Ontology highlight
ABSTRACT: Background
We use an approach based on Factor Analysis to analyze datasets generated for transcriptional profiling. The method groups samples into biologically relevant categories, and enables the identification of genes and pathways most significantly associated to each phenotypic group, while allowing for the participation of a given gene in more than one cluster. Genes assigned to each cluster are used for the detection of pathways predominantly activated in that cluster by finding statistically significant associated GO terms. We tested the approach with a published dataset of microarray experiments in yeast. Upon validation with the yeast dataset, we applied the technique to a prostate cancer dataset.Results
Two major pathways are shown to be activated in organ-confine
SUBMITTER: Lozano JJ
PROVIDER: S-EPMC1239914 | biostudies-literature | 2005 Aug
REPOSITORIES: biostudies-literature