To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("http://bioc.ism.ac.jp/biocLite.R")
biocLite("coseq")

In most cases, you don't need to download the package archive at all.

coseq

DOI: 10.18129/B9.bioc.coseq    

Co-Expression Analysis of Sequencing Data

Bioconductor version: Release (3.6)

Co-expression analysis for expression profiles arising from high-throughput sequencing data. Feature (e.g., gene) profiles are clustered using adapted transformations and mixture models or a K-means algorithm, and model selection criteria (to choose an appropriate number of clusters) are provided.

Author: Andrea Rau, Cathy Maugis-Rabusseau, Antoine Godichon-Baggioni

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

Citation (from within R, enter citation("coseq")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("http://bioc.ism.ac.jp/biocLite.R")
biocLite("coseq")

Documentation

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Details

biocViews GeneExpression, RNASeq, Sequencing, Software
Version 1.2.0
In Bioconductor since BioC 3.5 (R-3.4) (0.5 years)
License GPL (>=3)
Depends R (>= 3.4.1), SummarizedExperiment, S4Vectors
Imports edgeR, DESeq2, capushe, Rmixmod, e1071, BiocParallel, ggplot2 (>= 2.1.0), scales, HTSFilter, corrplot, HTSCluster (>= 2.0.8), gridExtra, grDevices, graphics, stats, methods, compositions, mvtnorm
LinkingTo
Suggests Biobase, knitr, rmarkdown, testthat
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package coseq_1.2.0.tar.gz
Windows Binary coseq_1.2.0.zip
Mac OS X 10.11 (El Capitan) coseq_1.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/coseq
Package Short Url http://bioconductor.org/packages/coseq/
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