Asterias: A parallelized web-based suite for the analysis of expression and aCGH data
CitationCancer Informatics 3 (2007): 1-9
ISSN1176-9351 (on line)
Funded byFunding provided by Fundación de Investigación Médica Mutua Madrileña and Project TIC2003-09331-C02-02 of the Spanish Ministry of Education and Science (MEC). R.D.- U. is partially supported by the Ramón y Cajal programme of the Spanish MEC. Applications are running on clusters of machines purchased with funds from the RTICCC from the Spanish FIS
ProjectGobierno de España. TIC2003-09331-C02-02
SubjectsMicroarray; aCGH; Classification; Prediction; Parallel computing; Web-based application; Biología y Biomedicina / Biología
The analysis of expression and CGH arrays plays a central role in the study of complex diseases, especially cancer, including fi nding markers for early diagnosis and prognosis, choosing an optimal therapy, or increasing our understanding of cancer development and metastasis. Asterias (http://www.asterias.info) is an integrated collection of freely-accessible web tools for the analysis of gene expression and aCGH data. Most of the tools use parallel computing (via MPI) and run on a server with 60 CPUs for computation; compared to a desktop or server-based but not parallelized application, parallelization provides speed ups of factors up to 50. Most of our applications allow the user to obtain additional information for user-selected genes (chromosomal location, PubMed ids, Gene Ontology terms, etc.) by using clickable links in tables and/or fi gures. Our tools include: normalization of expression and aCGH data (DNMAD); converting between different types of gene/clone and protein identifi ers (IDconverter/IDClight); fi ltering and imputation (preP); fi nding differentially expressed genes related to patient class and survival data (Pomelo II); searching for models of class prediction (Tnasas); using random forests to search for minimal models for class prediction or for large subsets of genes with predictive capacity (GeneSrF); searching for molecular signatures and predictive genes with survival data (SignS); detecting regions of genomic DNA gain or loss (ADaCGH). The capability to send results between different applications, access to additional functional information, and parallelized computation make our suite unique and exploit features only available to web-based applications
Google Scholar:Alibés, Andreu - Morrissey, Edward R. - Cañada, Andrés - Rueda, Oscar M. - Casado, David - Yankilevich, Patricio - Díaz-Uriarte, Ramón
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Asterias: Integrated analysis of expression and aCGH data using an open-source, web-based, parallelized software suite Díaz-Uriarte, Ramón; Alibés, Andreu; Morrissey, Edward R.; Cañada, Andrés; Rueda, Oscar M.; Neves, Mariana L.
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