ClusterSignificance

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

The ClusterSignificance package provides tools to assess if class clusters in dimensionality reduced data representations have a separation different from permuted data

Bioconductor version: Development (3.18)

The ClusterSignificance package provides tools to assess if class clusters in dimensionality reduced data representations have a separation different from permuted data. The term class clusters here refers to, clusters of points representing known classes in the data. This is particularly useful to determine if a subset of the variables, e.g. genes in a specific pathway, alone can separate samples into these established classes. ClusterSignificance accomplishes this by, projecting all points onto a one dimensional line. Cluster separations are then scored and the probability of the seen separation being due to chance is evaluated using a permutation method.

Author: Jason T. Serviss [aut, cre], Jesper R. Gadin [aut]

Maintainer: Jason T Serviss <jason.serviss at ki.se>

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

Installation

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

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

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

BiocManager::install("ClusterSignificance")

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("ClusterSignificance")

ClusterSignificance Vignette	HTML	R Script
Reference Manual	PDF
NEWS	Text

Details

biocViews	Classification, Clustering, PrincipalComponent, Software, StatisticalMethod
Version	1.29.0
In Bioconductor since	BioC 3.3 (R-3.3) (7.5 years)
License	GPL-3
Depends	R (>= 3.3.0)
Imports	methods, pracma, princurve (>= 2.0.5), scatterplot3d, RColorBrewer, grDevices, graphics, utils, stats
Linking To
Suggests	knitr, rmarkdown, testthat, BiocStyle, ggplot2, plsgenomics, covr
System Requirements
Enhances
URL	https://github.com/jasonserviss/ClusterSignificance/
Bug Reports	https://github.com/jasonserviss/ClusterSignificance/issues

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	ClusterSignificance_1.29.0.tar.gz
Windows Binary	ClusterSignificance_1.29.0.zip (64-bit only)
macOS Binary (x86_64)	ClusterSignificance_1.29.0.tgz
macOS Binary (arm64)	ClusterSignificance_1.29.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/ClusterSignificance
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/ClusterSignificance
Bioc Package Browser	https://code.bioconductor.org/browse/ClusterSignificance/
Package Short Url	https://bioconductor.org/packages/ClusterSignificance/
Package Downloads Report	Download Stats