cola

DOI: 10.18129/B9.bioc.cola    

A Framework for Consensus Partitioning

Bioconductor version: Release (3.14)

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

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

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

Installation

To install this package, start R (version "4.1") and enter:

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

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")

 

HTML Use of cola
PDF   Reference Manual
Text   NEWS
Text   LICENSE

Details

biocViews Classification, Clustering, GeneExpression, Software
Version 2.0.0
In Bioconductor since BioC 3.9 (R-3.6) (3 years)
License MIT + file LICENSE
Depends R (>= 3.6.0)
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, markdown, digest, impute, brew, Rcpp (>= 0.11.0), BiocGenerics, eulerr, foreach, doParallel, irlba
LinkingTo Rcpp
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
SystemRequirements
Enhances
URL https://github.com/jokergoo/cola https://jokergoo.github.io/cola_collection/
Depends On Me
Imports Me
Suggests Me InteractiveComplexHeatmap, simplifyEnrichment
Links To Me
Build Report  

Package Archives

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

Source Package cola_2.0.0.tar.gz
Windows Binary cola_2.0.0.zip (32- & 64-bit)
macOS 10.13 (High Sierra) cola_2.0.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/cola
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/cola
Package Short Url https://bioconductor.org/packages/cola/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.14 Source Archive

Documentation »

Bioconductor

R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: