Your browser doesn't support javascript.
loading
MWASTools: an R/bioconductor package for metabolome-wide association studies.
Rodriguez-Martinez, Andrea; Posma, Joram M; Ayala, Rafael; Neves, Ana L; Anwar, Maryam; Petretto, Enrico; Emanueli, Costanza; Gauguier, Dominique; Nicholson, Jeremy K; Dumas, Marc-Emmanuel.
  • Rodriguez-Martinez A; Department of Surgery and Cancer, Computational and Systems Medicine, Imperial College London, UK.
  • Posma JM; Department of Surgery and Cancer, Computational and Systems Medicine, Imperial College London, UK.
  • Ayala R; Department of Surgery and Cancer, Computational and Systems Medicine, Imperial College London, UK.
  • Neves AL; Department of Surgery and Cancer, Computational and Systems Medicine, Imperial College London, UK.
  • Anwar M; Division of Myocardial Function, National Heart and Lung Institute, Imperial College London, UK.
  • Petretto E; Duke-NUS Medical School, Singapore.
  • Emanueli C; Division of Myocardial Function, National Heart and Lung Institute, Imperial College London, UK.
  • Gauguier D; Bristol Heart Institute, University of Bristol, UK.
  • Nicholson JK; Department of Surgery and Cancer, Computational and Systems Medicine, Imperial College London, UK.
  • Dumas ME; Department of Surgery and Cancer, Computational and Systems Medicine, Imperial College London, UK.
Bioinformatics ; 34(5): 890-892, 2018 03 01.
Article en En | MEDLINE | ID: mdl-28961702
ABSTRACT

Summary:

MWASTools is an R package designed to provide an integrated pipeline to analyse 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 metabolome-wide association studies results. Availability and implementation The MWASTools R package is implemented in R (version > =3.4) and is available from Bioconductor https//bioconductor.org/packages/MWASTools/. Contact m.dumas@imperial.ac.uk. Supplementary information Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Metaboloma / Metabolómica Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2018 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Metaboloma / Metabolómica Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Año: 2018 Tipo del documento: Article