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

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

Author information

1
Department of Systems Biology and.
2
Department of Systems Biology and Department of Dermatology, Columbia University, New York, NY 10032 USA.

Abstract

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).

PMID:
26338767
PMCID:
PMC4692968
DOI:
10.1093/bioinformatics/btv499
[Indexed for MEDLINE]
Free PMC Article

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