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>

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