HitWalker: Variant prioritization for personalized functional cancer genomics

Daniel Bottomly, Beth Wilmot, Jeffrey W. Tyner, Christopher A. Eide, Marc M. Loriaux, Brian J. Druker, Shannon K. McWeeney

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)509-510
Number of pages2
Issue number4
StatePublished - Feb 15 2013

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics


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