AN INTEGRATIVE ANALYSIS OF CANCER GENE EXPRESSION STUDIES USING BAYESIAN LATENT FACTOR MODELING.

ABSTRACT: We present an applied study in cancer genomics for integrating data and inferences from laboratory experiments on cancer cell lines with observational data obtained from human breast cancer studies. The biological focus is on improving understanding of transcriptional responses of tumors to changes in the pH level of the cellular microenvironment. The statistical focus is on connecting experimentally defined biomarkers of such responses to clinical outcome in observational studies of breast cancer patients. Our analysis exemplifies a general strategy for accomplishing this kind of integration across contexts. The statistical methodologies employed here draw heavily on Bayesian sparse factor models for identifying, modularizing and correlating with clinical outcome these signatures of aggre

SUBMITTER: Merl D 

PROVIDER: S-EPMC2954437 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature