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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("genArise")
In most cases, you don't need to download the package archive at all.
genArise
Microarray Analysis tool
Bioconductor version: 2.14
genArise is an easy to use tool for dual color microarray data. Its GUI-Tk based environment let any non-experienced user performs a basic, but not simple, data analysis just following a wizard. In addition it provides some tools for the developer.
Author: Ana Patricia Gomez Mayen <pgomez at ifc.unam.mx>,\\ Gustavo Corral Guille <gcorral at ifc.unam.mx>, \\ Lina Riego Ruiz <lriego at ifc.unam.mx>,\\ Gerardo Coello Coutino <gcoello at ifc.unam.mx>
Maintainer: IFC Development Team <info-genarise at ifc.unam.mx>
Citation (from within R,
enter citation("genArise")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("genArise")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("genArise")
| R Script | genAriseGUI Vignette | |
| Reference Manual | ||
| Text | LICENSE |
Details
| biocViews | Microarray, Preprocessing, Software, TwoChannel |
| Version | 1.40.0 |
| In Bioconductor since | BioC 1.6 (R-2.1) or earlier |
| License | file LICENSE |
| Depends | R (>= 1.7.1), locfit, tkrplot, methods |
| Imports | graphics, grDevices, methods, stats, tcltk, utils, xtable |
| Suggests | |
| System Requirements | |
| URL | http://www.ifc.unam.mx/genarise |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | genArise_1.40.0.tar.gz |
| Windows Binary | genArise_1.40.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | genArise_1.40.0.tgz |
| Mac OS X 10.9 (Mavericks) | genArise_1.40.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
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