intcomp: a benchmarking pipeline for integrative cancer gene detection algorithms
Leo Lahti, Martin Schäfer², Hans-Ulrich Klein³, Silvio Bicciato4; and Martin Dugas³
(1) Wageningen University, Netherlands. (2) TU Dortmund University, Germany (3) University of M√ľnster, Germany (4) University of Modena and Reggio Emilia, Italy.

The intcomp R package provides a benchmarking tools for quantitative comparison of cancer gene detection algorithms based on integrative analysis of DNA copy number and gene expression data. The cancer gene prioritization performance of the methods is compared with respect to golden-standard lists of known cancer genes in real and simulated data sets [1]. The comparison methods include variants of CNAmet, DRI, edira, intCNGEan, pint/simcca, PMA, PREDA/SODEGIR, SIM and Ortiz-Estevez.

The current version focuses on cancer gene prioritization performance of these algorithms. Contributions for further methods, data sets and benchmarking procedures are welcome.
DNA Double Helix


Download the source code package intcomp_latest.tar.gz. The sources are also available through SVN from R-Forge. See the package vignette for installation instructions, package dependencies, further details and references.

Benchmarking results

The benchmarking results reported in Briefings in Bioinformatics [1] are available as R data files from the results directory.


This work was supported by EuGESMA COST Action BM0801 (European Genomics and Epigenomics Study on MDS and AML). The work is licensed under the FreeBSD open source license. Your feedback and contributions are welcome. See the project page at R-Forge, or contact project admin.


  1. Lahti L, Schäfer M, Klein H-U, Bicciato S, and Dugas M. Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review. Briefings in Bioinformatics. Online March 2012. (Abstract; PDF).