MWASTools

DOI: 10.18129/B9.bioc.MWASTools    

This package is for version 3.13 of Bioconductor; for the stable, up-to-date release version, see MWASTools.

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

Bioconductor version: 3.13

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>

Installation

To install this package, start R (version "4.1") and enter:

if (!requireNamespace("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")

 

HTML	R Script	MWASTools
PDF		Reference Manual
Text		NEWS

Details

biocViews	Cheminformatics, Lipidomics, Metabolomics, QualityControl, Software, SystemsBiology
Version	1.16.0
In Bioconductor since	BioC 3.5 (R-3.4) (4.5 years)
License	CC BY-NC-ND 4.0
Depends	R (>= 3.4)
Imports	glm2, ppcor, qvalue, car, boot, grid, ggplot2, gridExtra, igraph, SummarizedExperiment, KEGGgraph, RCurl, KEGGREST, ComplexHeatmap, stats, utils
LinkingTo
Suggests	RUnit, BiocGenerics, knitr, BiocStyle, rmarkdown
SystemRequirements
Enhances
URL
Depends On Me
Imports Me	MetaboSignal
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	MWASTools_1.16.0.tar.gz
Windows Binary	MWASTools_1.16.0.zip
macOS 10.13 (High Sierra)	MWASTools_1.16.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/MWASTools
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/MWASTools
Package Short Url	https://bioconductor.org/packages/MWASTools/
Package Downloads Report	Download Stats