ClusterSignificance
This is the released version of ClusterSignificance; for the devel 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: Release (3.23)
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")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") 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 | 1.40.0 |
| In Bioconductor since | BioC 3.3 (R-3.3) (10.5 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_1.40.0.tar.gz |
| Windows Binary (x86_64) | ClusterSignificance_1.40.0.zip |
| macOS Binary (big-sur-x86_64) | ClusterSignificance_1.40.0.tgz |
| macOS Binary (sonoma-arm64) | ClusterSignificance_1.40.0.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 |