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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>

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


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

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

ctsGE Package HTML R Script
Reference Manual PDF


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) (7.5 years)
License GPL-2
Depends R (>= 3.2)
Imports ccaPP, ggplot2, limma, reshape2, shiny, stats, stringr, utils
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Suggests BiocStyle, dplyr, DT, GEOquery, knitr, pander, rmarkdown, testthat
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Source Package ctsGE_1.30.0.tar.gz
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