RT Journal Article
SR Electronic
T1 Removing unwanted variation in a differential methylation analysis of Illumina HumanMethylation450 array data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 019042
DO 10.1101/019042
A1 Jovana Maksimovic
A1 Johann A. Gagnon-Bartsch
A1 Terence P. Speed
A1 Alicia Oshlack
YR 2015
UL http://biorxiv.org/content/early/2015/05/07/019042.abstract
AB Due to their relatively low-cost per sample and broad, gene-centric coverage of CpGs across the human genome, Illumina’s 450k arrays are widely used in large scale differential methylation studies. However, by their very nature, large studies are particularly susceptible to the effects of unwanted variation. The effects of unwanted variation have been extensively documented in gene expression array studies and numerous methods have been developed to mitigate these effects. However, there has been much less research focused on the appropriate methodology to use for accounting for unwanted variation in methylation array studies. Here we present a novel 2-stage approach using RUV-inverse in a differential methylation analysis of 450k data and show that it outperforms existing methods.