SDisc: Integrated methodology for the identification of homogeneous profiles in data distribution

Integrated set of tools and methods to identify homogeneous profiles/subtypes in data distribution by cluster analysis. It includes methods for data treatment and pre-processing, repeated cluster analysis, model selection, model reliability and reproducibility assessment, profiles characterization and validation by visual and table summaries. It applies particularly to the search for more homogeneous profiles in cohort studies.

Version: 1.17
Depends: R (≥ 2.5.1), mclust, stats, utils, RColorBrewer, abind, xtable, digest, e1071, snow
Published: 2009-11-05
Author: Fabrice Colas
Maintainer: Fabrice Colas <fcolas at liacs.nl>
License: BSD
URL: https://gforge.nbic.nl/projects/subtypediscover/, http://www.grano-salis.net/
CRAN checks: SDisc results

Downloads:

Package source: SDisc_1.17.tar.gz
MacOS X binary: SDisc_1.17.tgz
Windows binary: SDisc_1.17.zip
Reference manual: SDisc.pdf