Bioconductor - MWASTools
Bioconductor 3.22
Software Packages
MWASTools
MWASTools
This is the
released
version of MWASTools; for the devel version, see
MWASTools
MWASTools: an integrated pipeline to perform metabolome-wide association studies
DOI:
10.18129/B9.bioc.MWASTools
Bioconductor version:
Release (3.22)
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
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")
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
1.34.0
In Bioconductor since
BioC 3.5 (R-3.4) (9 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
See More
Suggests
RUnit
BiocGenerics
knitr
BiocStyle
rmarkdown
Linking To
Enhances
Depends On Me
Imports Me
MetaboSignal
Suggests Me
Links To Me
Build Report
Build Report
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Installation
instructions to use this package in your R session.
Source Package
MWASTools_1.34.0.tar.gz
Windows Binary (x86_64)
MWASTools_1.34.0.zip
macOS Binary (x86_64)
MWASTools_1.34.0.tgz
macOS Binary (arm64)
MWASTools_1.34.0.tgz
Source Repository
git clone https://git.bioconductor.org/packages/MWASTools
Source Repository (Developer Access)
git clone git@git.bioconductor.org:packages/MWASTools
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