DIGGIT: a Bioconductor package to infer genetic variants driving cellular phenotypes

Bioinformatics. 2015 Dec 15;31(24):4032-4. doi: 10.1093/bioinformatics/btv499. Epub 2015 Sep 2.


Identification of driver mutations in human diseases is often limited by cohort size and availability of appropriate statistical models. We propose a method for the systematic discovery of genetic alterations that are causal determinants of disease, by prioritizing genes upstream of functional disease drivers, within regulatory networks inferred de novo from experimental data. Here we present the implementation of Driver-gene Inference by Genetical-Genomic Information Theory as an R-system package.

Availability and implementation: The diggit package is freely available under the GPL-2 license from Bioconductor (http://www.bioconductor.org).

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Gene Expression
  • Gene Regulatory Networks
  • Genome, Human
  • Genomics
  • Humans
  • Models, Statistical
  • Mutation*
  • Phenotype
  • Software*