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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 jouy.inra.fr>
License: GPL (≥ 3)
NeedsCompilation: no
Citation: HTSCluster citation info
Materials: README NEWS
In views: Omics
CRAN checks: HTSCluster results

Documentation:

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

Downloads:

Package source: HTSCluster_2.0.11.tar.gz
Windows binaries: r-devel: HTSCluster_2.0.11.zip, r-release: HTSCluster_2.0.11.zip, r-oldrel: HTSCluster_2.0.11.zip
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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=HTSCluster to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.