Leo Lahti*¹, Martin Schäfer², Hans-Ulrich Klein³, Silvio
Bicciato4; and Martin Dugas³
(1) Wageningen University, Netherlands. (2) TU Dortmund University, Germany (3) University of Münster,
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.
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