cola

This is the development version of cola; for the stable release version, see cola.

A Framework for Consensus Partitioning


Bioconductor version: Development (3.20)

Subgroup classification is a basic task in genomic data analysis, especially for gene expression and DNA methylation data analysis. It can also be used to test the agreement to known clinical annotations, or to test whether there exist significant batch effects. The cola package provides a general framework for subgroup classification by consensus partitioning. It has the following features: 1. It modularizes the consensus partitioning processes that various methods can be easily integrated. 2. It provides rich visualizations for interpreting the results. 3. It allows running multiple methods at the same time and provides functionalities to straightforward compare results. 4. It provides a new method to extract features which are more efficient to separate subgroups. 5. It automatically generates detailed reports for the complete analysis. 6. It allows applying consensus partitioning in a hierarchical manner.

Author: Zuguang Gu [aut, cre]

Maintainer: Zuguang Gu <z.gu at dkfz.de>

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

Installation

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


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("cola")

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("cola")
Use of cola HTML
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews Classification, Clustering, GeneExpression, Software
Version 2.11.0
In Bioconductor since BioC 3.9 (R-3.6) (5.5 years)
License MIT + file LICENSE
Depends R (>= 4.0.0)
Imports grDevices, graphics, grid, stats, utils, ComplexHeatmap(>= 2.5.4), matrixStats, GetoptLong, circlize (>= 0.4.7), GlobalOptions (>= 0.1.0), clue, parallel, RColorBrewer, cluster, skmeans, png, mclust, crayon, methods, xml2, microbenchmark, httr, knitr (>= 1.4.0), markdown (>= 1.6), digest, impute, brew, Rcpp (>= 0.11.0), BiocGenerics, eulerr, foreach, doParallel, doRNG, irlba
System Requirements
URL https://github.com/jokergoo/cola https://jokergoo.github.io/cola_collection/
See More
Suggests genefilter, mvtnorm, testthat (>= 0.3), samr, pamr, kohonen, NMF, WGCNA, Rtsne, umap, clusterProfiler, ReactomePA, DOSE, AnnotationDbi, gplots, hu6800.db, BiocManager, data.tree, dendextend, Polychrome, rmarkdown, simplifyEnrichment, cowplot, flexclust, randomForest, e1071
Linking To Rcpp
Enhances
Depends On Me
Imports Me
Suggests Me InteractiveComplexHeatmap, simplifyEnrichment
Links To Me
Build Report Build Report

Package Archives

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

Source Package cola_2.11.0.tar.gz
Windows Binary (x86_64) cola_2.11.0.zip
macOS Binary (x86_64) cola_2.11.0.tgz
macOS Binary (arm64) cola_2.11.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/cola
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/cola
Bioc Package Browser https://code.bioconductor.org/browse/cola/
Package Short Url https://bioconductor.org/packages/cola/
Package Downloads Report Download Stats