MCbiclust

DOI: 10.18129/B9.bioc.MCbiclust    

Massive correlating biclusters for gene expression data and associated methods

Bioconductor version: Release (3.6)

Custom made algorithm and associated methods for finding, visualising and analysing biclusters in large gene expression data sets. Algorithm is based on with a supplied gene set of size n, finding the maximum strength correlation matrix containing m samples from the data set.

Author: Robert Bentham

Maintainer: Robert Bentham <robert.bentham.11 at ucl.ac.uk>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("MCbiclust")

Documentation

HTML	R Script	Introduction to MCbiclust
PDF		Reference Manual

Details

biocViews	Clustering, GeneExpression, Microarray, RNASeq, Software, StatisticalMethod
Version	1.2.2
In Bioconductor since	BioC 3.5 (R-3.4) (1 year)
License	GPL-2
Depends	R (>= 3.4)
Imports	BiocParallel, graphics, utils, stats, AnnotationDbi, GO.db, org.Hs.eg.db, GGally, ggplot2, scales, cluster, WGCNA
LinkingTo
Suggests	gplots, knitr, rmarkdown, BiocStyle, gProfileR, MASS, dplyr, pander, devtools, testthat, GSVA
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	MCbiclust_1.2.2.tar.gz
Windows Binary	MCbiclust_1.2.2.zip
Mac OS X 10.11 (El Capitan)	MCbiclust_1.2.2.tgz
Source Repository	git clone https://git.bioconductor.org/packages/MCbiclust
Package Short Url	http://bioconductor.org/packages/MCbiclust/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.6	Source Archive