To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("Risa")

In most cases, you don't need to download the package archive at all.

Risa

 

Converting experimental metadata from ISA-tab into Bioconductor data structures

Bioconductor version: Release (3.1)

The Investigation / Study / Assay (ISA) tab-delimited format is a general purpose framework with which to collect and communicate complex metadata (i.e. sample characteristics, technologies used, type of measurements made) from experiments employing a combination of technologies, spanning from traditional approaches to high-throughput techniques. Risa allows to access metadata/data in ISA-Tab format and build Bioconductor data structures. Currently, data generated from microarray, flow cytometry and metabolomics-based (i.e. mass spectrometry) assays are supported. The package is extendable and efforts are undergoing to support metadata associated to proteomics assays.

Author: Alejandra Gonzalez-Beltran, Audrey Kauffmann, Steffen Neumann, Gabriella Rustici, ISA Team

Maintainer: Alejandra Gonzalez-Beltran, ISA Team <isatools at googlegroups.com>

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

Installation

To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("Risa")

Documentation

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

browseVignettes("Risa")

 

PDF R Script Risa: converts experimental metadata from ISA-tab into Bioconductor data structures
PDF   Reference Manual
Text   NEWS

Details

biocViews Annotation, DataImport, MassSpectrometry, Software
Version 1.10.0
In Bioconductor since BioC 2.11 (R-2.15) (3 years)
License LGPL
Depends R (>= 2.0.9), Biobase(>= 2.4.0), methods, Rcpp (>= 0.9.13), biocViews, affy
Imports xcms
LinkingTo
Suggests faahKO(>= 1.2.11)
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source Risa_1.10.0.tar.gz
Windows Binary Risa_1.10.0.zip
Mac OS X 10.6 (Snow Leopard) Risa_1.10.0.tgz
Mac OS X 10.9 (Mavericks) Risa_1.10.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/Risa/tree/release-3.1
Package Short Url http://bioconductor.org/packages/Risa/
Package Downloads Report Download Stats

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