Web-based Gene Pathogenicity Analysis (WGPA): a web platform to interpret gene pathogenicity from personal genome data
Author(s)
Diaz-Montana, JJ
Rackham, OJ
Diaz-Diaz, N
Petretto, E
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.
Date Issued
2015-10-21
Date Acceptance
2015-10-09
Citation
Bioinformatics, 2015, 32 (4), pp.635-637
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.
License URL
Subjects
Bioinformatics
01 Mathematical Sciences
06 Biological Sciences
08 Information And Computing Sciences
Publication Status
Published