Cofea: correlation-based feature selection for single-cell chromatin accessibility data.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 38113078.
- Also identified by DOI 10.1093/bib/bbad458 and PMC identifier 10782922.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Single-cell chromatin accessibility sequencing (scCAS) technologies have enabled characterizing the epigenomic heterogeneity of individual cells. However, the identification of features of scCAS data that are relevant to underlying biological processes remains a significant gap. Here, we introduce a novel method Cofea, to fill this gap. Through comprehensive experiments on 5 simulated and 54 real datasets, Cofea demonstrates its superiority in capturing cellular heterogeneity and facilitating downstream analysis. Applying this method to identification of cell type-specific peaks and candidate enhancers, as well as pathway enrichment analysis and partitioned heritability analysis, we illustrate the potential of Cofea to uncover functional biological process.
Medical subject headings
- Chromatin
- Regulatory Sequences, Nucleic Acid