ADaCGH: A parallelized web-based application and R package for the analysis of aCGH data
Entity
UAM. Departamento de BioquímicaPublisher
Public Library of ScienceDate
2007-08-15Citation
10.1371/journal.pone.0000737
Plos One 2.8 (2007): e737
ISSN
1932-6203DOI
10.1371/journal.pone.0000737Funded by
Funding provided by Fundacion de Investigacion Medica Mutua Madrilena and Project TIC2003-09331-C02-02 of the Spanish Ministry of Education and Science (MEC)Project
Gobierno de España. TIC2003-09331-C02-02Editor's Version
http://dx.doi.org/10.1371/journal.pone.0000737Subjects
Comparative Genomic Hybridization; Computational Biology; Software; Biología y Biomedicina / BiologíaRights
© 2007 Diaz-Uriarte, RuedaAbstract
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 456); 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
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Google Scholar:Díaz Uriarte, Ramón
-
Rueda, Oscar M.
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