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Nucleic Acids Res
2007 Jul 01;35Web Server issue:W75-80. doi: 10.1093/nar/gkm229.
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Asterias: integrated analysis of expression and aCGH data using an open-source, web-based, parallelized software suite.
Díaz-Uriarte R
,
Alibés A
,
Morrissey ER
,
Cañada A
,
Rueda OM
,
Neves ML
.
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Asterias (http://www.asterias.info) is an open-source, web-based, suite for the analysis of gene expression and aCGH data. Asterias implements validated statistical methods, and most of the applications use parallel computing, which permits taking advantage of multicore CPUs and computing clusters. Access to, and further analysis of, additional biological information and annotations (PubMed references, Gene Ontology terms, KEGG and Reactome pathways) are available either for individual genes (from clickable links in tables and figures) or sets of genes. These applications cover from array normalization to imputation and preprocessing, differential gene expression analysis, class and survival prediction and aCGH analysis. The source code is available, allowing for extention and reuse of the software. The links and analysis of additional functional information, parallelization of computation and open-source availability of the code make Asterias a unique suite that can exploit features specific to web-based environments.
Figure 1. Asterias: functionality and data and information flow between sets of applications (see details in Figure 2). References for ADaCGH methods are: circular binary segmentation (21), wavelet-based smoothing (22), SW-ARRAY (23) and ACE (24). The method implemented in SignS is from (25).
Figure 2. Asterias: input/output and data and information flow between applications. Black and blue arrows involve files, green arrows URLs. Olive boxes denote graphical output.
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