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: | 2.0.10 |
Depends: | R (≥ 2.10.0) |
Imports: | edgeR, plotrix, capushe, grDevices, graphics, stats |
Suggests: | HTSFilter, Biobase |
Published: | 2022-08-24 |
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 |
CRAN checks: | HTSCluster results |
Reference manual: | HTSCluster.pdf |
Vignettes: |
Co-expression analysis of RNA-seq data with the "HTSCluster" package |
Package source: | HTSCluster_2.0.10.tar.gz |
Windows binaries: | r-devel: HTSCluster_2.0.10.zip, r-release: HTSCluster_2.0.10.zip, r-oldrel: HTSCluster_2.0.10.zip |
macOS binaries: | r-release (arm64): HTSCluster_2.0.10.tgz, r-oldrel (arm64): HTSCluster_2.0.10.tgz, r-release (x86_64): HTSCluster_2.0.10.tgz, r-oldrel (x86_64): HTSCluster_2.0.10.tgz |
Old sources: | HTSCluster archive |
Reverse imports: | coseq |
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