Registration Open for Bioc2024 July 24-26


Massive correlating biclusters for gene expression data and associated methods

Bioconductor version: Release (3.19)

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>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


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


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

Introduction to MCbiclust HTML R Script
Reference Manual PDF


biocViews Clustering, GeneExpression, ImmunoOncology, Microarray, RNASeq, Software, StatisticalMethod
Version 1.28.0
In Bioconductor since BioC 3.5 (R-3.4) (7 years)
License GPL-2
Depends R (>= 3.4)
Imports BiocParallel, graphics, utils, stats, AnnotationDbi, GO.db,, GGally, ggplot2, scales, cluster, WGCNA
System Requirements
See More
Suggests gplots, knitr, rmarkdown, BiocStyle, gProfileR, MASS, dplyr, pander, devtools, testthat, GSVA
Linking To
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package MCbiclust_1.28.0.tar.gz
Windows Binary (64-bit only)
macOS Binary (x86_64) MCbiclust_1.28.0.tgz
macOS Binary (arm64) MCbiclust_1.28.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
Bioc Package Browser
Package Short Url
Package Downloads Report Download Stats