Penalized logistic regression for high-dimensional DNA methylation data with case-control studies.

ABSTRACT:

Motivation

DNA methylation is a molecular modification of DNA that plays crucial roles in regulation of gene expression. Particularly, CpG rich regions are frequently hypermethylated in cancer tissues, but not methylated in normal tissues. However, there are not many methodological literatures of case-control association studies for high-dimensional DNA methylation data, compared with those of microarray gene expression. One key feature of DNA methylation data is a grouped structure among CpG sites from a gene that are possibly highly correlated. In this article, we proposed a penalized logistic regression model for correlated DNA methylation CpG sites within genes from high-dimensional array data. Our regularization procedure is based on a combination of the l(1) penalty and squar

SUBMITTER: Sun H 

PROVIDER: S-EPMC3348559 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature