HitWalker: Variant prioritization for personalized functional cancer genomics

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

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

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
JournalBioinformatics
Volume29
Issue number4
DOIs
StatePublished - Feb 15 2013

Fingerprint

Prioritization
Genomics
Cancer
Program documentation
Proteins
Protein Interaction Maps
Documentation
Assays
Neoplasms
Visualization
Protein Interaction Networks
Availability
Protein-protein Interaction
Shortest path
Proximity
Therapy
Intuitive
Target
Therapeutics

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability
  • Medicine(all)

Cite this

HitWalker : Variant prioritization for personalized functional cancer genomics. / Bottomly, Daniel; Wilmot, Beth; Tyner, Jeffrey; Eide, Christopher A.; Loriaux, Marc; Druker, Brian; McWeeney, Shannon.

In: Bioinformatics, Vol. 29, No. 4, 15.02.2013, p. 509-510.

Research output: Contribution to journalArticle

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