Abstract
BackgroundAs public microarray repositories are constantly growing, we are facing the challenge of designing strategies to provide productive access to the available data.MethodologyWe used a modified version of the Markov clustering algorithm to systematically extract clusters of co-regulated genes from hundreds of microarray datasets stored in the Gene Expression Omnibus database (n = 1,484). This approach led to the definition of 18,250 transcriptional signatures (TS) that were tested for functional enrichment using the DAVID knowledgebase. Over-representation of functional terms was found in a large proportion of these TS (84%). We developed a JAVA application, TBrowser that comes with an open plug-in architecture and whose interface implements a highly sophisticated search engine supporting several Boolean operators (http://tagc.univ-mrs.fr/tbrowser/). User can search and analyze TS containing a list of identifiers (gene symbols or AffyIDs) or associated with a set of functional terms.Conclusions/SignificanceAs proof of principle, TBrowser was used to define breast cancer cell specific genes and to detect chromosomal abnormalities in tumors. Finally, taking advantage of our large collection of transcriptional signatures, we constructed a comprehensive map that summarizes gene-gene co-regulations observed through all the experiments performed on HGU133A Affymetrix platform. We provide evidences that this map can extend our knowledge of cellular signaling pathways.
Highlights
Microarray technology provides biologists with a powerful approach for comprehensive analyzes of cells or tissues at the transcriptional level
We present the construction of a unique collection of transcriptional signatures (TS) that summarize almost all human, mouse and rat Affymetrix microarray data stored in the Gene Expression Omnibus repository (GEO) database
It is well suited to compare results obtained through microarray, ChIP-on-chip, ChIP-seq, CGH or protein-protein interaction experiments to those previously stored in the GEO database
Summary
Microarray technology provides biologists with a powerful approach for comprehensive analyzes of cells or tissues at the transcriptional level. DNA chips are widely used to assess the expression levels from all genes of a given organism These data, most generally deposited in MIAME-compliant public databases, constitute an unprecedented source of knowledge for biologists [1]. Until now, the Gene Expression Omnibus repository (GEO) host approximately 8,000 experiments encompassing about 200,000 biological samples analyzed using various high through-put technologies [2]. This represents billions of measurements that reflect the biological states of cells or tissues recorded in physiological or pathological conditions or in response to various chemical compounds and/or natural molecules. As public microarray repositories are constantly growing, we are facing the challenge of designing strategies to provide productive access to the available data
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