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Nat Methods. 2017 Oct;14(10):975-978. doi: 10.1038/nmeth.4401. Epub 2017 Aug 21.

chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data.

Author information

1
Department of Genetics, Stanford University School of Medicine, Stanford, California, USA.
2
Center for Personal Dynamic Regulomes, Stanford University, Stanford, California, USA.
3
Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
4
Harvard Society of Fellows, Harvard University, Cambridge, Massachusetts, USA.
5
Department of Applied Physics, Stanford University, Stanford, California, USA.
6
Chan Zuckerberg Biohub, San Francisco, California, USA.

Abstract

Single-cell ATAC-seq (scATAC) yields sparse data that make conventional analysis challenging. We developed chromVAR (http://www.github.com/GreenleafLab/chromVAR), an R package for analyzing sparse chromatin-accessibility data by estimating gain or loss of accessibility within peaks sharing the same motif or annotation while controlling for technical biases. chromVAR enables accurate clustering of scATAC-seq profiles and characterization of known and de novo sequence motifs associated with variation in chromatin accessibility.

PMID:
28825706
PMCID:
PMC5623146
DOI:
10.1038/nmeth.4401
[Indexed for MEDLINE]
Free PMC Article

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