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MCbiclust

Massive correlating biclusters for gene expression data and associated methods

Bioconductor version: Release (3.17)

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>

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

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("MCbiclust")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

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

browseVignettes("MCbiclust")
Introduction to MCbiclust HTML R Script
Reference Manual PDF

Details

biocViews Clustering, GeneExpression, ImmunoOncology, Microarray, RNASeq, Software, StatisticalMethod
Version 1.24.0
In Bioconductor since BioC 3.5 (R-3.4) (6.5 years)
License GPL-2
Depends R (>= 3.4)
Imports BiocParallel, graphics, utils, stats, AnnotationDbi, GO.db, org.Hs.eg.db, GGally, ggplot2, scales, cluster, WGCNA
Linking To
Suggests gplots, knitr, rmarkdown, BiocStyle, gProfileR, MASS, dplyr, pander, devtools, testthat, GSVA
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Package Archives

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

Source Package MCbiclust_1.24.0.tar.gz
Windows Binary MCbiclust_1.24.0.zip
macOS Binary (x86_64) MCbiclust_1.24.0.tgz
macOS Binary (arm64) MCbiclust_1.24.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/MCbiclust
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MCbiclust
Bioc Package Browser https://code.bioconductor.org/browse/MCbiclust/
Package Short Url https://bioconductor.org/packages/MCbiclust/
Package Downloads Report Download Stats