RT Journal Article
SR Electronic
T1 A cross-package Bioconductor workflow for analysing methylation array data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 055087
DO 10.1101/055087
A1 Jovana Maksimovic
A1 Belinda Phipson
A1 Alicia Oshlack
YR 2016
UL http://biorxiv.org/content/early/2016/05/25/055087.abstract
AB Methylation in the human genome is known to be associated with development and disease. The Illumina Infinium methylation arrays are by far the most common way to interrogate methylation across the human genome. This paper provides a Bioconductor workflow using multiple packages for the analysis of methylation array data. Specifically, we demonstrate the steps involved in a typical differential methylation analysis pipeline including: quality control, filtering, normalization, data exploration and statistical testing for probe-wise differential methylation. We further outline other analyses such as differential methylation of regions, differential variability analysis, estimating cell type composition and gene ontology testing. Finally, we provide some examples of how to visualise methylation array data.