Most genetic variations associated with human complex traits are located in 
non-coding genomic regions. Therefore, understanding the genotype-to-phenotype 
axis requires a comprehensive catalog of functional non-coding genomic elements, 
most of which are involved in epigenetic regulation of gene expression. 
Genome-wide maps of open chromatin regions can facilitate functional analysis of 
cis- and trans-regulatory elements via their connections with trait-associated 
sequence variants. Currently, Assay for Transposase Accessible Chromatin with 
high-throughput sequencing (ATAC-seq) is considered the most accessible and 
cost-effective strategy for genome-wide profiling of chromatin accessibility. 
Single-cell ATAC-seq (scATAC-seq) technology has also been developed to study 
cell type-specific chromatin accessibility in tissue samples containing a 
heterogeneous cellular population. However, due to the intrinsic nature of 
scATAC-seq data, which are highly noisy and sparse, accurate extraction of 
biological signals and devising effective biological hypothesis are difficult. 
To overcome such limitations in scATAC-seq data analysis, new methods and 
software tools have been developed over the past few years. Nevertheless, there 
is no consensus for the best practice of scATAC-seq data analysis yet. In this 
review, we discuss scATAC-seq technology and data analysis methods, ranging from 
preprocessing to downstream analysis, along with an up-to-date list of published 
studies that involved the application of this method. We expect this review will 
provide a guideline for successful data generation and analysis methods using 
appropriate software tools and databases for the study of chromatin 
accessibility at single-cell resolution.