Going beyond cell clustering and feature aggregation: Is there single cell level information in single-cell ATAC-seq data?

ABSTRACT: Single-cell Assay for Transposase Accessible Chromatin with sequencing (scATAC-seq) has become a widely used method for investigating chromatin accessibility at single-cell resolution. However, the resulting data is highly sparse with most data entries being zeros. As such, currently available computational methods for scATAC-seq feature a range of transformation procedures to extract meaningful information from the sparse data. Most notably, these transformations can be categorized into: 1) feature aggregation with known biological associations, 2) pseudo-bulking cells of similar biology, and 3) binarisation of count data. These strategies beg the question of whether or not scATAC-seq data actually has usable single-cell and single-region information as intended from the assay. If we can

SUBMITTER: Kwok AWC 

PROVIDER: S-EPMC11661094 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature