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SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data

BACKGROUND: Censored data are increasingly common in many microarray studies that attempt to relate gene expression to patient survival. Several new methods have been proposed in the last two years. Most of these methods, however, are not available to biomedical researchers, leading to many re-imple...

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Autor principal: Diaz-Uriarte, Ramon
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2265264/
https://www.ncbi.nlm.nih.gov/pubmed/18208605
http://dx.doi.org/10.1186/1471-2105-9-30
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author Diaz-Uriarte, Ramon
author_facet Diaz-Uriarte, Ramon
author_sort Diaz-Uriarte, Ramon
collection PubMed
description BACKGROUND: Censored data are increasingly common in many microarray studies that attempt to relate gene expression to patient survival. Several new methods have been proposed in the last two years. Most of these methods, however, are not available to biomedical researchers, leading to many re-implementations from scratch of ad-hoc, and suboptimal, approaches with survival data. RESULTS: We have developed SignS (Signatures for Survival data), an open-source, freely-available, web-based tool and R package for gene selection, building molecular signatures, and prediction with survival data. SignS implements four methods which, according to existing reviews, perform well and, by being of a very different nature, offer complementary approaches. We use parallel computing via MPI, leading to large decreases in user waiting time. Cross-validation is used to asses predictive performance and stability of solutions, the latter an issue of increasing concern given that there are often several solutions with similar predictive performance. Biological interpretation of results is enhanced because genes and signatures in models can be sent to other freely-available on-line tools for examination of PubMed references, GO terms, and KEGG and Reactome pathways of selected genes. CONCLUSION: SignS is the first web-based tool for survival analysis of expression data, and one of the very few with biomedical researchers as target users. SignS is also one of the few bioinformatics web-based applications to extensively use parallelization, including fault tolerance and crash recovery. Because of its combination of methods implemented, usage of parallel computing, code availability, and links to additional data bases, SignS is a unique tool, and will be of immediate relevance to biomedical researchers, biostatisticians and bioinformaticians.
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spelling pubmed-22652642008-03-07 SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data Diaz-Uriarte, Ramon BMC Bioinformatics Software BACKGROUND: Censored data are increasingly common in many microarray studies that attempt to relate gene expression to patient survival. Several new methods have been proposed in the last two years. Most of these methods, however, are not available to biomedical researchers, leading to many re-implementations from scratch of ad-hoc, and suboptimal, approaches with survival data. RESULTS: We have developed SignS (Signatures for Survival data), an open-source, freely-available, web-based tool and R package for gene selection, building molecular signatures, and prediction with survival data. SignS implements four methods which, according to existing reviews, perform well and, by being of a very different nature, offer complementary approaches. We use parallel computing via MPI, leading to large decreases in user waiting time. Cross-validation is used to asses predictive performance and stability of solutions, the latter an issue of increasing concern given that there are often several solutions with similar predictive performance. Biological interpretation of results is enhanced because genes and signatures in models can be sent to other freely-available on-line tools for examination of PubMed references, GO terms, and KEGG and Reactome pathways of selected genes. CONCLUSION: SignS is the first web-based tool for survival analysis of expression data, and one of the very few with biomedical researchers as target users. SignS is also one of the few bioinformatics web-based applications to extensively use parallelization, including fault tolerance and crash recovery. Because of its combination of methods implemented, usage of parallel computing, code availability, and links to additional data bases, SignS is a unique tool, and will be of immediate relevance to biomedical researchers, biostatisticians and bioinformaticians. BioMed Central 2008-01-21 /pmc/articles/PMC2265264/ /pubmed/18208605 http://dx.doi.org/10.1186/1471-2105-9-30 Text en Copyright © 2008 Diaz-Uriarte; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Diaz-Uriarte, Ramon
SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data
title SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data
title_full SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data
title_fullStr SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data
title_full_unstemmed SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data
title_short SignS: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data
title_sort signs: a parallelized, open-source, freely available, web-based tool for gene selection and molecular signatures for survival and censored data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2265264/
https://www.ncbi.nlm.nih.gov/pubmed/18208605
http://dx.doi.org/10.1186/1471-2105-9-30
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