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Candidate gene prioritization with Endeavour

Genomic studies and high-throughput experiments often produce large lists of candidate genes among which only a small fraction are truly relevant to the disease, phenotype or biological process of interest. Gene prioritization tackles this problem by ranking candidate genes by profiling candidates a...

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Autores principales: Tranchevent, Léon-Charles, Ardeshirdavani, Amin, ElShal, Sarah, Alcaide, Daniel, Aerts, Jan, Auboeuf, Didier, Moreau, Yves
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987917/
https://www.ncbi.nlm.nih.gov/pubmed/27131783
http://dx.doi.org/10.1093/nar/gkw365
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author Tranchevent, Léon-Charles
Ardeshirdavani, Amin
ElShal, Sarah
Alcaide, Daniel
Aerts, Jan
Auboeuf, Didier
Moreau, Yves
author_facet Tranchevent, Léon-Charles
Ardeshirdavani, Amin
ElShal, Sarah
Alcaide, Daniel
Aerts, Jan
Auboeuf, Didier
Moreau, Yves
author_sort Tranchevent, Léon-Charles
collection PubMed
description Genomic studies and high-throughput experiments often produce large lists of candidate genes among which only a small fraction are truly relevant to the disease, phenotype or biological process of interest. Gene prioritization tackles this problem by ranking candidate genes by profiling candidates across multiple genomic data sources and integrating this heterogeneous information into a global ranking. We describe an extended version of our gene prioritization method, Endeavour, now available for six species and integrating 75 data sources. The performance (Area Under the Curve) of Endeavour on cross-validation benchmarks using ‘gold standard’ gene sets varies from 88% (for human phenotypes) to 95% (for worm gene function). In addition, we have also validated our approach using a time-stamped benchmark derived from the Human Phenotype Ontology, which provides a setting close to prospective validation. With this benchmark, using 3854 novel gene–phenotype associations, we observe a performance of 82%. Altogether, our results indicate that this extended version of Endeavour efficiently prioritizes candidate genes. The Endeavour web server is freely available at https://endeavour.esat.kuleuven.be/.
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spelling pubmed-49879172016-08-22 Candidate gene prioritization with Endeavour Tranchevent, Léon-Charles Ardeshirdavani, Amin ElShal, Sarah Alcaide, Daniel Aerts, Jan Auboeuf, Didier Moreau, Yves Nucleic Acids Res Web Server issue Genomic studies and high-throughput experiments often produce large lists of candidate genes among which only a small fraction are truly relevant to the disease, phenotype or biological process of interest. Gene prioritization tackles this problem by ranking candidate genes by profiling candidates across multiple genomic data sources and integrating this heterogeneous information into a global ranking. We describe an extended version of our gene prioritization method, Endeavour, now available for six species and integrating 75 data sources. The performance (Area Under the Curve) of Endeavour on cross-validation benchmarks using ‘gold standard’ gene sets varies from 88% (for human phenotypes) to 95% (for worm gene function). In addition, we have also validated our approach using a time-stamped benchmark derived from the Human Phenotype Ontology, which provides a setting close to prospective validation. With this benchmark, using 3854 novel gene–phenotype associations, we observe a performance of 82%. Altogether, our results indicate that this extended version of Endeavour efficiently prioritizes candidate genes. The Endeavour web server is freely available at https://endeavour.esat.kuleuven.be/. Oxford University Press 2016-07-08 2016-04-30 /pmc/articles/PMC4987917/ /pubmed/27131783 http://dx.doi.org/10.1093/nar/gkw365 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Web Server issue
Tranchevent, Léon-Charles
Ardeshirdavani, Amin
ElShal, Sarah
Alcaide, Daniel
Aerts, Jan
Auboeuf, Didier
Moreau, Yves
Candidate gene prioritization with Endeavour
title Candidate gene prioritization with Endeavour
title_full Candidate gene prioritization with Endeavour
title_fullStr Candidate gene prioritization with Endeavour
title_full_unstemmed Candidate gene prioritization with Endeavour
title_short Candidate gene prioritization with Endeavour
title_sort candidate gene prioritization with endeavour
topic Web Server issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987917/
https://www.ncbi.nlm.nih.gov/pubmed/27131783
http://dx.doi.org/10.1093/nar/gkw365
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