Author: Andrea Rau, Gilles Celeux, Marie-Laure Martin-Magniette, Cathy
Description: 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

Depends: R (>= 2.10.0), plotrix, ggplot2, RColorBrewer
Description: This package implements 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 ICL criterion is used for model selection (i.e., to choose the number of clusters).

Title: Clustering High-Throughput Transcriptome Sequencing (HTS) Data
Author: Andrea Rau, Gilles Celeux, Marie-Laure Martin-Magniette, Cathy Maugis-
Imports: edgeR, plotrix, capushe, grDevices, graphics, stats
Description: 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).

Description: This package implements 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 slope heuristics are used for model selection (i.e., to choose the number of clusters).

Title: Differential analysis of RNA-seq data with Poisson mixture
Author: Andrea Rau, Marie-Laure Martin-Magniette, Cathy Maugis-Rabusseau
Depends: R (>= 2.10.0), plotrix, HTSCluster (>= 1.99.0)
Description: This package implements a Poisson mixture model to identify differentially expressed genes from RNA-seq data.

Depends: R (>= 2.10.0), plotrix, HTSCluster (>= 2.0.3)

Title: Differential Analysis of RNA-Seq Data with Poisson Mixture
Depends: R (>= 2.10.0), plotrix, HTSCluster (>= 2.0.4)