HTSCluster: Clustering High-Throughput Transcriptome Sequencing (HTS) Data (original) (raw)
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 |
| In views: | Omics |
| CRAN checks: | HTSCluster results |
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