Unsupervised clustering and epigenetic classification of single cells

Mahdi Zamanighomi; Zhixiang Lin; Timothy Daley; Xi Chen; Zhana Duren; Alicia Schep; William J Greenleaf; Wing Hung Wong

doi:10.1038/s41467-018-04629-3

Unsupervised clustering and epigenetic classification of single cells

Nat Commun. 2018 Jun 20;9(1):2410. doi: 10.1038/s41467-018-04629-3.

Authors

Mahdi Zamanighomi¹, Zhixiang Lin¹, Timothy Daley^{1

2}, Xi Chen^{1

3}, Zhana Duren¹, Alicia Schep^{4

5}, William J Greenleaf^{4

5

6}, Wing Hung Wong^{7

8}

Affiliations

¹ Department of Statistics, Stanford University, Stanford, CA, 94305, USA.
² Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
³ Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA.
⁴ Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA.
⁵ Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, 94305, USA.
⁶ Department of Applied Physics, Stanford University, Stanford, CA, 94305, USA.
⁷ Department of Statistics, Stanford University, Stanford, CA, 94305, USA. whwong@stanford.edu.
⁸ Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA. whwong@stanford.edu.

Abstract

Characterizing epigenetic heterogeneity at the cellular level is a critical problem in the modern genomics era. Assays such as single cell ATAC-seq (scATAC-seq) offer an opportunity to interrogate cellular level epigenetic heterogeneity through patterns of variability in open chromatin. However, these assays exhibit technical variability that complicates clear classification and cell type identification in heterogeneous populations. We present scABC, an R package for the unsupervised clustering of single-cell epigenetic data, to classify scATAC-seq data and discover regions of open chromatin specific to cell identity.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Algorithms
Animals
Cell Line
Chromatin / genetics
Cluster Analysis
Epigenomics / methods*
Mice
Models, Statistical*
Mouse Embryonic Stem Cells
Sequence Analysis, DNA / methods
Single-Cell Analysis / methods*
Software

Substances

Chromatin

Abstract

Publication types

MeSH terms

Substances

Grants and funding