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arXiv · 1310.7226

ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS based metabolomics

Ricardo R. Silva·Fabien Jourdan·Diego M. Salvanha·Fabien Letisse·Emilien L. Jamin·Simone Guidetti-Gonzalez·Carlos A. Labate·Ricardo Z. N. Vêncio
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Abstract

We present ProbMetab, an R package which promotes substantial improvement in automatic probabilistic LC-MS based metabolome annotation. The inference engine core is based on a Bayesian model implemented to: (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and; (ii) allow sensitive selection of biologically meaningful biochemical reactions databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the annotation in a network where observed mass peaks are connected if their candidate metabolites are substrate/product of known biochemical reactions. This graph can be overlaid with other graph-based analysis, such as partial correlation networks, in a visualization scheme exported to Cytoscape, with web and stand alone versions. ProbMetab was implemented in a modular fashion to fit together with established upstream (xcms, CAMERA, AStream, mzMatch.R, etc) and downstream R package tools (GeneNet, RCytoscape, DiffCorr, etc). ProbMetab, along with extensive documentation and case studies, is freely available under GNU license at: http://labpib.fmrp.usp.br/methods/probmetab/.

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BibTeXRIS

Ricardo R. Silva, Fabien Jourdan, Diego M. Salvanha, Fabien Letisse, Emilien L. Jamin, Simone Guidetti-Gonzalez, Carlos A. Labate, Ricardo Z. N. Vêncio. 2013-10-27. ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS based metabolomics. https://doi.org/10.1093/bioinformatics%2Fbtu019

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