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

By Bin Li, Young Li, Kun Li, Lianbang Zhu, Qiaoni Yu, Pengfei Cai, Jingwen Fang, Wen Zhang, Pengcheng Du, Chen Jiang, Kun Qu

Posted 23 May 2019
bioRxiv DOI: 10.1101/646331 (published DOI: 10.1186/s13059-020-02034-y)

The development of sequencing technologies has promoted the survey of genome-wide chromatin accessibility at single-cell resolution; however, comprehensive analysis of single-cell epigenomic profiles remains a challenge. Here, we introduce an accessibility pattern-based epigenomic clustering (APEC) method, which classifies each individual cell by groups of accessible regions with synergistic signal patterns termed “accessons”. By integrating with other analytical tools, this python-based APEC package greatly improves the accuracy of unsupervised single-cell clustering for many different public data sets. APEC also predicts gene expressions, identifies significant differential enriched motifs, discovers super enhancers, and projects pseudotime trajectories. Furthermore, we adopted a fluorescent tagmentation-based single-cell ATAC-seq technique (ftATAC-seq) to investigated the per cell regulome dynamics of mouse thymocytes. Associated with ftATAC-seq, APEC revealed a detailed epigenomic heterogeneity of thymocytes, characterized the developmental trajectory and predicted the regulators that control the stages of maturation process. Overall, this work illustrates a powerful approach to study single-cell epigenomic heterogeneity and regulome dynamics.

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