ctsGE

DOI: 10.18129/B9.bioc.ctsGE    

Clustering of Time Series Gene Expression data

Bioconductor version: Release (3.6)

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 and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("ctsGE")

Documentation

HTML R Script ctsGE Package
PDF   Reference Manual

Details

biocViews Bayesian, Clustering, DifferentialExpression, GeneExpression, GeneSetEnrichment, Genetics, RNASeq, Sequencing, Software, TimeCourse, Transcription
Version 1.4.0
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
LinkingTo
Suggests BiocStyle, dplyr, DT, GEOquery, knitr, pander, rmarkdown, testthat
SystemRequirements
Enhances
URL https://github.com/michalsharabi/ctsGE
BugReports https://github.com/michalsharabi/ctsGE/issues
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Source Package ctsGE_1.4.0.tar.gz
Windows Binary ctsGE_1.4.0.zip
Mac OS X 10.11 (El Capitan) ctsGE_1.4.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/ctsGE
Package Short Url http://bioconductor.org/packages/ctsGE/
Package Downloads Report Download Stats

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