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: | 2.0.8 |
| Depends: | R (≥ 2.10.0) |
| Imports: | edgeR, plotrix, capushe, grDevices, graphics, stats |
| Suggests: | HTSFilter, Biobase |
| Published: | 2016-05-26 |
| 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 |
| Reference manual: | HTSCluster.pdf |
| Vignettes: |
Co-expression analysis of RNA-seq data with the "HTSCluster" package |
| Package source: | HTSCluster_2.0.8.tar.gz |
| Windows binaries: | r-devel: HTSCluster_2.0.8.zip, r-release: HTSCluster_2.0.8.zip, r-oldrel: HTSCluster_2.0.8.zip |
| macOS binaries: | r-release: HTSCluster_2.0.8.tgz, r-oldrel: HTSCluster_2.0.8.tgz |
| Old sources: | HTSCluster archive |
| Reverse imports: | coseq |
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