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Web-based Gene Pathogenicity Analysis (WGPA): a web platform to interpret gene pathogenicity from personal genome data

Title: Web-based Gene Pathogenicity Analysis (WGPA): a web platform to interpret gene pathogenicity from personal genome data
Authors: Diaz-Montana, JJ
Rackham, OJ
Diaz-Diaz, N
Petretto, E
Item Type: Journal Article
Abstract: UNLABELLED: As the volume of patient-specific genome sequences increases the focus of biomedical research is switching from the detection of disease-mutations to their interpretation. To this end a number of techniques have been developed that use mutation data collected within a population to predict whether individual genes are likely to be disease-causing or not. As both sequence data and associated analysis tools proliferate, it becomes increasingly difficult for the community to make sense of these data and their implications. Moreover, no single analysis tool is likely to capture all relevant genomic features that contribute to the gene's pathogenicity. Here, we introduce Web-based Gene Pathogenicity Analysis (WGPA), a web-based tool to analyze genes impacted by mutations and rank them through the integration of existing prioritization tools, which assess different aspects of gene pathogenicity using population-level sequence data. Additionally, to explore the polygenic contribution of mutations to disease, WGPA implements gene set enrichment analysis to prioritize disease-causing genes and gene interaction networks, therefore providing a comprehensive annotation of personal genomes data in disease. AVAILABILITY AND IMPLEMENTATION: wgpa.systems-genetics.net.
Issue Date: 21-Oct-2015
Date of Acceptance: 9-Oct-2015
URI: http://hdl.handle.net/10044/1/39467
DOI: http://dx.doi.org/10.1093/bioinformatics/btv598
ISSN: 1367-4803
Publisher: Oxford University Press
Start Page: 635
End Page: 637
Journal / Book Title: Bioinformatics
Volume: 32
Issue: 4
Copyright Statement: © The Author 2015. 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.
Keywords: Bioinformatics
01 Mathematical Sciences
06 Biological Sciences
08 Information And Computing Sciences
Publication Status: Published
Appears in Collections:Clinical Sciences
Molecular Sciences
Faculty of Medicine



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