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MWASTools

This is the released version of MWASTools; for the devel version, see MWASTools.

MWASTools: an integrated pipeline to perform metabolome-wide association studies


Bioconductor version: Release (3.21)

MWASTools provides a complete pipeline to perform metabolome-wide association studies. Key functionalities of the package include: quality control analysis of metabonomic data; MWAS using different association models (partial correlations; generalized linear models); model validation using non-parametric bootstrapping; visualization of MWAS results; NMR metabolite identification using STOCSY; and biological interpretation of MWAS results.

Author: Andrea Rodriguez-Martinez, Joram M. Posma, Rafael Ayala, Ana L. Neves, Maryam Anwar, Jeremy K. Nicholson, Marc-Emmanuel Dumas

Maintainer: Andrea Rodriguez-Martinez <andrea.rodriguez-martinez13 at imperial.ac.uk>, Rafael Ayala <rafael.ayala at oist.jp>

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

Installation

To install this package, start R (version "4.5") and enter:

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

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

Documentation

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

browseVignettes("MWASTools")
MWASToolsHTMLR Script
Reference ManualPDF
NEWSText

Details

biocViewsCheminformatics, Lipidomics, Metabolomics, QualityControl, Software, SystemsBiology
Version1.32.0
In Bioconductor sinceBioC 3.5 (R-3.4) (8 years)
LicenseCC BY-NC-ND 4.0
DependsR (>= 3.5.0)
Importsglm2, ppcor, qvalue, car, boot, grid, ggplot2, gridExtra, igraph, SummarizedExperiment, KEGGgraph, RCurl, KEGGREST, ComplexHeatmap, stats, utils
System Requirements
URL
See More
SuggestsRUnit, BiocGenerics, knitr, BiocStyle, rmarkdown
Linking To
Enhances
Depends On Me
Imports MeMetaboSignal
Suggests Me
Links To Me
Build ReportBuild Report

Package Archives

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

Source PackageMWASTools_1.32.0.tar.gz
Windows Binary (x86_64) MWASTools_1.32.0.zip (64-bit only)
macOS Binary (x86_64)MWASTools_1.32.0.tgz
macOS Binary (arm64)MWASTools_1.32.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/MWASTools
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/MWASTools
Bioc Package Browserhttps://code.bioconductor.org/browse/MWASTools/
Package Short Urlhttps://bioconductor.org/packages/MWASTools/
Package Downloads ReportDownload Stats
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