Gene set analysis for longitudinal gene expression data.

ABSTRACT:

Background

Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. GSA performs statistical tests for independent microarray samples at the level of gene sets rather than individual genes. Nowadays, an increasing number of microarray studies are conducted to explore the dynamic changes of gene expression in a variety of species and biological scenarios. In these longitudinal studies, gene expression is repeatedly measured over time such that a GSA needs to take into account the within-gene correlations in addition to possible between-gene correlations.

Results

We provide a robust nonparametric approach to compare the expressions of longitudinally measured sets of ge

SUBMITTER: Zhang K 

PROVIDER: S-EPMC3142525 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature