Large-batch unicellular ATAC-seq data quality controlling and analyzing method

Abstract

The invention discloses a large-batch unicellular ATAC-seq data quality controlling and analyzing method. The unicellular ATAC-seq data quality controlling and analyzing method is characterized by comprising the first step of regarding a FASTQ format of an original sequencing file or a SAM / BAM format which is already compared as an input file; the second step of conducting quality control over a sequencing section level and a multicellular level; the third step of conducting quality control over a single cell layer; the fourth step of detecting cell clusters and cell specific peaks; the fifth step of providing a report file about quality control for a user. According to the large-batch unicellular ATAC-seq data quality controlling and analyzing method, scATAC-seq data research serves as a starting point, a systematic and comprehensive quality control and analysis procedure is constructed, specificity quality control and analysis of unicellular data of different types and visualization of unsupervised cell clusters can be systematically generated, and the true cognition of unicellular epigenetic groups is reinforced. The large-batch unicellular ATAC-seq data quality controlling and analyzing method can be applicable to unicellular ATAC-seq data of different types.

Description

technical field [0001] The invention belongs to the technical field of biology, in particular to the technical field of biological information analysis based on large batches of single-cell ATAC-seq data, and explores and develops the quality control and data analysis process of single-cell ATAC-seq data. Background technique [0002] In recent years, researchers have developed single-cell-based sequencing technologies to study epigenetic phenomena. The emergence of single-cell transcriptome sequencing technology has largely solved the problems that existed in the previous second-generation sequencing. Compared with the vigorous development and application of scRNA-seq technology, the single-cell genome and epigenome sequencing technology Progress has been relatively slow. An important reason for this phenomenon is that most genome and epigenome sequencing technologies require DNA pretreatment. For example, the amplification of DNA fragments; the conversion of bisulfite ...

AI Technical Summary

Problems solved by technology

Currently no dedicated quality control and analysis pipelines have been developed for single-cell epigenome sequencing data

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