Method and device for detecting expression quantity of human endogenous retrovirus

Abstract

The embodiment of the invention provides a human endogenous retrovirus expression quantity detection method and device, and belongs to the field of gene expression quantity detection. The method comprises the following steps: summarizing virus information of known human endogenous retroviruses in a plurality of repetitive sequence databases, and generating a human endogenous retrovirus annotation file in a gene transfer format based on the summarized virus information; obtaining single cell sequencing data of the target tissue sample, and comparing a sequencing read in the single cell sequencing data to the reference genome to obtain a unique mapping read; determining a plurality of target unique mapping read segments corresponding to each cell according to the cell bar codes in the unique mapping read segments; and determining expression quantity information of the human endogenous retrovirus in each cell based on the human endogenous retrovirus annotation file and the plurality of target unique mapping reads corresponding to each cell. The method can be used for accurately detecting the expression quantity of the human endogenous retrovirus at a single cell and a unit site.

Description

Technical Field

[0001] The present disclosure relates to the technical field of gene expression level detection, and in particular to a method and device for detecting the expression level of human endogenous retrovirus. Background Art

[0002] Human endogenous retroviruses (HERVs) are endogenous retroviruses present in the human genome. They are a class of DNA sequences that originate from past viral infections that invade host cells and leave genetic traces on their chromosomes. The genetic information of HERVs viruses is fixed in the human genome and continuously passed on to future generations, playing an important role in the function and evolution of the human genome. HERVs contain characteristic sequences that are different from ordinary genes, such as LTRS and reverse transcriptase sequences, which are characteristic sequences of retroviruses. These sequences enable HERVs to have the ability to transcribe and translate in host cells, so they can produce viral particles and infect cells.

[0003] In recent years, more and more studies have shown that HERVs may have an impact on human biological processes. For example, in embryonic development, HERVs can regulate gene expression and participate in embryonic stem cell differentiation; in certain diseases, HERVs can participate in pathological processes, such as tumors and autoimmune diseases. In order to explore the extent of the impact of HERVs on human biological processes, it is necessary to detect the expression of HERVs.

[0004] However, the current detection of HERVs expression is still limited to bulk cell sequencing data, and there is still a lack of accurate detection methods for single-cell HERVs expression. Summary of the invention

[0005] The main purpose of the embodiments of the present application is to propose a method and device for detecting the expression level of human endogenous retroviruses, aiming to improve the accuracy of detecting the expression level of human endogenous retroviruses in single cells.

[0006] To achieve the above-mentioned purpose, the first aspect of the embodiment of the present application proposes a method for detecting the expression level of human endogenous retrovirus, the method comprising:

[0007] Summarize the virus information of known human endogenous retroviruses in multiple repetitive sequence databases, and generate a human endogenous retrovirus annotation file in a gene transfer format based on the summarized virus information;

[0008] Acquire single-cell sequencing data of a target tissue sample, and align sequencing reads in the single-cell sequencing data to a reference genome to obtain uniquely mapped reads;

[0009] Determine a plurality of target unique mapping reads corresponding to each cell according to the cell barcode in the unique mapping read;

[0010] The expression amount information of the human endogenous retrovirus in each cell is determined based on the human endogenous retrovirus annotation file and a plurality of target unique mapping reads corresponding to each cell.

[0011] To achieve the above-mentioned purpose, the second aspect of the embodiment of the present application proposes a device for detecting the expression level of human endogenous retrovirus, the device comprising:

[0012] A generating unit, used for summarizing the virus information of known human endogenous retroviruses in multiple repetitive sequence databases, and generating a human endogenous retrovirus annotation file in a gene transfer format based on the summarized virus information;

[0013] An alignment unit, used to obtain single-cell sequencing data of a target tissue sample, and align sequencing reads in the single-cell sequencing data to a reference genome to obtain uniquely mapped reads;

[0014] A first determining unit, configured to determine a plurality of target unique mapping reads corresponding to each cell according to the cell barcode in the unique mapping read;

[0015] The second determining unit is used to determine the expression amount information of the human endogenous retrovirus in each cell based on the human endogenous retrovirus annotation file and a plurality of target unique mapping reads corresponding to each cell.

[0016] In some embodiments, the second determining unit includes:

[0017] A reading subunit, used for reading gene sequence information corresponding to each human endogenous retrovirus from the human endogenous retrovirus annotation file;

[0018] The allocation subunit is used to allocate multiple target unique mapping reads corresponding to each cell to each human endogenous retrovirus according to the gene sequence information, so as to obtain the expression amount information of the human endogenous retrovirus in each cell.

[0019] Optionally, in some embodiments, the allocation subunit includes:

[0020] an alignment module, for aligning each human endogenous retrovirus with a plurality of target unique mapping reads corresponding to each cell according to the gene sequence information;

[0021] The first determination module is used to determine the expression amount information of the human endogenous retrovirus in each cell according to the expression amount of the target unique mapping read segment aligned with the human endogenous retrovirus.

[0022] Optionally, in some embodiments, the first determining module includes:

[0023] a determination submodule, for determining the initial expression amount of the target uniquely mapped read corresponding to the human endogenous retrovirus in each cell according to the alignment results;

[0024] The standardization processing module is used to perform standardization processing on the initial expression amount to obtain the expression amount information of the human endogenous retrovirus in each cell.

[0025] Optionally, in some embodiments, the annotation processing module may also be used to:

[0026] Get the total expression of the target uniquely mapped reads in each cell;

[0027] The expression amount information of the human endogenous retrovirus in each cell is calculated according to the initial expression amount and the total expression amount.

[0028] Optionally, in some embodiments, the generating unit comprises:

[0029] A generation subunit, used for generating an initial annotation file of an initial single site in a gene transfer format based on the summarized virus information;

[0030] The deletion subunit is used to delete the sites overlapping with human gene exons in the initial annotation file to obtain a human endogenous retrovirus annotation file.

[0031] Optionally, in some embodiments, the human endogenous retrovirus expression level detection device provided by the present application further includes:

[0032] an acquisition subunit, configured to acquire a first cell quantity corresponding to the target tissue sample;

[0033] A first determining subunit, configured to determine the number of second cells expressing each type of human endogenous retrovirus according to the expression amount information of the human endogenous retrovirus in each cell;

[0034] a second determination subunit, configured to determine a plurality of categories of target human endogenous retroviruses based on the first cell number and the second cell number;

[0035] The third determination subunit is used to determine the target expression amount information of the human endogenous retrovirus of the target category in each cell.

[0036] Optionally, in some embodiments, the second determining subunit includes:

[0037] A calculation module, used for calculating the ratio between the corresponding second cell number and the first cell number for each category of human endogenous retrovirus;

[0038] The second determination module is used to determine the human endogenous retrovirus with a ratio greater than a preset threshold as a target human endogenous retrovirus.

[0039] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the method for detecting the expression level of human endogenous retrovirus described in the first aspect.

[0040] To achieve the above-mentioned purpose, the fourth aspect of the embodiments of the present application proposes a storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the method for detecting the expression level of human endogenous retrovirus described in the first aspect.

[0041] To achieve the above-mentioned purpose, the fifth aspect of the embodiment of the present application proposes a computer program product, which includes a computer program, and the computer program is read and executed by a processor of a computer device, so that the computer device executes the method for detecting the expression level of human endogenous retrovirus described in the first aspect.

[0042] The method for detecting the expression level of human endogenous retrovirus proposed in the embodiment of the present application summarizes the virus information of known human endogenous retroviruses in multiple repetitive sequence databases, and generates a human endogenous retrovirus annotation file in a gene transfer format based on the summarized virus information; obtains single-cell sequencing data of a target tissue sample, and aligns the sequencing reads in the single-cell sequencing data to a reference genome to obtain a unique mapping read; determines multiple target unique mapping reads corresponding to each cell according to the cell barcode in the unique mapping read; and determines the expression level information of the human endogenous retrovirus in each cell based on the human endogenous retrovirus annotation file and the multiple target unique mapping reads corresponding to each cell.

[0043] It can be seen that the method for detecting the expression of human endogenous retroviruses provided in the embodiment of the present application first summarizes the known human endogenous retroviruses and compiles an annotation file in a gene transfer format, and then matches the unique mapping reads corresponding to each cell in the single-cell sequencing results of each cell based on the annotation file, and determines the single-site expression of human endogenous retroviruses in each cell according to the expression of the matched unique mapping reads. This method provides a method for detecting the expression of human endogenous retroviruses at a single site in a single cell, which improves the accuracy of detecting the expression of human endogenous retroviruses in a single cell. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings are used to provide further understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0045] Figure 1 A schematic diagram of the process of detecting the expression level of human endogenous retrovirus provided in this application;

[0046] Figure 2 Another schematic diagram of the process of detecting the expression level of human endogenous retrovirus provided in the present application;

[0047] Figure 3 Schematic diagram of some HERVs expression matrices obtained based on the GSE196830 dataset;

[0048] Figure 4 Heatmap for differential expression analysis based on HERV expression matrix at single locus resolution;

[0049] Figure 5 It is a UMAP map of the expression information of a specific type of HERV (LT7_dup7-chr12);

[0050] Figure 6 Schematic diagram of some HERVs expression matrices obtained based on AIDA dataset processing;

[0051] Figure 7 Heat map for age differential expression analysis based on the HERV expression matrix at a single locus resolution;

[0052] Figure 8 A scatter plot showing an example of changes in a single site with age;

[0053] Fig. 9 A schematic diagram of a human endogenous retrovirus expression level detection device provided in an embodiment of the present application;

[0054] Fig.10 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0056] Before further describing the embodiments of the present application in detail, the nouns and terms involved in the embodiments of the present application are explained. The nouns and terms involved in the embodiments of the present application are subject to the following interpretations:

[0057] Repetitive sequence: A repetitive sequence refers to a sequence that exists in a nucleic acid (DNA or RNA) molecule, has a specific nucleotide sequence pattern, and is repeated in the genome. Repetitive sequences can be classified into tandem repeats and interspersed repeats, and have functions such as gene expression regulation, chromosome structure maintenance, and providing raw materials for genome evolution. Human endogenous retroviruses are a type of repetitive sequence, specifically similar to retrotransposons interspersed in repetitive sequences, which can move and replicate themselves in the genome through a mechanism similar to that of transposons. The repetitive sequence database in the present application can be a database containing a large number of known repetitive sequences, which contains a large amount of sequence information of known human endogenous retroviruses.

[0058] Gene transfer format (GTF): An extended version based on the General Feature Format (GFF) used to store transcriptome annotation information of genes. It is recorded in a table format, with each line describing a feature on the genome. Each line includes 9 fixed fields, and the fields are separated by tabs. The fields include: chromosome number, feature source, feature type, start position, end position, score, chain, reading frame, and attribute. The gene transfer format file has the function of annotating gene functions. By parsing the gene transfer format file, the location, structure and other information of the gene can be obtained, and the functional area of ​​the gene can be identified. In addition, the gene transfer format file also has the ability of gene expression analysis, which is often used in RNA-seq analysis, helping tools such as HISAT2, STAR and StringTie to align the alignment results with the gene model, thereby calculating the gene expression.

[0059] Uniquely mapped reads (UMR): In high-throughput sequencing data analysis, uniquely mapped reads refer to short sequences (reads) obtained by sequencing that have only one clear alignment position on the reference genome (or reference transcriptome, etc.). When a large number of short sequences generated by sequencing are aligned with the reference sequence, each read will try to find its possible origin position on the reference sequence. If a read can only be located at a specific position in the reference sequence, then this read is called a uniquely mapped read. In contrast to uniquely mapped reads are multi-mapped reads, which refer to sequencing reads that can be aligned to multiple different positions in the reference genome. This may be due to the short read sequence and the presence of multiple similar sequence regions in the genome (such as similar coding regions of gene family members, repetitive sequence regions, etc.). For example, when analyzing transcriptome sequencing data, some non-specific transcript sequences or highly conserved transcript sequence portions of gene family members may generate multiple mapped reads. Uniquely mapped reads do not have this ambiguity. They clearly correspond to a position in the reference sequence, which is more conducive to accurately determining the expression position and structure of genes. In RNA-Seq (transcriptome sequencing), uniquely mapped reads are essential for accurate gene expression quantification. Gene expression levels are usually estimated by counting the number of reads mapped to a specific gene region. Uniquely mapped reads can be more accurately assigned to the corresponding gene, resulting in a more accurate estimate of gene expression.

[0060] Cell Barcoding (CB): A technology used to label and distinguish individual cells. It assigns a unique nucleic acid sequence tag to each cell (similar to the barcode of a commodity), so that the origin, identity and other relevant information of each cell can be tracked and identified in complex cell population experiments. These tags are usually short DNA or RNA sequences. In single-cell transcriptome sequencing (scRNA-Seq), cell barcodes play a key role. Because different cells can be distinguished, transcripts of a large number of single cells can be sequenced and analyzed at the same time. For example, when studying the heterogeneity of tumor tissue, tumor tissue contains many different types of cells, such as cancer cells, immune cells, vascular endothelial cells, etc. Through cell barcoding, the gene expression of each single cell can be analyzed, so as to more accurately understand the gene expression differences and functional status of different cell types in tumor tissue.

[0061] Unique Molecular Identifier (UMI): A short nucleic acid sequence tag, usually a random combination of nucleotides, generally about 4-10 nucleotides in length. These tags are added to DNA or RNA molecules to distinguish individual nucleic acid molecules in the original sample. UMI can be generated during library preparation by synthesizing primers or oligonucleotides with UMI tags. For example, when preparing mRNA sequencing libraries, UMI is added to reverse transcription primers. When mRNA molecules undergo reverse transcription reactions, each mRNA molecule will be labeled with a unique UMI. Due to some deviations in the sequencing process, such as errors in PCR amplification, sequencing errors, etc., the estimation of the number of original nucleic acid molecules may be inaccurate. The existence of UMI can correct this deviation. Because all amplification products from the same original nucleic acid molecule will carry the same UMI, by counting UMIs, the true number of original nucleic acid molecules can be more accurately estimated.

[0062] In the related technologies, quantitative analysis of human endogenous retroviruses usually includes the Telescope solution, the ERVmap solution, and the ScTE solution. Among them, the Telescope solution can only quantify the expression of HERV for bulk RNA-seq, and is not applicable to single-cell sequencing data. In addition, Telescope uses the Bayesian inference method for read segment allocation, which requires a lot of computing resources, especially when processing large-scale RNA-Seq data, the computing time and memory consumption may be high. The ERVmap solution can also only quantify the expression of HERV for bulk RNA-seq, and is not applicable to single-cell sequencing data. The ScTE solution provides HERV expression at family resolution, and cannot detect HERV expression at a single site.

[0063] In summary, there is currently a lack of a method that can detect the expression level of human endogenous retroviruses at a single cell unit site.

[0064] Based on this, the embodiments of the present application provide a method, device, electronic device and storage medium for detecting the expression level of human endogenous retroviruses, which uses a pre-compiled single-site human endogenous retrovirus annotation file to identify human endogenous retroviruses in the unique mapping reads of each cell in the single-cell sequencing data, thereby obtaining the human endogenous retrovirus expression level of the single-cell single-site. Below, the method for detecting the expression level of human endogenous retroviruses provided in the embodiments of the present application is described.

[0065] Reference Figure 1In some embodiments, the method for detecting the expression level of human endogenous retrovirus provided in the embodiments of the present application includes but is not limited to steps 101 to 104.

[0066] Step 101, summarize the virus information of known human endogenous retroviruses in multiple repetitive sequence databases, and generate a human endogenous retrovirus annotation file in a gene transfer format based on the summarized virus information.

[0067] In the method for detecting the expression level of human endogenous retrovirus provided in the present application, firstly, an annotation file of human endogenous retrovirus can be compiled. Specifically, multiple repetitive sequence databases can be integrated to collect and organize human endogenous retroviruses. The repetitive sequence databases can include public databases such as RepeatMasker and Repbase. The known human endogenous retroviruses in these public databases are collected and organized, and then a human endogenous retrovirus annotation file in a gene transfer format is generated to provide annotation information for the subsequent quantitative process.

[0068] The human endogenous retrovirus annotation file is compiled based on the collected and collated human endogenous retrovirus data, and specifically, the human endogenous retrovirus data is compiled into an annotation file at a resolution of a single site. That is, for each known human endogenous retrovirus, the corresponding 9 fields of gene information are obtained, and then a row of data in the human endogenous retrovirus annotation file is generated.

[0069] In some embodiments, generating a human endogenous retrovirus annotation file in a gene transfer format based on the aggregated virus information comprises:

[0070] Generate an initial annotation file of the initial single locus in the gene transfer format based on the summarized virus information;

[0071] The sites in the initial annotation file that overlap with human gene exons were deleted to obtain the human endogenous retrovirus annotation file.

[0072] In the embodiment of the present application, a large number of known human endogenous retroviruses are collected and sorted from multiple repetitive sequence databases, and detailed information of each known human endogenous retrovirus is queried in the repetitive sequence database, and the information of the above 9 fixed fields of each known human endogenous retrovirus is sorted and extracted, and the annotation information of each human endogenous retrovirus is sorted and obtained, and then these information are summarized to obtain the initial annotation file of a single gene locus. Then, these initial annotation files can be further screened to obtain high-quality human endogenous retrovirus annotation files.

[0073] Among them, the specific process of screening the initial annotation file can be to delete the information corresponding to the gene sites overlapping with the human gene exons in the initial annotation file, so as to obtain a high-quality human endogenous retrovirus annotation file. Among them, exons are part of the eukaryotic gene. The gene is structurally composed of alternating exons and introns. Exons are the sequence parts that encode proteins. The genetic information contained in them will eventually be reflected in mature mRNA (messenger ribonucleic acid), which will be used to synthesize proteins after transcription and translation. For example, the human hemoglobin gene contains multiple exons. After gene expression, the information of these exons will guide the synthesis of hemoglobin protein. By deleting the human endogenous retrovirus gene sites that overlap with the human gene exons, a more accurate human endogenous retrovirus annotation file can be obtained. In the examples of the present application, human endogenous retroviruses in the two databases, RepeatMasker and Repbase, were collected and sorted, and then converted into gene transfer formats at a single site resolution, and human endogenous retrovirus sites overlapping with exons of human genes were deleted, thereby obtaining approximately 700,000 human endogenous retrovirus sites, providing annotation information for the subsequent quantification process of human endogenous retroviruses.

[0074] Step 102 , obtaining single-cell sequencing data of the target tissue sample, and aligning sequencing reads in the single-cell sequencing data to a reference genome to obtain uniquely mapped reads.

[0075] Among them, after compiling the human endogenous retrovirus annotation file, it can be used to perform quantitative detection of human endogenous retroviruses at a single cell single site. Specifically, the single-cell sequencing data of the target tissue sample to be detected can be obtained, and then based on the single-cell sequencing data and the compiled human endogenous retrovirus annotation file, the cells in the target tissue sample can be quantitatively detected for human endogenous retroviruses at a single cell single site dimension.

[0076] Specifically, the target tissue sample to be tested can be first subjected to single-cell sequencing, and the mainstream single-cell sequencing platform can be used to perform single-cell sequencing on the target tissue sample to be tested, and the single-cell sequencing platform can specifically include 10x Genomics, DNBelabC4, etc. Then, the original data obtained by sequencing can be aligned using the Spliced ​​Transcripts Alignment to a Reference (STAR) tool, and then each read segment can be mapped to the reference genome.

[0077] After mapping each read to the reference genome, it can be determined which reads are multi-mapped reads and which reads are uniquely mapped reads. In order to improve the accuracy of detecting the expression of human endogenous retroviruses, in the disclosed embodiment, only uniquely mapped reads can be used to detect the expression level of human endogenous retroviruses. Specifically, after aligning the multi-mapped reads and the uniquely mapped reads, the multi-mapped reads can be discarded and only the uniquely mapped reads can be retained.

[0078] Step 103 , determining a plurality of target unique mapping reads corresponding to each cell according to the cell barcode in the unique mapping read.

[0079] Since single-cell sequencing divides a large number of cells in a tissue sample into individual cells for sequencing, the offline data still contains the reads corresponding to the gene fragments in all cells in the tissue, that is, the unique mapping reads screened in step 102 contain all the unique mapping reads in the tissue sample. At this time, the expression level of human endogenous retroviruses determined based on the unique mapping reads is still the batch expression of human endogenous retroviruses in the tissue sample. If the quantitative expression of human endogenous retroviruses in a single cell is required, the unique mapping reads screened in step 102 need to be divided into cell dimensions. Specifically, since a cell barcode and a unique molecular identifier are added to each read in the single-cell sequencing process, after the unique mapping reads are screened, the cell barcode of each unique mapping read can be detected and parsed to obtain the cell label information corresponding to each read.

[0080] After determining the cell label information corresponding to each unique mapping read, the unique mapping reads screened in step 102 can be divided according to the cell dimension to obtain multiple target unique mapping reads corresponding to each cell. Further, the human endogenous retrovirus quantitative analysis can be performed on the cell based on the multiple target unique mapping reads corresponding to each cell.

[0081] Step 104 : determining the expression level information of the human endogenous retrovirus in each cell based on the human endogenous retrovirus annotation file and the multiple target unique mapping reads corresponding to each cell.

[0082] Among them, after determining the multiple target unique mapping reads corresponding to each cell, the human endogenous retrovirus annotation file compiled in step 101 and the target unique mapping reads corresponding to each cell determined in step 103 can be further used to determine the expression level information of the human endogenous retrovirus in each cell.

[0083] In some embodiments, determining the expression level information of the human endogenous retrovirus in each cell based on the human endogenous retrovirus annotation file and multiple target unique mapping reads corresponding to each cell includes:

[0084] Read the gene sequence information corresponding to each human endogenous retrovirus from the human endogenous retrovirus annotation file;

[0085] According to the gene sequence information, multiple target unique mapping reads corresponding to each cell are assigned to each human endogenous retrovirus to obtain the expression amount information of the human endogenous retrovirus in each cell.

[0086] The expression level information of the human endogenous retrovirus in each cell in the target tissue sample is detected based on the compiled human endogenous retrovirus annotation file and multiple target unique mapping reads contained in each cell in the target tissue sample. Specifically, the gene sequence information corresponding to each human endogenous retrovirus can be first read from the human endogenous retrovirus annotation file.

[0087] Then, according to the extracted gene sequence information corresponding to each human endogenous retrovirus, multiple unique mapping reads corresponding to each cell are assigned to each human endogenous retrovirus, so as to obtain the expression amount information of the human endogenous retrovirus in each cell.

[0088] In some embodiments, assigning multiple target unique mapping reads corresponding to each cell to each human endogenous retrovirus according to the gene sequence information to obtain the expression amount information of the human endogenous retrovirus in each cell includes:

[0089] Aligning each human endogenous retrovirus with multiple target uniquely mapped reads corresponding to each cell based on gene sequence information;

[0090] The expression level information of human endogenous retrovirus in each cell is determined based on the expression level of the target uniquely mapped reads aligned to the human endogenous retrovirus.

[0091] In an embodiment of the present disclosure, a specific method for assigning multiple target unique mapping reads corresponding to each cell to each human endogenous retrovirus according to the gene sequence information of each human endogenous retrovirus can be to first align each human endogenous retrovirus with the multiple target unique mapping reads corresponding to each cell according to the gene sequence information of each human endogenous retrovirus, and after the alignment, determine the expression level information of the human endogenous retrovirus in each cell according to the expression level of the target unique mapping reads aligned with the human endogenous retrovirus.

[0092] Specifically, the gene sequence information of each target unique mapping read can be determined first, and then the gene sequence information of each target unique mapping read can be aligned with the gene sequence of each human endogenous retrovirus one by one. When the gene sequence information of a target unique mapping read is aligned with the gene sequence of a human endogenous retrovirus, the expression value of the endogenous retrovirus can be added by 1 until the gene sequences of all unique mapping reads of the cell are aligned with the gene sequence information of each human endogenous retrovirus. In this way, the expression information of each human endogenous retrovirus in the cell is obtained.

[0093] Then, each cell in the single-cell sequencing result can be traversed, and the expression amount information of each human endogenous retrovirus in each cell can be obtained by aligning them one by one according to the above method, and finally the quantitative expression of the single-cell unit point of the human endogenous retrovirus in the target tissue sample can be obtained. Specifically, the expression matrix of the human endogenous retrovirus in the target tissue sample can be generated.

[0094] In some embodiments, determining the expression level information of the human endogenous retrovirus in each cell according to the expression level of the target unique mapped read segment aligned with the human endogenous retrovirus comprises:

[0095] Determine the initial expression of the target uniquely mapped reads corresponding to human endogenous retroviruses in each cell based on the alignment results;

[0096] The initial expression levels were normalized to obtain the expression level information of human endogenous retrovirus in each cell.

[0097] In the examples of the present application, when different tissue samples are subjected to single-cell sequencing, there will be technical deviations in the sequencing results, such as differences in sequencing depth or batch effects, which will lead to a lack of comparability between the expression levels of human endogenous retroviruses detected by different tissue samples due to uncontrolled variables. Therefore, the examples of the present application further propose a method for standardizing the expression levels of human endogenous retroviruses to eliminate these deviations, thereby making the expression level data of human endogenous retroviruses detected by different samples comparable, thereby making the downstream analysis results reasonable.

[0098] Specifically, after aligning multiple target unique mapping reads corresponding to each cell with each human endogenous retrovirus based on the gene sequence information of each human endogenous retrovirus to obtain the alignment result, the expression amount of the target unique mapping read corresponding to the human endogenous retrovirus in each cell determined according to the alignment result can be determined as the initial expression amount. Then, the initial expression amount is standardized to obtain the final expression amount information of the human endogenous retrovirus in each cell.

[0099] In some embodiments, the initial expression level is normalized to obtain the expression level information of the human endogenous retrovirus in each cell, including:

[0100] Get the total expression of the target uniquely mapped reads in each cell;

[0101] The expression level information of human endogenous retrovirus in each cell was calculated based on the initial expression level and the total expression level.

[0102] In the embodiment of the present disclosure, after determining the initial number of unique mapped reads corresponding to each human endogenous retrovirus in each cell, that is, determining the initial expression level of each human endogenous retrovirus in each cell, the total expression level of the target unique mapped reads in each cell can be further obtained. Then, the expression level information of the human endogenous retrovirus in each cell can be calculated based on the initial expression level and the total expression level.

[0103] That is, a method of Counts Per Million (CPM) standardization is provided in the embodiment of the present application to standardize the initial number of unique mapped reads corresponding to each human endogenous retrovirus. Among them, CPM standardization is mainly used to convert the original count data into relative frequencies per million. It has applications in many fields such as gene expression analysis and microbiome. For example, in gene expression research, CPM standardization can help compare the expression levels of genes in different samples. For example, the gene expression data obtained by high-throughput sequencing technology (such as RNA-seq), the original count (such as the number of gene reads) will be affected by factors such as sample sequencing depth, and the total number of reads obtained by sequencing different samples may be different. It is inaccurate to directly compare the original counts of genes. At this time, the gene counts are standardized by using the CPM standardization method, so that the relative frequency of gene expression can be obtained, and the relative frequency is used to characterize the expression level of the gene with better semantic rationality.

[0104] In the present application embodiment, the final expression amount information of the human endogenous retrovirus in each cell can be obtained by calculating the ratio between the initial expression amount of each human endogenous retrovirus and the target unique mapping read segment of the whole cell, and then scaling up the ratio. The specific calculation formula can be as follows:

[0105] HERV expression level = HERV counts*1e6 / (HERV+gene)total counts

[0106] Among them, HERV counts is the initial expression of human endogenous retrovirus in the cell, (HERV+gene)total counts is the total expression of HERV and other genes in the cell, or it can be understood as the total expression of the target unique mapping reads in the cell. 1e6 is the exponent of the scale expansion, which means e to the sixth power.

[0107] In some embodiments, after determining the expression amount information of the human endogenous retrovirus in each cell based on the human endogenous retrovirus annotation file and the multiple target unique mapping reads corresponding to each cell, the method further comprises:

[0108] Obtaining a first cell number corresponding to the target tissue sample;

[0109] Determining the number of second cells expressing each type of human endogenous retrovirus according to the expression amount information of the human endogenous retrovirus in each cell;

[0110] determining a plurality of categories of target human endogenous retroviruses based on the first cell number and the second cell number;

[0111] Determine the target expression information of human endogenous retrovirus of the target class in each cell.

[0112] After obtaining the expression level information of all human endogenous retroviruses in each cell, the human endogenous retroviruses contained in each cell can be further quality screened to eliminate the human endogenous retroviruses with a low probability of expression in the cell, thereby retaining the expression level of the human endogenous retroviruses with a high expression ratio in each cell, and then constructing the final high-quality human endogenous retrovirus expression matrix corresponding to each cell.

[0113] Specifically, the number of cells in the target tissue sample can be first obtained, which can be determined based on the single-cell sequencing data of the target tissue sample to obtain a first cell number of cells contained in the target tissue sample. Then, based on the expression amount information of the human endogenous retrovirus in each cell obtained by the above detection, the second cell number of cells in which each human endogenous retrovirus is expressed is determined. Then, based on the comparison result between the second cell number and the first cell number, the commonly expressed target human endogenous retrovirus can be screened out from the human endogenous retrovirus detected in the target tissue sample, and then the expression matrix of the target human endogenous retrovirus corresponding to each cell can be constructed.

[0114] The human endogenous retroviruses in the expression matrix of the target human endogenous retrovirus corresponding to each cell constructed by this method have more universal expression and are higher quality human endogenous retroviruses. Using the expression levels of the human endogenous retroviruses in the expression matrix to process downstream data can achieve better results.

[0115] In some embodiments, determining a plurality of categories of target human endogenous retroviruses based on the first cell number and the second cell number comprises:

[0116] For each category of human endogenous retrovirus, the ratio between the corresponding second cell number and the first cell number is calculated;

[0117] The human endogenous retrovirus with a ratio greater than a preset threshold is determined as a target human endogenous retrovirus.

[0118] In the disclosed embodiment, the specific method for determining the target human endogenous retrovirus based on the first cell number and the second cell number can be to calculate the ratio of the second cell number to the first cell number corresponding to each human endogenous retrovirus, and then determine whether the human endogenous retrovirus is the target human endogenous retrovirus based on the comparison result of the ratio and the preset threshold. Specifically, the human endogenous retrovirus with a ratio greater than the preset threshold can be determined as the target human endogenous retrovirus.

[0119] Specifically, the preset threshold can be set to 10%, and then for each human endogenous retrovirus, the second cell number of cells expressing the virus is obtained, and then the ratio of the second cell number to the first cell number of all cells contained in the target tissue sample is calculated. When the ratio is greater than 10%, the human endogenous retrovirus can be determined to be the target human endogenous retrovirus; when the ratio is less than 10%, it can be determined that the human endogenous retrovirus is not the target human endogenous retrovirus, and the expression information corresponding to the human endogenous retrovirus can be deleted from the initial human endogenous retrovirus expression matrix to obtain the final high-quality human endogenous retrovirus expression matrix with single-cell unit point resolution.

[0120] In some embodiments, after obtaining a high-quality expression matrix of human endogenous retroviruses, the HERVs therein can be further annotated, including whether the HERV is located on a gene or in a gene interval, which genes are nearby the HERV, or whether there are transcription factors that can bind to it, etc., to facilitate subsequent use by researchers.

[0121] like Figure 2 FIG. 1 is another schematic diagram of a method for detecting the expression level of human endogenous retrovirus provided in the present application, the method comprising:

[0122] Step 201 , summarize the HERVs in RepeatMasker and Repbase, and convert the HERV information into a gene transfer format file at a single site resolution.

[0123] Step 202, delete the HERV sites in the gene transfer format file that overlap with human gene exons to obtain a HERVs annotation file.

[0124] Step 203, obtain the single-cell sequencing offline data, align the raw reads using STAR, and map each read to the reference genome.

[0125] Step 204 , determining unique mapping reads according to the mapping results of the reads, and determining unique mapping reads corresponding to each cell according to the cell barcodes of the unique mapping reads.

[0126] Step 205 , assigning the unique mapped reads of each cell to a specific HERV according to the HERVs annotation file, and generating an initial HERVs expression matrix for each cell.

[0127] Step 206, normalize the expression data in the initial HERVs expression matrix to obtain a standardized HERVs expression matrix for each cell.

[0128] Step 207 , quality screening is performed on each HERV in the standardized HERVs expression matrix of each cell to obtain a target HERVs expression matrix.

[0129] pass Figure 2 The human endogenous retrovirus expression detection method provided can directly detect the human endogenous retrovirus expression matrix with high-quality single-cell unit-site resolution of tissue samples. Parsing the expression of HERV with unit-site accuracy in single-cell data can help researchers analyze the functions of HERVs as cis-regulatory elements (such as promoters, enhancers, insulators, etc.) and understand their position and role in the gene regulatory network. In addition, the human endogenous retrovirus expression detection method provided in this application can provide the HERVs expression data required for a deeper exploration of the regulatory mechanism of HERVs affecting diseases, thereby accelerating the search for new diagnostic and therapeutic targets for diseases.

[0130] The following demonstrates the process of the method for detecting the expression level of human endogenous retrovirus provided by the present application and the research results brought about by it through implementation in two data sets.

[0131] Embodiment 1

[0132] The human endogenous retrovirus expression detection method provided in this application was implemented in the GSE196830 data set. This example obtained 981 healthy human PBMC single-cell RNA sequencing data based on the public GEO database, and used the human endogenous retrovirus expression detection method provided in this application to mine HERV expression and filter HERV. After filtering, an expression matrix of 1.2 million cells and 566,668 HERVs was obtained. Figure 3 As shown, Figure 3 This is a schematic diagram of a partial HERVs expression matrix obtained based on the GSE196830 dataset. Each row represents a cell, each column represents a HERV site, and the value is the expression level of the corresponding HERV point in the corresponding cell.

[0133] According to the expression matrix of human endogenous retroviruses obtained based on the GSE196830 dataset, differential expression analysis revealed that some HERVs have cell-specific expression characteristics. Figure 4 As shown, Figure 4 This is a heat map of differential expression analysis based on a HERV expression matrix with single site resolution. Each column represents a cell, each row represents a HERV site, and the color of the heat map represents the HERV expression level.

[0134] like Figure 5As shown in the figure, it is a UMAP diagram of the expression information of a specific type of HERV (LT7_dup7-chr12). As shown in the figure, LT7_dup7-chr12 is only expressed in the cell cluster in the lower left corner. Each point in the figure represents a cell, and the color is the expression level of LT7_dup7-chr12.

[0135] Embodiment 2

[0136] The human endogenous retrovirus expression detection method provided in this application was implemented in the AIDA data set. The embodiment of this application obtained 339 healthy human PBMC single-cell RNA sequencing data based on the public database humancellatlas, and the human endogenous retrovirus expression detection method provided in this application was used to mine HERV expression and filter HERV. After filtering, the expression matrix of 727,992 cells and 73,372 HERVs was obtained. Figure 6 The figure shows a schematic diagram of a partial HERVs expression matrix obtained based on the AIDA dataset. Each row in the figure represents a cell, each column represents a HERV site, and the value is the expression level of the corresponding HERV in the cell.

[0137] According to the HERV expression matrix obtained by processing the AIDA dataset, many HERVs that are differentially expressed between different ages can be found through age differential expression analysis. Figure 7 As shown, Figure 7 This is a heat map of age differential expression analysis based on the HERV expression matrix with single site resolution, where each point in the figure represents a HERV site, and red represents the gradual increase in HERV expression with age. A total of 866 HERV sites with increased expression with age were identified in this dataset.

[0138] like Figure 8 As shown in the figure, it is a scatter plot of an example of the change of a single locus with age. As shown in the figure, the expression levels of LTR45B_dup4-chr11 and MER57F_dup17-chr1 both increase with age. The expression levels of LTR54_dup24-chr5 and MLT1D_dup649-chr2 both decrease with age.

[0139] Reference Fig. 9 In some embodiments, the present application also provides a human endogenous retrovirus expression level detection device 900, the human endogenous retrovirus expression level detection device 900 comprises:

[0140] A generating unit 910 is used to summarize the virus information of known human endogenous retroviruses in multiple repetitive sequence databases, and generate a human endogenous retrovirus annotation file in a gene transfer format based on the summarized virus information;

[0141] An alignment unit 920 is used to obtain single-cell sequencing data of a target tissue sample, and align sequencing reads in the single-cell sequencing data to a reference genome to obtain uniquely mapped reads;

[0142] A first determining unit 930 is used to determine a plurality of target unique mapping reads corresponding to each cell according to the cell barcode in the unique mapping read;

[0143] The second determining unit 940 is configured to determine the expression level information of the human endogenous retrovirus in each cell based on the human endogenous retrovirus annotation file and a plurality of target unique mapping reads corresponding to each cell.

[0144] In some embodiments, the second determining unit includes:

[0145] A reading subunit, used for reading gene sequence information corresponding to each human endogenous retrovirus from a human endogenous retrovirus annotation file;

[0146] The allocation subunit is used to allocate multiple target unique mapping reads corresponding to each cell to each human endogenous retrovirus according to the gene sequence information, so as to obtain the expression amount information of the human endogenous retrovirus in each cell.

[0147] Optionally, in some embodiments, the allocation subunit includes:

[0148] An alignment module, for aligning each human endogenous retrovirus with a plurality of target unique mapping reads corresponding to each cell according to gene sequence information;

[0149] The first determination module is used to determine the expression amount information of the human endogenous retrovirus in each cell according to the expression amount of the target unique mapping read segment aligned with the human endogenous retrovirus.

[0150] Optionally, in some embodiments, the first determining module includes:

[0151] a determination submodule, for determining the initial expression amount of the target uniquely mapped read corresponding to the human endogenous retrovirus in each cell according to the alignment results;

[0152] The standardization processing module is used to standardize the initial expression amount to obtain the expression amount information of the human endogenous retrovirus in each cell.

[0153] Optionally, in some embodiments, the annotation processing module may also be used to:

[0154] Get the total expression of the target uniquely mapped reads in each cell;

[0155] The expression level information of human endogenous retrovirus in each cell was calculated based on the initial expression level and the total expression level.

[0156] Optionally, in some embodiments, the generating unit comprises:

[0157] A generation subunit, used for generating an initial annotation file of an initial single site in a gene transfer format based on the summarized virus information;

[0158] The deletion subunit is used to delete the sites overlapping with human gene exons in the initial annotation file to obtain the human endogenous retrovirus annotation file.

[0159] Optionally, in some embodiments, the human endogenous retrovirus expression level detection device provided by the present application further includes:

[0160] An acquisition subunit, used to acquire a first cell number corresponding to a target tissue sample;

[0161] A first determination subunit is used to determine the second number of cells expressing each type of human endogenous retrovirus according to the expression amount information of the human endogenous retrovirus in each cell;

[0162] a second determination subunit, configured to determine a plurality of categories of target human endogenous retroviruses based on the first cell number and the second cell number;

[0163] The third determination subunit is used to determine the target expression amount information of the human endogenous retrovirus of the target category in each cell.

[0164] Optionally, in some embodiments, the second determining subunit includes:

[0165] A calculation module, used for calculating the ratio between the corresponding second cell number and the first cell number for each category of human endogenous retrovirus;

[0166] The second determination module is used to determine the human endogenous retrovirus with a ratio greater than a preset threshold as a target human endogenous retrovirus.

[0167] Reference Fig.10 , Fig.10 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0168] The processor 1001 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0169] The memory 1002 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1002 can store an operating system and other application programs. When the technical solution provided in the embodiments of this specification is implemented by software or firmware, the relevant program code is stored in the memory 1002, and the processor 1001 calls and executes the method for detecting the expression level of human endogenous retrovirus in the embodiments of this application;

[0170] Input / output interface 1003, used to implement information input and output;

[0171] The communication interface 1004 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.);

[0172] A bus 1005 , which transmits information between various components of the device (e.g., the processor 1001 , the memory 1002 , the input / output interface 1003 , and the communication interface 1004 );

[0173] The processor 1001 , the memory 1002 , the input / output interface 1003 and the communication interface 1004 are connected to each other in communication within the device via the bus 1005 .

[0174] The embodiment of the present application further provides a computer program product, which includes a computer program. A processor of a computer device reads and executes the computer program, so that the computer device executes the above-mentioned method for detecting the expression level of human endogenous retrovirus.

[0175] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "comprises" and "comprising" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0176] It should be understood that in the present disclosure, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0177] It should be understood that in the description of the embodiments of the present application, the meaning of multiple (or multiple items) is more than two, greater than, less than, exceed, etc. are understood to not include the number, and above, below, within, etc. are understood to include the number.

[0178] In the several embodiments provided in the present disclosure, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0179] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0180] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0181] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present disclosure is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present disclosure. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store program codes.

[0182] It should also be understood that the various implementations provided in the embodiments of the present application can be combined arbitrarily to achieve different technical effects.

[0183] The above is a specific description of the implementation methods of the present disclosure, but the present disclosure is not limited to the above implementation methods. Technical personnel familiar with the art can also make various equivalent modifications or substitutions without violating the spirit of the present disclosure. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present disclosure.

Claims

1. A method for detecting the expression level of human endogenous retrovirus, characterized in that: The method comprises: Summarize the virus information of known human endogenous retroviruses in multiple repetitive sequence databases, and generate a human endogenous retrovirus annotation file in a gene transfer format based on the summarized virus information; Acquire single-cell sequencing data of a target tissue sample, and align sequencing reads in the single-cell sequencing data to a reference genome to obtain uniquely mapped reads; Determine a plurality of target unique mapping reads corresponding to each cell according to the cell barcode in the unique mapping read; The expression amount information of the human endogenous retrovirus in each cell is determined based on the human endogenous retrovirus annotation file and a plurality of target unique mapping reads corresponding to each cell.

2. The method according to claim 1, characterized in that The step of determining the expression amount information of the human endogenous retrovirus in each cell based on the human endogenous retrovirus annotation file and the multiple target unique mapping reads corresponding to each cell includes: Reading gene sequence information corresponding to each human endogenous retrovirus from the human endogenous retrovirus annotation file; According to the gene sequence information, multiple target unique mapping reads corresponding to each cell are assigned to each human endogenous retrovirus to obtain the expression amount information of the human endogenous retrovirus in each cell.

3. The method according to claim 2, characterized in that The step of assigning a plurality of target unique mapping reads corresponding to each cell to each human endogenous retrovirus according to the gene sequence information to obtain the expression amount information of the human endogenous retrovirus in each cell includes: Aligning each human endogenous retrovirus with a plurality of target uniquely mapped reads corresponding to each cell according to the gene sequence information; The expression level information of human endogenous retrovirus in each cell is determined based on the expression level of the target uniquely mapped reads aligned to the human endogenous retrovirus.

4. The method according to claim 3, characterized in that The step of determining the expression level information of the human endogenous retrovirus in each cell according to the expression level of the target unique mapping read segment aligned with the human endogenous retrovirus comprises: Determine the initial expression of the target uniquely mapped reads corresponding to human endogenous retroviruses in each cell based on the alignment results; The initial expression level is standardized to obtain the expression level information of the human endogenous retrovirus in each cell.

5. The method according to claim 4, characterized in that The step of normalizing the initial expression level to obtain the expression level information of the human endogenous retrovirus in each cell includes: Get the total expression of the target uniquely mapped reads in each cell; The expression amount information of the human endogenous retrovirus in each cell is calculated according to the initial expression amount and the total expression amount.

6. The method according to any one of claims 1 to 5, characterized in that The method of generating a human endogenous retrovirus annotation file in a gene transfer format based on the summarized virus information comprises: Generate an initial annotation file of the initial single locus in the gene transfer format based on the summarized virus information; The sites in the initial annotation file that overlap with human gene exons are deleted to obtain a human endogenous retrovirus annotation file.

7. The method according to claim 1, characterized in that After determining the expression amount information of the human endogenous retrovirus in each cell based on the human endogenous retrovirus annotation file and the multiple target unique mapping reads corresponding to each cell, the method further includes: Obtaining a first cell number corresponding to the target tissue sample; Determining the number of second cells expressing each type of human endogenous retrovirus according to the expression amount information of the human endogenous retrovirus in each cell; determining a plurality of categories of target human endogenous retroviruses based on the first cell number and the second cell number; Determine the target expression amount information of the human endogenous retrovirus of the target class in each cell.

8. The method according to claim 7, characterized in that The method of determining a plurality of categories of target human endogenous retroviruses based on the first cell number and the second cell number comprises: For each category of human endogenous retrovirus, the ratio between the corresponding second cell number and the first cell number is calculated; The human endogenous retrovirus with a ratio greater than a preset threshold is determined as a target human endogenous retrovirus.

9. A device for detecting the expression level of human endogenous retrovirus, characterized in that: The human endogenous retrovirus expression detection device comprises: A generating unit, used for summarizing the virus information of known human endogenous retroviruses in multiple repetitive sequence databases, and generating a human endogenous retrovirus annotation file in a gene transfer format based on the summarized virus information; An alignment unit, used to obtain single-cell sequencing data of a target tissue sample, and align sequencing reads in the single-cell sequencing data to a reference genome to obtain uniquely mapped reads; A first determining unit, configured to determine a plurality of target unique mapping reads corresponding to each cell according to the cell barcode in the unique mapping read; The second determining unit is used to determine the expression amount information of the human endogenous retrovirus in each cell based on the human endogenous retrovirus annotation file and a plurality of target unique mapping reads corresponding to each cell.

10. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method for detecting the expression level of human endogenous retrovirus according to any one of claims 1 to 8 is implemented.

11. A storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for detecting the expression level of human endogenous retrovirus according to any one of claims 1 to 8 is implemented.

12. A computer program product, comprising a computer program, wherein the computer program is read and executed by a processor of a computer device, so that the computer device executes the method for detecting the expression level of human endogenous retrovirus according to any one of claims 1 to 8.

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