| Literature DB >> 27018579 |
Elior Rahmani1, Noah Zaitlen2, Yael Baran1, Celeste Eng2, Donglei Hu2, Joshua Galanter2,3, Sam Oh2, Esteban G Burchard2,3, Eleazar Eskin4,5, James Zou6, Eran Halperin1,7,8.
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.Entities:
Mesh:
Year: 2016 PMID: 27018579 PMCID: PMC5548182 DOI: 10.1038/nmeth.3809
Source DB: PubMed Journal: Nat Methods ISSN: 1548-7091 Impact factor: 28.547