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.