Identifying mislabeled and contaminated DNA methylation microarray data: an extended quality control toolset with examples from GEO.

ABSTRACT:

Background

Mislabeled, contaminated or poorly performing samples can threaten power in methylation microarray analyses or even result in spurious associations. We describe a set of quality checks for the popular Illumina 450K and EPIC microarrays to identify problematic samples and demonstrate their application in publicly available datasets.

Methods

Quality checks implemented here include 17 control metrics defined by the manufacturer, a sex check to detect mislabeled sex-discordant samples, and both an identity check for fingerprinting sample donors and a measure of sample contamination based on probes querying high-frequency SNPs. These checks were tested on 80 datasets comprising 8327 samples run on the 450K microarray from the GEO repository.

Results

Nine hundred

SUBMITTER: Heiss JA 

PROVIDER: S-EPMC5984806 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature