BATMAN--an R package for the automated quantification of metabolites from nuclear magnetic resonance spectra using a Bayesian model.
BACKGROUND
Nuclear Magnetic Resonance (NMR) spectra are widely used in metabolomics to obtain metabolite profiles in complex biological mixtures. Common methods used to assign and estimate concentrations of metabolites involve either an expert manual peak fitting or extra pre-processing steps, such as peak alignment and binning. Peak fitting is very time consuming and is subject to human error. Conversely, alignment and binning can introduce artefacts and limit immediate biological interpretation of models.


RESULTS
We present the Bayesian automated metabolite analyser for NMR spectra (BATMAN), an R package that deconvolutes peaks from one-dimensional NMR spectra, automatically assigns them to specific metabolites from a target list and obtains concentration estimates. The Bayesian model incorporates information on characteristic peak patterns of metabolites and is able to account for shifts in the position of peaks commonly seen in NMR spectra of biological samples. It applies a Markov chain Monte Carlo algorithm to sample from a joint posterior distribution of the model parameters and obtains concentration estimates with reduced error compared with conventional numerical integration and comparable to manual deconvolution by experienced spectroscopists.


METHODS
http://www1.imperial.ac.uk/medicine/people/t.ebbels/


BACKGROUND
t.ebbels@imperial.ac.uk.
Section of Biomolecular Medicine, Department of Surgery and Cancer, Sir Alexander Fleming Building, Imperial College London, London SW7 2AZ, UK.
Jie
J
Hao
William
W
Astle
Maria
M
De Iorio
Timothy M D
TM
Ebbels
D000465:Algorithms; D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008390:Markov Chains; D055432:Metabolomics / Q000379:methods*; D009010:Monte Carlo Method; D012984:Software