EpiScanpy: integrated single-cell epigenomic analysis.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
01 09 2021
01 09 2021
Historique:
received:
30
08
2020
accepted:
22
07
2021
entrez:
2
9
2021
pubmed:
3
9
2021
medline:
21
9
2021
Statut:
epublish
Résumé
EpiScanpy is a toolkit for the analysis of single-cell epigenomic data, namely single-cell DNA methylation and single-cell ATAC-seq data. To address the modality specific challenges from epigenomics data, epiScanpy quantifies the epigenome using multiple feature space constructions and builds a nearest neighbour graph using epigenomic distance between cells. EpiScanpy makes the many existing scRNA-seq workflows from scanpy available to large-scale single-cell data from other -omics modalities, including methods for common clustering, dimension reduction, cell type identification and trajectory learning techniques, as well as an atlas integration tool for scATAC-seq datasets. The toolkit also features numerous useful downstream functions, such as differential methylation and differential openness calling, mapping epigenomic features of interest to their nearest gene, or constructing gene activity matrices using chromatin openness. We successfully benchmark epiScanpy against other scATAC-seq analysis tools and show its outperformance at discriminating cell types.
Identifiants
pubmed: 34471111
doi: 10.1038/s41467-021-25131-3
pii: 10.1038/s41467-021-25131-3
pmc: PMC8410937
doi:
Substances chimiques
Chromatin
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
5228Informations de copyright
© 2021. The Author(s).
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