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ABSTRACT: Summary
Determining the functional relevance of identified sequence variants in cancer is a prerequisite to ultimately matching specific therapies with individual patients. This level of mechanistic understanding requires integration of genomic information with complementary functional analyses to identify oncogenic targets and relies on the development of computational frameworks to aid in the prioritization and visualization of these diverse data types. In response to this, we have developed HitWalker, which prioritizes patient variants relative to their weighted proximity to functional assay results in a protein-protein interaction network. It is highly extensible, allowing incorporation of diverse data types to refine prioritization. In addition to a ranked list of variants, we have also devised a simple shortest path-based approach of visualizing the results in an intuitive manner to provide biological interpretation.Availability and implementation
The program, documentation and example data are available as an R package from www.biodevlab.org/HitWalker.html.
SUBMITTER: Bottomly D
PROVIDER: S-EPMC3570211 | biostudies-literature | 2013 Feb
REPOSITORIES: biostudies-literature
Bottomly Daniel D Wilmot Beth B Tyner Jeffrey W JW Eide Christopher A CA Loriaux Marc M MM Druker Brian J BJ McWeeney Shannon K SK
Bioinformatics (Oxford, England) 20130109 4
<h4>Summary</h4>Determining the functional relevance of identified sequence variants in cancer is a prerequisite to ultimately matching specific therapies with individual patients. This level of mechanistic understanding requires integration of genomic information with complementary functional analyses to identify oncogenic targets and relies on the development of computational frameworks to aid in the prioritization and visualization of these diverse data types. In response to this, we have dev ...[more]