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

AIM: We aimed to prove the existence of positional effects in the Illumina methylation beadchip data and to find an optimal correction method.

MATERIALS & METHODS: 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.

RESULTS: 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.

CONCLUSION: Positional effects exist in the Illumina methylation array and may bias the analyses. Using ComBat to correct positional effects is recommended.