MWASTools

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

Bioconductor version: Release (3.20)

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 "4.4") 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")

MWASTools	HTML	R Script
Reference Manual	PDF
NEWS	Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Cheminformatics, Lipidomics, Metabolomics, QualityControl, Software, SystemsBiology
Version	1.30.0
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
URL

Suggests	RUnit, BiocGenerics, knitr, BiocStyle, rmarkdown
Linking To
Enhances
Depends On Me
Imports Me	MetaboSignal
Suggests Me
Links To Me
Build Report	Build Report

Package Archives

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

Source Package	MWASTools_1.30.0.tar.gz
Windows Binary (x86_64)	MWASTools_1.30.0.zip (64-bit only)
macOS Binary (x86_64)	MWASTools_1.30.0.tgz
macOS Binary (arm64)	MWASTools_1.29.0.tgz
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