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Review
. 2022 Sep 27;3(3):212-223.
doi: 10.1007/s42994-022-00082-5. eCollection 2022 Sep.

Fundamental and practical approaches for single-cell ATAC-seq analysis

Peiyu Shi  1 , Yage Nie  2 , Jiawen Yang  1 , Weixing Zhang  1 , Zhongjie Tang  1 , Jin Xu  1
Affiliations
Review

Fundamental and practical approaches for single-cell ATAC-seq analysis

Peiyu Shi et al. aBIOTECH. .

Erratum in

Abstract

Assays for transposase-accessible chromatin through high-throughput sequencing (ATAC-seq) are effective tools in the study of genome-wide chromatin accessibility landscapes. With the rapid development of single-cell technology, open chromatin regions that play essential roles in epigenetic regulation have been measured at the single-cell level using single-cell ATAC-seq approaches. The application of scATAC-seq has become as popular as that of scRNA-seq. However, owing to the nature of scATAC-seq data, which are sparse and noisy, processing the data requires different methodologies and empirical experience. This review presents a practical guide for processing scATAC-seq data, from quality evaluation to downstream analysis, for various applications. In addition to the epigenomic profiling from scATAC-seq, we also discuss recent studies in which the function of non-coding variants has been investigated based on cell type-specific cis-regulatory elements and how to use the by-product genetic information obtained from scATAC-seq to infer single-cell copy number variants and trace cell lineage. We anticipate that this review will assist researchers in designing and implementing scATAC-seq assays to facilitate research in diverse fields.

Keywords: Bioinformatic tools; Chromatin accessibility; Data analysis; scATAC-seq.

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Conflict of interest statement

Conflict of interestThe authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
General steps and quality control of a conventional scATAC-seq experiment. A Schematic summary of scATAC-seq library generation. B Length distribution of library fragment quantified by Qseq. C Length distribution of library fragment quantified by Agilent Bioanalyzer 2100. D Length distribution of DNA fragment by sequencing
Fig. 2
Fig. 2
Schematic overview of scATAC-seq data preprocessing workflow
Fig. 3
Fig. 3
Schematic overview of epigenomic profiling from scATAC-seq data
Fig. 4
Fig. 4
Schematic overview of genetics bonus from scATAC-seq
See this image and copyright information in PMC

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