A comparative analysis of cell-type adjustment methods for epigenome-wide association studies based on simulated and real data sets.

ABSTRACT: Technological advances and reduced costs of high-density methylation arrays have led to an increasing number of association studies on the possible relationship between human disease and epigenetic variability. DNA samples from peripheral blood or other tissue types are analyzed in epigenome-wide association studies (EWAS) to detect methylation differences related to a particular phenotype. Since information on the cell-type composition of the sample is generally not available and methylation profiles are cell-type specific, statistical methods have been developed for adjustment of cell-type heterogeneity in EWAS. In this study we systematically compared five popular adjustment methods: the factored spectrally transformed linear mixed model (FaST-LMM-EWASher), the sparse principal componen

SUBMITTER: Bragelmann J 

PROVIDER: S-EPMC6954449 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature