APEC : an accesson-based method for single-cell chromatin accessibility analysis
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 cell by groups of accessible regions with synergistic signal patterns termed "accessons". This python-based package greatly improves the accuracy of unsupervised single-cell clustering for many public datasets. It also predicts gene expression, identifies enriched motifs, discovers super-enhancers, and projects pseudotime trajectories. APEC is available at https://github.com/QuKunLab/APEC.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:21 |
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| Enthalten in: |
Genome biology - 21(2020), 1 vom: 12. Mai, Seite 116 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Li, Bin [VerfasserIn] |
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| Links: |
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| Themen: |
Accesson |
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| Anmerkungen: |
Date Completed 01.04.2021 Date Revised 01.04.2021 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1186/s13059-020-02034-y |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM309811015 |
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| 520 | |a 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 cell by groups of accessible regions with synergistic signal patterns termed "accessons". This python-based package greatly improves the accuracy of unsupervised single-cell clustering for many public datasets. It also predicts gene expression, identifies enriched motifs, discovers super-enhancers, and projects pseudotime trajectories. APEC is available at https://github.com/QuKunLab/APEC | ||
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| 700 | 1 | |a Li, Kun |e verfasserin |4 aut | |
| 700 | 1 | |a Zhu, Lianbang |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Qiaoni |e verfasserin |4 aut | |
| 700 | 1 | |a Cai, Pengfei |e verfasserin |4 aut | |
| 700 | 1 | |a Fang, Jingwen |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Wen |e verfasserin |4 aut | |
| 700 | 1 | |a Du, Pengcheng |e verfasserin |4 aut | |
| 700 | 1 | |a Jiang, Chen |e verfasserin |4 aut | |
| 700 | 1 | |a Lin, Jun |e verfasserin |4 aut | |
| 700 | 1 | |a Qu, Kun |e verfasserin |4 aut | |
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