M3C

DOI: 10.18129/B9.bioc.M3C    

Monte Carlo Reference-based Consensus Clustering

Bioconductor version: Release (3.8)

Genome-wide data is used to stratify large complex datasets into classes using class discovery algorithms. A widely applied technique is consensus clustering, however; the approach is prone to overfitting and false positives. These issues arise from not considering reference distributions while selecting the number of classes (K). As a solution, we developed Monte Carlo reference-based consensus clustering (M3C). M3C uses a multi-core enabled Monte Carlo simulation to generate null distributions along the range of K which are used to select its value. Using a reference, that maintains the correlation structure of the input features, eliminates the limitations of consensus clustering. M3C uses the Relative Cluster Stability Index (RCSI) and p values to decide on the value of K and reject the null hypothesis, K=1. M3C can also quantify structural relationships between clusters, and uses spectral clustering to deal with non-Gaussian and complex structures. M3C can automatically analyse biological or clinical data with respect to the discovered classes.

Author: Christopher John [aut, cre]

Maintainer: Christopher John <chris.r.john86 at gmail.com>

Citation (from within R, enter citation("M3C")):

Installation

To install this package, start R and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("M3C", version = "3.8")

Documentation

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

browseVignettes("M3C")

 

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Details

biocViews Clustering, GeneExpression, RNASeq, Sequencing, Software, Transcription
Version 1.4.0
License AGPL-3
Depends R (>= 3.4.0)
Imports ggplot2, Matrix, doSNOW, NMF, RColorBrewer, cluster, parallel, foreach, doParallel, matrixcalc, dendextend, sigclust, Rtsne, survival
LinkingTo
Suggests knitr, rmarkdown
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package M3C_1.4.0.tar.gz
Windows Binary M3C_1.4.0.zip
Mac OS X 10.11 (El Capitan) M3C_1.4.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/M3C
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/M3C
Package Short Url http://bioconductor.org/packages/M3C/
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