avoid obscuring the invention, and this also takes into account the fact that details regarding the implementation of these block diagram devices are highly dependent on the platform on which the invention is to be implemented (i.e. , these details should be well within the understanding of those skilled in the art). Where specific details (eg, circuits) have been set forth to describe example embodiments of the invention, it will be apparent to those skilled in the art that other embodiments may be implemented without or with variations from these specific details. Implement the present invention down. Accordingly, these descriptions should be regarded as illustrative rather than restrictive.

Although the invention has been described in conjunction with specific embodiments of the invention, many alternatives, modifications and variations of those embodiments will be apparent to those of ordinary skill in the art from the foregoing description. For example, other memory architectures such as dynamic RAM (DRAM) may use the discussed embodiments.

Embodiments of the present invention are intended to embrace all such alterations, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent replacements, improvements, etc. within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (10)

1. A method of genomic data storage, comprising:

in the comparison process, obtaining gene sequence comparison information and creating gene sequence statistical information;

storing the gene sequence comparison information in a magnetic disk, and storing corresponding indexes in an internal memory according to the comparison position of the gene sequence comparison information in a genome; the index is the storage position of the gene sequence comparison information in a magnetic disk;

classifying the genome statistical information to obtain first statistical information and second statistical information;

storing first statistical information in a memory, wherein the first statistical information is statistical information of which the access frequency is higher than a preset frequency in a variation detection process;

and storing second statistical information in the magnetic disk, wherein the second statistical information is statistical information which cannot be stored in the memory and/or statistical information of which the access frequency is lower than the preset frequency in the variation detection process.

2. The method of claim 1, wherein the first statistical information comprises base weighted quality value statistics, sign statistics, indel statistics, and soft-clip statistics.

3. The method of claim 2, wherein for a site where no insertion deletion or soft splicing has occurred and at most 2 base types have occurred, first statistical information of the site is stored using a first data structure;

the first data structure, comprising:

a first header for indicating a base type;

a first quality value storage unit for storing a base weight quality value;

a first positive strand number storage unit for indicating the number of positive strands;

a first minus-strand number storage unit for indicating the number of minus strands.

4. The method of claim 2, wherein for a site where an indel occurs and 3 to 4 base types occur, the first statistical information of the site is stored using the first data structure and the second data structure;

the second data structure, comprising:

statistical information of base weight quality values and statistical information of positive and negative chains of the 4 base types respectively; the storage structure of the statistical information of the base weight quality value and the statistical information of the positive and negative chains of each base type specifically comprises the following steps: a second mass value storage unit for indicating a base weight mass value, a second positive strand number storage unit for indicating the number of positive strands, and a second negative strand number storage unit for indicating the number of negative strands;

the first insertion statistical information specifically includes: a first insertion sequence storage unit for storing an insertion sequence, a first low-quality insertion number storage unit for storing a low-quality insertion number;

the first missing statistical information specifically includes: a first missing length storage section for indicating a missing length, a first high-quality missing number storage section for indicating a number of high-quality missing, a first low-quality missing number storage section for indicating a number of low-quality missing;

the first data structure, comprising:

a second head filled with 11;

the first insertion information storage unit for indicating whether or not there is an insertion, specifically includes: a first insertion information sub-storage unit for indicating whether or not there is an insertion, an insertion length sub-storage unit for indicating an insertion length, and a low quality insertion number sub-storage unit for indicating a low quality insertion number;

the first missing information storage unit for indicating whether there is a missing includes: a first missing information sub-storage unit for indicating whether or not there is a missing;

a pointer to a corresponding second data structure storage location.

5. The method according to claim 2, wherein for a site where more than 1 indel occurs and the length of the insertion is greater than 12 bases, the first statistical information for the site is stored using the first data structure and the third data structure, and for the first statistical information for such site, a memory pool is created in the memory for storage;

the third data structure, comprising:

statistical information of base weight quality values and statistical information of positive and negative chains of the 4 base types respectively; the storage structure of the statistical information of the base weight quality value and the statistical information of the positive and negative chains of each base type specifically comprises the following steps: a third quality value storage unit for indicating a base weight quality value, a third positive strand number storage unit for indicating the number of positive strands, and a third negative strand number storage unit for indicating the number of negative strands;

the second insertion statistical information specifically includes: an insertion length storage section for indicating an insertion length, a second insertion sequence storage section for indicating an insertion sequence, a second low-quality insertion number storage section for indicating a low-quality insertion number, and a high-quality insertion number storage section for indicating a high-quality insertion number;

the second missing statistical information specifically includes: a second missing length storage for indicating the missing length, a second high quality missing number storage for indicating the number of high quality misses, a second low quality missing number storage for indicating the number of low quality misses;

the first data structure, comprising:

a third head filled with 11;

the second insertion information storage unit for indicating whether or not there is an insertion, specifically includes: a second insertion information sub-storage unit for indicating whether or not there is an insertion, a first memory pool information sub-storage unit for indicating whether or not a memory pool is used, and a first occupied length sub-storage unit for indicating an occupied length in the memory pool;

the second missing information storage unit for indicating whether or not there is a missing specifically includes: a second missing information sub-storage unit for indicating whether there is a miss, a second memory pool information sub-storage unit for indicating whether the memory pool is used, and a second occupied length sub-storage unit for indicating the occupied length in the memory pool.

6. The method of claim 2, wherein for the soft-cut statistics, a dynamic array is used for the records, each record comprising:

a soft-clip position storage unit for storing a position of soft clip on the genome;

a soft-clipping left-side number storage section for indicating the number of times soft clipping occurs to the left of the corresponding site;

a soft-clip right-side number storage for indicating the number of times soft-clip occurs to the right of the corresponding site.

7. The method of claim 1, wherein the index comprises a double-ended alignment information index and a single-ended alignment information index;

for the double-end comparison information index, a double-end comparison array structure is adopted for storage, and the double-end comparison array structure comprises:

a first ID storage unit for storing an ID representing a gene sequence;

a first alignment position storage unit for storing a position at which a gene sequence is aligned on a genome;

an insert length storage unit for storing an insert length of a gene sequence;

a first comparison quality value storage unit for storing a comparison quality value indicating a gene sequence;

a first average quality value storage unit for storing an average quality value of a gene sequence;

for the single-ended comparison information index, storing by adopting a single-ended comparison array structure, wherein the single-ended comparison array structure comprises:

a second ID storage unit for storing an ID representing a gene sequence;

a second alignment position storage unit for storing a position of the gene sequence aligned on the genome;

a second alignment quality value storage unit for storing an alignment quality value representing a gene sequence;

a second average quality value storage unit for storing an average quality value of the gene sequence;

wherein, for each gene sequence for comparison, the corresponding indexes are arranged in sequence according to the comparison position of the gene sequence on the genome.

8. The method of claim 1, wherein storing the gene sequence alignment information in a disk comprises:

therefore, the gene sequence comparison information is divided into 512 files and stored in a disk, each file stores the gene sequence comparison information of a certain genome interval, and the storage data structure of each gene sequence comparison information comprises:

a sequence length storage unit for storing a sequence length of a gene sequence;

a sequence storage unit for storing a gene sequence;

a quality value storage unit for storing a quality value representing a gene sequence;

a start position storage unit for storing a start position of an alignment algorithm used for aligning gene sequences;

a positive/negative chain storage unit for storing positive/negative chain information of gene sequences during alignment;

a region length storage unit for storing the length of a genomic region selected when gene sequences are aligned;

a left position storage part for representing the left riveted position of the gene sequence during the comparison;

a right position storage unit for storing the right position of the gene sequence to be aligned.

9. The method according to any one of claims 1-8, further comprising:

subtracting interference caused by repeated sequences in the genome statistical information in a de-duplication process;

and/or the presence of a gas in the gas,

in the process of comparing the genes, extracting the gene sequences of the comparing regions of the genome, and adjusting the genome statistical information of the gene sequences of the comparing regions after comparing the gene sequences of the comparing regions again.

10. An electronic device, comprising:

at least one processor; and the number of the first and second groups,

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the one processor to cause the at least one processor to perform the method of any one of claims 1-9.