Regression modeling to assess association between gene expression data and clinical measures
Jeremy Taylor
University of Michigan
Biostatistics
In this talk I will present the methods of analysis we are using and investigating to analyze oligonucleotide (Affymetrix) gene expression data in a lung cancer study. The goal is to identify "interesting" sets of genes based on their association with stage of disease, patient survival time and histology of the tumor. P-value plots and penalised likelihood approaches will be described.