Detecting differentially methylated loci for Illumina Array methylation data based on human ovarian cancer data.

ABSTRACT:

Background

It is well known that DNA methylation, as an epigenetic factor, has an important effect on gene expression and disease development. Detecting differentially methylated loci under different conditions, such as cancer types or treatments, is of great interest in current research as it is important in cancer diagnosis and classification. However, inappropriate testing approaches can result in large false positives and/or false negatives. Appropriate and powerful statistical methods are desirable but very limited in the literature.

Results

In this paper, we propose a nonparametric method to detect differentially methylated loci under multiple conditions for Illumina Array Methylation data. We compare the new method with other methods using simulated and real data. Our

SUBMITTER: Chen Z 

PROVIDER: S-EPMC3552689 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature