In:
Bioinformatics, Oxford University Press (OUP), Vol. 32, No. 4 ( 2016-02-15), p. 635-637
Abstract:
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. Availability and implementation: wgpa.systems-genetics.net Contact: enrico.petretto@duke-nus.edu.sg Supplementary information: Supplementary data are available at Bioinformatics online.
Type of Medium:
Online Resource
ISSN:
1367-4811
,
1367-4803
DOI:
10.1093/bioinformatics/btv598
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2016
detail.hit.zdb_id:
1468345-3
SSG:
12
