HTSCluster: Clustering high throughput sequencing (HTS) data

This package implements a Poisson mixture model to cluster observations (e.g., genes) in high throughput sequencing data. Parameter estimation is performed using either the EM or CEM algorithm, and the slope heuristics are used for model selection (i.e., to choose the number of clusters).

Version: 2.0.4
Depends: R (≥ 2.10.0), capushe
Imports: edgeR, poisson.glm.mix, plotrix
Suggests: HTSFilter, Biobase
Published: 2014-08-26
Author: Andrea Rau, Gilles Celeux, Marie-Laure Martin-Magniette, Cathy Maugis-Rabusseau
Maintainer: Andrea Rau <andrea.rau at jouy.inra.fr>
License: GPL (≥ 3)
NeedsCompilation: no
Citation: HTSCluster citation info
Materials: NEWS
CRAN checks: HTSCluster results

Downloads:

Reference manual: HTSCluster.pdf
Vignettes: Co-expression analysis of RNA-seq data with the "HTSCluster" package
Package source: HTSCluster_2.0.4.tar.gz
Windows binaries: r-devel: HTSCluster_2.0.4.zip, r-release: HTSCluster_2.0.4.zip, r-oldrel: HTSCluster_2.0.4.zip
OS X Snow Leopard binaries: r-release: HTSCluster_2.0.3.tgz, r-oldrel: HTSCluster_2.0.3.tgz
OS X Mavericks binaries: r-release: HTSCluster_2.0.4.tgz
Old sources: HTSCluster archive

Reverse dependencies:

Reverse depends: HTSDiff