MADGiC 0.2 – a Model-based approach for identifying Driver Genes in Cancer

MADGiC 0.2

:: DESCRIPTION

The R package `MADGiC‘ fits an empirical Bayesian hierarchical model to obtain posterior probabilities that each gene is a driver. The model accounts for (1) frequency of mutation compared to a sophisticated background model that accounts for gene-specific factors in addition to mutation type and nucleotide context, (2) predicted functional impact (in the form of SIFT scores) of each specific change, and (3) positional patterns in mutations that have been deposited into the COSMIC (Catalogue of Somatic Mutations in Cancer) database. Example data from the The Cancer Genome Atlas (TCGA) project ovarian cohort is provided.

::DEVELOPER

Kendziorski Lab

:: SCREENSHOTS

n/a

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • R package

:: DOWNLOAD

 MADGiC

:: MORE INFORMATION

Citation

MADGiC: a model-based approach for identifying driver genes in cancer.
Korthauer KD, Kendziorski C.
Bioinformatics. 2015 Jan 7. pii: btu858.