ctsGE

Clustering of Time Series Gene Expression data


Bioconductor version: Release (3.19)

Methodology for supervised clustering of potentially many predictor variables, such as genes etc., in time series datasets Provides functions that help the user assigning genes to predefined set of model profiles.

Author: Michal Sharabi-Schwager [aut, cre], Ron Ophir [aut]

Maintainer: Michal Sharabi-Schwager <michalsharabi at gmail.com>

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

Installation

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


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

BiocManager::install("ctsGE")

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("ctsGE")
ctsGE Package HTML R Script
Reference Manual PDF

Details

biocViews Bayesian, Clustering, DifferentialExpression, GeneExpression, GeneSetEnrichment, Genetics, ImmunoOncology, RNASeq, Sequencing, Software, TimeCourse, Transcription
Version 1.30.0
In Bioconductor since BioC 3.4 (R-3.3) (8 years)
License GPL-2
Depends R (>= 3.2)
Imports ccaPP, ggplot2, limma, reshape2, shiny, stats, stringr, utils
System Requirements
URL https://github.com/michalsharabi/ctsGE
Bug Reports https://github.com/michalsharabi/ctsGE/issues
See More
Suggests BiocStyle, dplyr, DT, GEOquery, knitr, pander, rmarkdown, testthat
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Package Archives

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

Source Package ctsGE_1.30.0.tar.gz
Windows Binary (x86_64) ctsGE_1.30.0.zip (64-bit only)
macOS Binary (x86_64) ctsGE_1.30.0.tgz
macOS Binary (arm64) ctsGE_1.30.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/ctsGE
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/ctsGE
Bioc Package Browser https://code.bioconductor.org/browse/ctsGE/
Package Short Url https://bioconductor.org/packages/ctsGE/
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