Risa

This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.

This package is for version 3.20 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see Risa.

Converting experimental metadata from ISA-tab into Bioconductor data structures


Bioconductor version: Release (3.20)

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 <alejandra.gonzalez.beltran at gmail.com>

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

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("Risa")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews Annotation, DataImport, MassSpectrometry, Software
Version 1.48.0
In Bioconductor since BioC 2.11 (R-2.15) (12 years)
License LGPL
Depends R (>= 2.0.9), Biobase(>= 2.4.0), methods, Rcpp (>= 0.9.13), biocViews, affy
Imports xcms
System Requirements
URL http://www.isa-tools.org/
Bug Reports https://github.com/ISA-tools/Risa/issues
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Suggests faahKO(>= 1.2.11)
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Package Archives

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

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/Risa
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/Risa
Package Short Url https://bioconductor.org/packages/Risa/
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