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EpiScanpy: Integrated single-cell epigenomic analysis.

Nat. Commun. 12:5228 (2021)
Publ. Version/Full Text DOI
Open Access Gold
Creative Commons Lizenzvertrag
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.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Accessibility
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Quellenangaben Volume: 12, Issue: 1, Pages: , Article Number: 5228 Supplement: ,
Publisher Nature Publishing Group
Publishing Place London
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Helmholtz Pioneer Campus (HPC)
Grants Joachim Herz Stiftung
German research foundation (DFG) fellowship through the Graduate School of Quantitative Biosciences Munich (QBM)
Incubator grant sparse2big
Federal Ministry of Education and Research (Single Cell Genomics Network Germany)
Graduate School QBM)
German Science Foundation
Impulsund Vernetzungsfonds of the Helmholtz-Gemeinschaft