dear members of the BioC-devel list,

Markus and I are pleased to announce that the survcomp and genefu packages are now available  
on BioConductor.

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| survcomp |
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'survcomp' is an R/BioConductor package for performance assessment and statistical comparison of risk (survival) prediction models. We implemented numerous performance criteria widely used in survival analysis but which, to the best of our knowledge, have never been put together in a single package. These performance criteria are:
	- The traditional Hazard ratio ('hazard.ratio(...)')
	- The D index ('D.index(...)')
	- The concordance index ('concordance.index(...)', fast C implementation and estimation of confidence interval + significance)
	- The time-dependent ROC curve ('tdrocc(...)')
	- The Brier score ('sbrier.score2proba(...)')
	- The cross-validated partial likelihood ('cvpl(...)')
Statistical comparison is done by paired statistical tests (e.g., 'cindex.comp(...)'). Moreover we implemented functions to compute the meta-estimators for most of these performance criteria using traditional meta-analytical formula used to combine estimates from multiple independent datasets (e.g., 'combine.est(...)').

Latest development version: http://www.bioconductor.org/help/bioc-views/devel/bioc/html/survcomp.html
Latest release version (available soon): http://www.bioconductor.org/help/bioc-views/release/bioc/html/survcomp.html


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| genefu |
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'genefu' is an R/BioConductor package containing numerous functions to analyze gene expression data related to cancer, with a particular emphasis on breast cancer. We implemented several state-of-the-art prognostic gene signatures (gene70, gene76, pik3cags, genius, ggi, ...) and classifiers for identifying breast cancer molecular subtypes (pam50, ssp2006, ssp2003, scmod1, scmod2, and scmgene). Additional functions are also available for displaying results (Kaplan-Meier curves, boxplot and forestplot with specific options which may be useful in the field) and to identify robust cluster and/or gene signatures.

Latest development version: http://www.bioconductor.org/help/bioc-views/devel/bioc/html/genefu.html
Latest release version (available soon): http://www.bioconductor.org/help/bioc-views/release/bioc/html/genefu.html

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Benjamin Haibe-Kains and Markus Schroder
Computational Biology and Functional Genomics Laboratory
Center for Cancer Computational Biology
Harvard School of Public Health, Dana-Farber Cancer Institute


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