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Updated: Nov 30, 2025

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
MGMIN: A Normalization Method for Correcting Probe Design Bias in Illumina Infinium HumanMethylation450 BeadChips
Zhenxing Wang1, Yongzhuang Liu1, Yadong Wang1
1School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.
Abstract:
The Illumina Infinium HumanMethylation450 Beadchips have been widely utilized in epigenome-wide association studies (EWAS). However, the existing two types of probes (type I and type II), with the distribution of measurements of probes and dynamic range different, may bias downstream analyses. Here, we propose a method, MGMIN (M-values Gaussian-MIxture Normalization), to correct the probe designs based on M-values of DNA methylation. Our strategy includes fitting Gaussian mixture distributions to type I and type II probes separately, a transformation of M-values into quantiles and finally a dilation transformation based on M-values of DNA methylation to maintain the continuity of the data. Our method is validated on several public datasets on reducing probe design bias, reducing the technical variation and improving the ability to find biologically differential methylation signals. The results show that MGMIN achieves competitive performances compared to BMIQ which is a well-known normalization method on β-values of DNA methylation.

