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Nat Methods. 2016 May;13(5):443-5. doi: 10.1038/nmeth.3809. Epub 2016 Mar 28.

Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies.

Author information

1
Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv, Israel.
2
Department of Medicine, University of California, San Francisco, San Francisco, California, USA.
3
Department of Bioengineering and Therapeutic Science, University of California, San Francisco, San Francisco, California, USA.
4
Department of Computer Science, University of California, Los Angeles, Los Angeles, California, USA.
5
Department of Human Genetics, University of California, Los Angeles, Los Angeles, California, USA.
6
Microsoft Research New England, Cambridge, Massachusetts, USA.
7
International Computer Science Institute, Berkeley, California, USA.
8
The Department of Molecular Microbiology and Biotechnology, Tel-Aviv University, Tel Aviv, Israel.

Abstract

In epigenome-wide association studies (EWAS), different methylation profiles of distinct cell types may lead to false discoveries. We introduce ReFACTor, a method based on principal component analysis (PCA) and designed for the correction of cell type heterogeneity in EWAS. ReFACTor does not require knowledge of cell counts, and it provides improved estimates of cell type composition, resulting in improved power and control for false positives in EWAS. Corresponding software is available at http://www.cs.tau.ac.il/~heran/cozygene/software/refactor.html.

PMID:
27018579
PMCID:
PMC5548182
DOI:
10.1038/nmeth.3809
[Indexed for MEDLINE]
Free PMC Article

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