GMQN: A Reference-Based Method for Correcting Batch Effects and Probe Bias in HumanMethylation BeadChip - Xiong, Zhuang; Li, Mengwei; Ma, Yingke; Li, Rujiao; Bao, Yiming (Frontiers in Genetics, 2022)
Illumina HumanMethylation BeadChip is one of the most cost-effective ways to quantify DNA methylation levels at the single-base level across the human genome, which makes it a routine platform for epigenome-wide association studies. It has accumulated tens of thousands of DNA methylation array samples in public databases, providing great support for data integration and further analysis. However, majority of public DNA methylation data are deposited as processed data without background probes which are widely used in data normalization. Here we present Gaussian mixture quantile normalization (GMQN), a reference based method for correcting batch effects as well as probe bias in HumanMethylation BeadChip. Availability and implementation: https://github.com/MengweiLi-project/gmqn.