HTSCluster: Clustering High-Throughput Transcriptome Sequencing (HTS) Data

A Poisson mixture model is implemented to cluster genes from high- throughput transcriptome sequencing (RNA-seq) 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: 2.0.11
Depends: R (≥ 2.10.0)
Imports: edgeR, plotrix, capushe, grDevices, graphics, stats
Suggests: HTSFilter, Biobase
Published: 2023-09-05
DOI: 10.32614/CRAN.package.HTSCluster
Author: Andrea Rau, Gilles Celeux, Marie-Laure Martin-Magniette, Cathy Maugis- Rabusseau
Maintainer: Andrea Rau <andrea.rau at>
License: GPL (≥ 3)
NeedsCompilation: no
Citation: HTSCluster citation info
Materials: README NEWS
In views: Omics
CRAN checks: HTSCluster results


Reference manual: HTSCluster.pdf
Vignettes: Co-expression analysis of RNA-seq data with the "HTSCluster" package


Package source: HTSCluster_2.0.11.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): HTSCluster_2.0.11.tgz, r-oldrel (arm64): HTSCluster_2.0.11.tgz, r-release (x86_64): HTSCluster_2.0.11.tgz, r-oldrel (x86_64): HTSCluster_2.0.11.tgz
Old sources: HTSCluster archive

Reverse dependencies:

Reverse imports: coseq


Please use the canonical form to link to this page.