ReFACTor: Reference-Free Adjustment for Cell-Type composition



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.






An updated implementation of ReFACTor is now available in GLINT, a user-friendly command-line tool for fast analysis of genome-wide DNA methylation data.


ReFACTor is also available in standalone implementations in both R and Python. These can be downloaded here via github.







A complete documentation of ReFACTor can be found in ReFACTor's main github page or can be downloaded here.



Citing ReFACTor



If you use ReFACTor in any published work, please cite the manuscript describing the method:


Elior Rahmani, Noah Zaitlen, Yael Baran, Celeste Eng, Donglei Hu, Joshua Galanter, Sam Oh, Esteban G Burchard, Eleazar Eskin, James Zou and Eran Halperin. "Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies". Nature Methods (2016).






This software was developed by Reut Yedidim, Noah Zaitlen and Elior Rahmani.


For any question and for reporting bugs please send an email to Elior Rahmani at: