Abstract
Joint profiling technologies combining single-cell chromatin accessibility (CA) and transcriptome sequencing enable cellular heterogeneity analysis from both gene and cis-regulatory element perspectives, greatly advancing molecular biology at a cellular resolution. These techniques have been used to construct gene regulatory networks across diverse cell types and biological tissues, contributing significantly to the mapping of cell developmental trajectories. In this review, we summarize existing single-cell joint profiling methods for CA and transcriptomics and systematically evaluate the data quality of each modality using consistent criteria: the median number of genes detected per cell (RNA) and the median number of accessible peaks per cell (ATAC). Furthermore, we examine relevant bioinformatics tools and highlight their applications in various omics research contexts. Finally, we discuss the current limitations of joint profiling technologies, prospects for future improvement, the extensibility of computational tools, and the potential for co-assaying with additional omics data.