Cofea: correlation-based feature selection for single-cell chromatin accessibility data

被引：0

作者：

Li, Keyi ^{[1
]}

Chen, Xiaoyang ^{[1
]}

Song, Shuang ^{[2
]}

Hou, Lin ^{[2
]}

Chen, Shengquan ^{[3
]}

Jiang, Rui ^{[1
,4
,5
]}

机构：

[1] Tsinghua Univ, Dept Automat, Beijing, Peoples R China

[2] Tsinghua Univ, Dept Ind Engn, Beijing, Peoples R China

[3] Nankai Univ, Sch Math Sci & LPMC, Tianjin 300071, Peoples R China

[4] Tsinghua Univ, Dept Automat, Bioinformat Div, BNRIST, Beijing 100084, Peoples R China

[5] Tsinghua Univ, MOE Key Lab Bioinformat, Beijing 100084, Peoples R China

来源：

BRIEFINGS IN BIOINFORMATICS | 2024年 / 25卷 / 01期

基金：

中国国家自然科学基金;

关键词：

feature selection; chromatin accessibility; single cell; data preprocessing; epigenome; AXON ENSHEATHMENT; LOCALIZATION; RNA;

D O I：

10.1093/bib/bbad458

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

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.

引用

页数：13

共 57 条

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