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

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


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

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Computer Simulation
  • CpG Islands / genetics
  • DNA Methylation / genetics*
  • Epigenomics / methods*
  • Epigenomics / statistics & numerical data
  • Genetic Heterogeneity*
  • Genome-Wide Association Study / methods*
  • Genome-Wide Association Study / statistics & numerical data
  • Humans
  • Leukocytes / cytology
  • Leukocytes / metabolism
  • Principal Component Analysis*