DOI: 10.18129/B9.bioc.ctsGE    

Clustering of Time Series Gene Expression data

Bioconductor version: Release (3.7)

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>

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biocViews Bayesian, Clustering, DifferentialExpression, GeneExpression, GeneSetEnrichment, Genetics, RNASeq, Sequencing, Software, TimeCourse, Transcription
Version 1.6.1
In Bioconductor since BioC 3.4 (R-3.3) (1.5 years)
License GPL-2
Depends R (>= 3.2)
Imports ccaPP, ggplot2, limma, reshape2, shiny, stats, stringr, utils
Suggests BiocStyle, dplyr, DT, GEOquery, knitr, pander, rmarkdown, testthat
URL https://github.com/michalsharabi/ctsGE
BugReports https://github.com/michalsharabi/ctsGE/issues
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Source Package ctsGE_1.6.1.tar.gz
Windows Binary ctsGE_1.6.1.zip
Mac OS X 10.11 (El Capitan) ctsGE_1.6.1.tgz
Source Repository git clone https://git.bioconductor.org/packages/ctsGE
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/ctsGE
Package Short Url http://bioconductor.org/packages/ctsGE/
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