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Detalle de: ADaCGH: A Parallelized Web-Based Application and R Package for the Analysis of aCGH Data

Title ADaCGH: A Parallelized Web-Based Application and R Package for the Analysis of aCGH Data
Abstract

Background Copy number alterations (CNAs) in genomic DNA have been associated with complex human diseases, including cancer. One of the most common techniques to detect CNAs is array-based comparative genomic hybridization (aCGH). The availability of aCGH platforms and the need for identification of CNAs has resulted in a wealth of methodological studies. Methodology/principal findings ADaCGH is an R package and a web-based application for the analysis of aCGH data. It implements eight methods for detection of CNAs, gains and losses of genomic DNA, including all of the best performing ones from two recent reviews (CBS, GLAD, CGHseg, HMM). For improved speed, we use parallel computing (via MPI). Additional information (GO terms, PubMed citations, KEGG and Reactome pathways) is available for individual genes, and for sets of genes with altered copy numbers. Conclusions/significance ADACGH represents a qualitative increase in the standards of these types of applications: a) all of the best performing algorithms are included, not just one or two; b) we do not limit ourselves to providing a thin layer of CGI on top of existing BioConductor packages, but instead carefully use parallelization, examining different schemes, and are able to achieve significant decreases in user waiting time (factors up to 45x); c) we have added functionality not currently available in some methods, to adapt to recent recommendations (e.g., merging of segmentation results in wavelet-based and CGHseg algorithms); d) we incorporate redundancy, fault-tolerance and checkpointing, which are unique among web-based, parallelized applications; e) all of the code is available under open source licenses, allowing to build upon, copy, and adapt our code for other software projects.

Apa Reference Díaz-Uriarte, R., & Rueda, O. M. (2007). ADaCGH: A Parallelized Web-Based Application and R Package for the Analysis of aCGH Data. PLoS ONE, 2(8), e737. 10.1371/journal.pone.0000737
Doi 10.1371/journal.pone.0000737
Publication Date 15 Aug 2007
Publication Type Article
Researcher Ramon Díaz Uriarte
Ontology Bioinformatics Software and Tools, Analysis packages (R, Python, etc.), Genomics, Functional annotation, Parallel Computing, Pathway analysis, Comparative Genomics
Research Groups Bioinformatics and Computational Biology in Cancer Evolution
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