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("clusterSeq")

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

clusterSeq

DOI: 10.18129/B9.bioc.clusterSeq    

Clustering of high-throughput sequencing data by identifying co-expression patterns

Bioconductor version: Release (3.6)

Identification of clusters of co-expressed genes based on their expression across multiple (replicated) biological samples.

Author: Thomas J. Hardcastle & Irene Papatheodorou

Maintainer: Thomas J. Hardcastle <tjh48 at cam.ac.uk>

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

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("clusterSeq")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("clusterSeq")

 

PDF R Script Advanced baySeq analyses
PDF   Reference Manual

Details

biocViews Clustering, DifferentialExpression, GeneExpression, MultipleComparison, Sequencing, Software
Version 1.2.0
In Bioconductor since BioC 3.5 (R-3.4) (0.5 years)
License GPL-3
Depends R (>= 3.0.0), methods, BiocParallel, baySeq, graphics, stats, utils
Imports BiocGenerics
LinkingTo
Suggests BiocStyle
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 clusterSeq_1.2.0.tar.gz
Windows Binary clusterSeq_1.2.0.zip
Mac OS X 10.11 (El Capitan) clusterSeq_1.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/clusterSeq
Package Short Url http://bioconductor.org/packages/clusterSeq/
Package Downloads Report Download Stats

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