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

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 i...

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Bibliographic Details
Published in:Bioinformatics 2016-02, Vol.32 (4), p.635-637
Main Authors: Diaz-Montana, Juan J, Rackham, Owen J L, Diaz-Diaz, Norberto, Petretto, Enrico
Format: Article
Language:English
Subjects:
Applications Notes
Bioinformatics
Communities
Disease - genetics
Gene sequencing
Genes
Genome, Human
Genomes
Genomics
Humans
Internet
Mutation
Mutations
Platforms
Software
Virulence Factors - genetics
World Wide Web
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Summary: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. wgpa.systems-genetics.net.
ISSN:1367-4803
1367-4811
1460-2059
DOI:10.1093/bioinformatics/btv598