Biomarker detection in the integration of multiple multi-class genomic studies.

ABSTRACT:

Motivation

Systematic information integration of multiple-related microarray studies has become an important issue as the technology becomes mature and prevalent in the past decade. The aggregated information provides more robust and accurate biomarker detection. So far, published meta-analysis methods for this purpose mostly consider two-class comparison. Methods for combining multi-class studies and considering expression pattern concordance are rarely explored.

Results

In this article, we develop three integration methods for biomarker detection in multiple multi-class microarray studies: ANOVA-maxP, min-MCC and OW-min-MCC. We first consider a natural extension of combining P-values from the traditional ANOVA model. Since P-values from ANOVA do not guarantee to reflect th

SUBMITTER: Lu S 

PROVIDER: S-EPMC2815659 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature