Quantifying stability in gene list ranking across microarray derived clinical biomarkers.

ABSTRACT:

Background

Identifying stable gene lists for diagnosis, prognosis prediction, and treatment guidance of tumors remains a major challenge in cancer research. Microarrays measuring differential gene expression are widely used and should be versatile predictors of disease and other phenotypic data. However, gene expression profile studies and predictive biomarkers are often of low power, requiring numerous samples for a sound statistic, or vary between studies. Given the inconsistency of results across similar studies, methods that identify robust biomarkers from microarray data are needed to relay true biological information. Here we present a method to demonstrate that gene list stability and predictive power depends not only on the size of studies, but also on the clinical phenotyp

SUBMITTER: Schneckener S 

PROVIDER: S-EPMC3206838 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature