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

Alicia N Schep; Beijing Wu; Jason D Buenrostro; William J Greenleaf

doi:10.1038/nmeth.4401

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

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

Authors

Alicia N Schep^{1

2}, Beijing Wu^{1

2}, Jason D Buenrostro^{3

4}, William J Greenleaf^{1

2

5

6}

Affiliations

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.

MeSH terms

Algorithms
Animals
Cell Line
Epigenomics / methods*
Gene Expression Regulation
Sequence Analysis, DNA / methods*
Software*
Transcription Factors / metabolism*

Substances

Transcription Factors

Abstract

MeSH terms

Substances

Grants and funding