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Formaldehyde-assisted Isolation of Regulatory Elements to Measure Chromatin Accessibility in Mammalian Cells

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Published on: April 2, 2018

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

Keyi Li¹, Xiaoyang Chen¹, Shuang Song²

¹Ministry 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, Tsinghua University, Beijing 100084, China.

Briefings in Bioinformatics

|December 19, 2023

Summary

This summary is machine-generated.

We developed Cofea, a new method to analyze single-cell chromatin accessibility sequencing (scCAS) data. Cofea effectively captures cellular heterogeneity and aids in discovering functional biological insights from epigenomic data.

Keywords:

chromatin accessibility data preprocessing epigenome feature selection single cell

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Area of Science:

Genomics
Epigenetics
Computational Biology

Background:

Single-cell chromatin accessibility sequencing (scCAS) provides insights into cellular epigenomic heterogeneity.
Identifying biologically relevant features within scCAS data remains a challenge.

Purpose of the Study:

To introduce Cofea, a novel computational method for analyzing scCAS data.
To address the gap in identifying functional features from scCAS datasets.

Main Methods:

Developed and validated the Cofea method.
Tested Cofea on 5 simulated and 54 real-world scCAS datasets.
Applied Cofea to identify cell type-specific peaks, candidate enhancers, and perform pathway and heritability analyses.

Main Results:

Cofea demonstrated superior performance in capturing cellular heterogeneity compared to existing methods.
The method successfully facilitated downstream analyses, including feature identification and enrichment.
Experiments confirmed Cofea's effectiveness across diverse datasets.

Conclusions:

Cofea is a powerful tool for dissecting epigenomic heterogeneity at single-cell resolution.
The method enhances the discovery of functional biological processes from scCAS data.
Cofea has broad potential for advancing epigenomic research.