MWASTools

This is the development version of MWASTools; for the stable release version, see MWASTools.

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


Bioconductor version: Development (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")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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")
MWASTools HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Cheminformatics, Lipidomics, Metabolomics, QualityControl, Software, SystemsBiology
Version 1.31.0
In Bioconductor since BioC 3.5 (R-3.4) (7.5 years)
License CC BY-NC-ND 4.0
Depends R (>= 3.5.0)
Imports glm2, ppcor, qvalue, car, boot, grid, ggplot2, gridExtra, igraph, SummarizedExperiment, KEGGgraph, RCurl, KEGGREST, ComplexHeatmap, stats, utils
System Requirements
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Suggests RUnit, BiocGenerics, knitr, BiocStyle, rmarkdown
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Depends On Me
Imports Me MetaboSignal
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Package Archives

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

Source Package MWASTools_1.31.0.tar.gz
Windows Binary (x86_64) MWASTools_1.31.0.zip (64-bit only)
macOS Binary (x86_64) MWASTools_1.31.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/MWASTools
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MWASTools
Bioc Package Browser https://code.bioconductor.org/browse/MWASTools/
Package Short Url https://bioconductor.org/packages/MWASTools/
Package Downloads Report Download Stats