HTSCluster: Clustering high throughput sequencing (HTS) data
This package implements two parameterizations of a Poisson
mixture model to cluster observations (e.g., genes) in high
throughput sequencing data. Parameter estimation is performed
using either the EM or CEM algorithm, and the BIC or ICL
criteria are used for model selection (i.e., to choose the
number of clusters).
| Version: |
1.1 |
| Depends: |
R (≥ 2.10.0), plotrix |
| Published: |
2012-06-11 |
| 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 |
| CRAN checks: |
HTSCluster results |
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