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APEC: an accesson-based method for single-cell chromatin accessibility analysis.

Bin Li1, Young Li1, Kun Li1

  • 1Department of Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, Division of Molecular Medicine, Hefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China, Hefei, 230001, Anhui, China.

Genome Biology
|May 14, 2020
PubMed
Summary

This study introduces an accessibility pattern-based epigenomic clustering (APEC) method for single-cell epigenomic analysis. APEC enhances unsupervised clustering accuracy and predicts gene expression, motifs, and cell trajectories.

Keywords:
AccessonCell clusteringPseudotime trajectoryRegulomescATAC-seq

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Area of Science:

  • Genomics
  • Computational Biology
  • Epigenetics

Background:

  • Single-cell sequencing technologies enable genome-wide chromatin accessibility surveys.
  • Comprehensive analysis of single-cell epigenomic data presents significant challenges.

Purpose of the Study:

  • To introduce a novel method, accessibility pattern-based epigenomic clustering (APEC), for improved single-cell epigenomic profile analysis.
  • To enhance the accuracy of unsupervised single-cell clustering and enable downstream analyses.

Main Methods:

  • Developed an accessibility pattern-based epigenomic clustering (APEC) method.
  • Classified cells based on synergistic signal patterns in accessible regions, termed "accessons".

Main Results:

  • The APEC method significantly improves the accuracy of unsupervised single-cell clustering across multiple public datasets.
  • APEC facilitates prediction of gene expression, identification of enriched motifs, discovery of super-enhancers, and projection of pseudotime trajectories.

Conclusions:

  • APEC offers a powerful and versatile tool for analyzing single-cell epigenomic data.
  • The method advances our ability to understand cellular heterogeneity and regulatory mechanisms at single-cell resolution.