Identification of a small optimal subset of CpG sites as bio-markers from high-throughput DNA methylation profiles.

ABSTRACT:

Background

DNA methylation patterns have been shown to significantly correlate with different tissue types and disease states. High-throughput methylation arrays enable large-scale DNA methylation analysis to identify informative DNA methylation biomarkers. The identification of disease-specific methylation signatures is of fundamental and practical interest for risk assessment, diagnosis, and prognosis of diseases.

Results

Using published high-throughput DNA methylation data, a two-stage feature selection method was developed to select a small optimal subset of DNA methylation features to precisely classify two sample groups. With this approach, a small number of CpG sites were highly sensitive and specific in distinguishing lung cancer tissue samples from normal lung tissu

SUBMITTER: Meng H 

PROVIDER: S-EPMC2613930 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature