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Abstract DNA methylation microarrays are popular for epigenome-wide association studies, but spurious outlier values complicate downstream analysis. It was demonstrated previously that commonly used detection p-value cut-offs were insufficient and led to many calls on the Y-chromosome probes in females. We extend these observations by assessing 2,578 samples from 18 studies run on the 450K chip as well as outliers across technical replicates. We provide comprehensive guidance and software for filtering methylation microarrays as an essential step to reduce outliers.
DNA methylation, microarray analysis, outlier detection, data cleaning, EWAS
DNA methylation, microarray analysis, outlier detection, data cleaning, EWAS
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