HTSCluster 2.0.8 – Clustering High Throughput Sequencing (HTS) data

HTSCluster 2.0.8

:: DESCRIPTION

HTSCluster 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).

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::DEVELOPER

Andrea Rau <andrea.rau at jouy.inra.fr>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • R

:: DOWNLOAD

 HTSCluster

:: MORE INFORMATION

Citation:

Co-expression analysis of high-throughput transcriptome sequencing data with Poisson mixture models.
Rau A, Maugis-Rabusseau C, Martin-Magniette ML, Celeux G.
Bioinformatics. 2015 Jan 5. pii: btu845.