- The Bioconductor package coseq: This package is devoted to the co-expression analysis of sequencing data. It contains the Poisson mixture models developed in HTSCluster (see below), the strategy based on Gaussian mixture models on transformed profiles (see Rau and Maugis-Rabusseau, 2016 for more details) and the use of the K-means algorithm for RNA-seq profiles after transformation via the centered log ratio (CLR) or log centered log ratio (logCLR) transformation (see Godichon-Baggioni et al, 2017).
To install coseq, start R and enter
source("https://bioconductor.org/biocLite.R")
biocLite("coseq")
A quick-start guide is available here
- R package HTSCluster: 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).
- R package HTSDiff: This package implements a Poisson mixture model to identify differentially expressed genes from RNA-seq data.
- The R-package SelvarMix for variable selection in model-based clustering and discriminant analysis with a regularization approach