Comparison of different cell type correction methods for genome-scale epigenetics studies.

ABSTRACT:

Background

Whole blood is frequently utilized in genome-wide association studies of DNA methylation patterns in relation to environmental exposures or clinical outcomes. These associations can be confounded by cellular heterogeneity. Algorithms have been developed to measure or adjust for this heterogeneity, and some have been compared in the literature. However, with new methods available, it is unknown whether the findings will be consistent, if not which method(s) perform better.

Results

Methods: We compared eight cell-type correction methods including the method in the minfi R package, the method by Houseman et al., the Removing unwanted variation (RUV) approach, the methods in FaST-LMM-EWASher, ReFACTor, RefFreeEWAS, and RefFreeCellMix R programs, along with one approac

SUBMITTER: Kaushal A 

PROVIDER: S-EPMC5391562 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature