MWASTools: an R/Bioconductor package for metabolome-wide association studies
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Author(s)
Type
Journal Article
Abstract
Summary: MWASTools is an R package designed to provide an integrated pipeline to analyze metabonomic data in large-scale epidemiological studies. Key functionalities of our package include: quality control analysis; metabolome-wide association analysis using various models (partial correlations, generalized linear models); visualization of statistical outcomes; metabolite assignment using statistical total correlation spectroscopy (STOCSY); and biological interpretation of MWAS results.
Availability: The MWASTools R package is implemented in R (version > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/
Availability: The MWASTools R package is implemented in R (version > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/
Date Issued
2017-07-26
Date Acceptance
2017-07-15
Citation
Bioinformatics, 2017, 34 (5), pp.890-892
ISSN
1367-4803
Publisher
Oxford University Press (OUP)
Start Page
890
End Page
892
Journal / Book Title
Bioinformatics
Volume
34
Issue
5
Copyright Statement
©
The Author 2017. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/
4.0/), which permits
unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
The Author 2017. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/
4.0/), which permits
unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Sponsor
Commission of the European Communities
Medical Research Council
Imperial College Healthcare NHS Trust- BRC Funding
Grant Number
305312
1583045
RDB20
Subjects
01 Mathematical Sciences
06 Biological Sciences
08 Information And Computing Sciences
Bioinformatics
Publication Status
Published