A new statistical approach to detecting differentially methylated loci for case control Illumina array methylation data.

Abstract

As an epigenetic alteration, DNA methylation plays an important role in epigenetic controls of gene transcription. Recent advances in genome-wide scan of DNA methylation provide great opportunities in studying the impact of DNA methylation on many human diseases including various types of cancer. Due to the unique feature of this type of data, applicable statistical methods are limited and new sophisticated approaches are desirable. In this article, we propose a new statistical test to detect differentially methylated loci for case control methylation data generated by Illumina arrays. This new method utilizes the important finding that DNA methylation is highly correlated with age. The proposed method estimates the overall P-value by combining the P-values from independent individual tests each for one age group. Through real data application and simulation study, we show that the proposed test is robust and usually more powerful than other methods.