An efficient and robust statistical modeling approach to discover differentially expressed genes using genomic expression profiles.

ABSTRACT: We have developed a statistical regression modeling approach to discover genes that are differentially expressed between two predefined sample groups in DNA microarray experiments. Our model is based on well-defined assumptions, uses rigorous and well-characterized statistical measures, and accounts for the heterogeneity and genomic complexity of the data. In contrast to cluster analysis, which attempts to define groups of genes and/or samples that share common overall expression profiles, our modeling approach uses known sample group membership to focus on expression profiles of individual genes in a sensitive and robust manner. Further, this approach can be used to test statistical hypotheses about gene expression. To demonstrate this methodology, we compared the expression profiles of 1

SUBMITTER: Thomas JG 

PROVIDER: S-EPMC311075 | biostudies-literature | 2001 Jul

REPOSITORIES: biostudies-literature