APEC: an accesson-based method for single-cell chromatin accessibility analysis
ABSTRACT 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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Preprint| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
bioRxiv.org - (2023) vom: 16. Sept. Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Li, Bin [VerfasserIn] |
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| doi: |
10.1101/646331 |
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| PPN (Katalog-ID): |
XBI000525642 |
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| 100 | 1 | |a Li, Bin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a APEC: an accesson-based method for single-cell chromatin accessibility analysis |
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| 520 | |a ABSTRACT 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. | ||
| 650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
| 650 | 4 | |a 570 |7 (dpeaa)DE-84 | |
| 700 | 1 | |a Li, Young |4 aut | |
| 700 | 1 | |a Li, Kun |4 aut | |
| 700 | 1 | |a Zhu, Lianbang |4 aut | |
| 700 | 1 | |a Yu, Qiaoni |4 aut | |
| 700 | 1 | |a Cai, Pengfei |4 aut | |
| 700 | 1 | |a Fang, Jingwen |4 aut | |
| 700 | 1 | |a Zhang, Wen |4 aut | |
| 700 | 1 | |a Du, Pengcheng |4 aut | |
| 700 | 1 | |a Jiang, Chen |4 aut | |
| 700 | 1 | |a Qu, Kun |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t bioRxiv.org |g (2023) vom: 16. Sept. |
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| 856 | 4 | 0 | |u http://dx.doi.org/10.1101/646331 |z kostenfrei |3 Volltext |
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