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

Author:

Li Keyi12ORCID,Chen Xiaoyang12,Song Shuang34,Hou Lin34ORCID,Chen Shengquan5,Jiang Rui12

Affiliation:

1. Ministry of Education Key Laboratory of Bioinformatics , Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, , Beijing 100084 , China

2. Tsinghua University , Bioinformatics Division at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, , Beijing 100084 , China

3. Center for Statistical Science , Department of Industrial Engineering, , Beijing 100084 , China

4. Tsinghua University , Department of Industrial Engineering, , Beijing 100084 , China

5. School of Mathematical Sciences and LPMC, Nankai University , Tianjin 300071 , China

Abstract

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.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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