Publication Date:
2013-02-13
Description:
: 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 . Contact: bottomly@ohsu.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Print ISSN:
1367-4803
Electronic ISSN:
1460-2059
Topics:
Biology
,
Computer Science
,
Medicine
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