Benchmarking computational methods for single-cell chromatin data analysis.

ABSTRACT:

Background

Single-cell chromatin accessibility assays, such as scATAC-seq, are increasingly employed in individual and joint multi-omic profiling of single cells. As the accumulation of scATAC-seq and multi-omics datasets continue, challenges in analyzing such sparse, noisy, and high-dimensional data become pressing. Specifically, one challenge relates to optimizing the processing of chromatin-level measurements and efficiently extracting information to discern cellular heterogeneity. This is of critical importance, since the identification of cell types is a fundamental step in current single-cell data analysis practices.

Results

We benchmark 8 feature engineering pipelines derived from 5 recent methods to assess their ability to discover and discriminate cell types. By usi

SUBMITTER: Luo S 

PROVIDER: S-EPMC11328424 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature