Positional effects revealed in Illumina methylation array and the impact on analysis

Epigenomics
Chuan JiaoChunyu Liu

Abstract

We aimed to prove the existence of positional effects in the Illumina methylation beadchip data and to find an optimal correction method. Three HumanMethylation450, three HumanMethylation27 datasets and two EPIC datasets were analyzed. ComBat, linear regression, functional normalization and single-sample Noob were used for minimizing positional effects. The corrected results were evaluated by four methods. We detected 52,988 CpG loci significantly associated with sample positions, 112 remained after ComBat correction in the primary dataset. The pre- and postcorrection comparisons indicate the positional effects could alter the measured methylation values and downstream analysis results. Positional effects exist in the Illumina methylation array and may bias the analyses. Using ComBat to correct positional effects is recommended.

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Citations

Oct 13, 2020·Nucleic Acids Research·Jiayi YinFeng Zhu
Sep 13, 2020·Acta Neuropathologica·Luke C DabinEmmanuelle Viré
Jan 21, 2021·Aging·Priyadarshini KachrooDawn L DeMeo
May 2, 2021·Genome Biology·Sergio Villicaña, Jordana T Bell
Sep 28, 2021·Epigenetics : Official Journal of the DNA Methylation Society·Amena KeshawarzGeorge O'Connor

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Datasets Mentioned

BETA
GSE58885
GSE74193
GSE38873
GSE93373
GSE26133
GSE86831

Methods Mentioned

BETA
chip
Methyl450

Software Mentioned

PVCA
BEclear
R package
minfi
ComBat
RUVm
impute
BrainCloud
R package sva
FN

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