ClusterSignificance
This package is for version 3.19 of Bioconductor; for the stable, up-to-date 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: 3.19
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("ClusterSignificance")):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
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 | ||
| NEWS | Text |
Details
| biocViews | Classification, Clustering, PrincipalComponent, Software, StatisticalMethod |
| Version | 1.32.0 |
| In Bioconductor since | BioC 3.3 (R-3.3) (8.5 years) |
| License | GPL-3 |
| Depends | R (>= 3.3.0) |
| Imports | methods, pracma, princurve (>= 2.0.5), scatterplot3d, RColorBrewer, grDevices, graphics, utils, stats |
| System Requirements | |
| URL | https://github.com/jasonserviss/ClusterSignificance/ |
| Bug Reports | https://github.com/jasonserviss/ClusterSignificance/issues |
See More
| Suggests | knitr, rmarkdown, testthat, BiocStyle, ggplot2, plsgenomics, covr |
| Linking To | |
| Enhances | |
| 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 | ClusterSignificance_1.32.0.tar.gz |
| Windows Binary (x86_64) | ClusterSignificance_1.32.0.zip |
| macOS Binary (x86_64) | ClusterSignificance_1.32.0.tgz |
| macOS Binary (arm64) | ClusterSignificance_1.32.0.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 |