Table 9.

Available Tools for Single-Cell ATAC-seq Data Processing

	Languages	Notes	Docs	Citation
BAP	R; Python	Bead-based scATAC-seq data processing.	++	Lareau et al. (2019) Last updated: 2019
BROCKMAN	R; Bash; Ruby	Convert genomics data into K-mer words associated with chromatin marks used to compare and identify changes across samples.	++	de Boer & Regev (2018) Last updated: 2018
Cell Ranger ATAC	NA	Commercial. Set of analysis pipelines for Chromium single cell ATAC-seq.	+++	Unpublished
chromVAR	R	Identify transcription factor accessibility in single-cell data. Enables clustering of single-cell ATAC-seq data.	+++	Schep et al. (2017) Last updated: 2019
Cicero	R	Predict cis-regulatory DNA interactions using single-cell chromatin accessibility data.	+++	Pliner et al. (2018) Last updated: 2019
cisTopic	R	Identify cell states and cis-regulatory topics from single-cell data.	+++	Bravo González-Blas et al.(2019) Last updated: 2019
scABC	R	Classify single-cell ATAC using unsupervised clustering and identify chromatin regions specific to cell identity.	+	Zamanighomi et al. (2018) Last updated: 2019
SCALE	Python	Clustering and visualization of single-cell ATAC-seq data into interpretable cell populations.	++	Xiong et al. (2019) Last updated: 2019
Scasat	Bash; Python; R	Complete pipeline to process scATAC-seq data with simple steps.	+++	Baker et al. (2019) Last updated: 2019
scATAC-pro	R; Python	Comprehensive pipeline for single cell ATAC-seq analysis.	+++	Yu et al. (2019) Last updated: 2020
scOpen	Python	Chromatin-accessibility estimation of single-cell ATAC data.	+	Li et al. (2019) Last updated: 2020
SCRAT	R	Useful for studying single cell heterogeneity. Can identify changes in gene sets or transcription factor binding sites. Includes GUI and web-based service.	+++	Ji et al. (2017) Last updated: 2018
SnapATAC	R; Python	Single Nucleus Analysis Pipeline for ATAC-seq.	+++	Fang et al. (2019) Last updated: 2019