Content-based microarray search using differential expression profiles

Background: With the expansion of public repositories such as the Gene Expression Omnibus (GEO), we are rapidly cataloging cellular transcriptional responses to diverse experimental conditions. Methods that query these repositories based on gene expression content, rather than textual annotations, may enable more effective experiment retrieval as well as the discovery of novel associations between drugs, diseases, and other perturbations. Results: We develop methods to retrieve gene expression experiments that differentially express the same transcriptional programs as a query experiment. Avoiding thresholds, we generate differential expression profiles that include a score for each gene measured in an experiment. We use existing and novel dimension reduction and correlation measures to rank relevant experiments in an entirely data-driven manner, allowing emergent features of the data to drive the results. A combination of matrix decomposition and p-weighted Pearson correlation proves...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Jesse M. Engreitz, Alexander A. Morgan, Joel Dudley, Rong Chen, Rahul Thathoo, Russ B. Altman, Atul J. Butte
• Keywords: BMCBI 2010, Business, Expression Profiles, Gene Expression, Gene Expression Omnibus