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A probabilistic approach Bayesian Quantification for fully automated database-based identification. BQuant also automated quantification of metabolites in local regions of 1H NMR spectra. It represents the spectra as mixtures of reference profiles from a database, and infers the identities and the abundances of metabolites by Bayesian model selection. BQuant outperforms the available automated alternatives in accuracy for both identification and quantification.

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BQuant classification

BQuant specifications

Software type:
Package
Restrictions to use:
None
Programming languages:
R
Computer skills:
Advanced
Stability:
Beta
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
License:
GNU General Public License version 2.0
Version:
1.0
Requirements:
R, mgcv, tmvtnorm, mvtnorm, Matrix, matrixcalc, MCMCpack and RColorBrewer

BQuant support

Documentation

Maintainer

Credits

Publications

  • (Zheng et al., 2011) Identification and quantification of metabolites in (1)H NMR spectra by Bayesian model selection. Bioinformatics.
    PMID: 21398670

Institution(s)

Department of Statistics, Purdue University, West Lafayette, IN, USA; Fred Hutchinson Cancer Research Center, Seattle, WA, USA; School of Medicine, Department of Pediatrics, Indiana University, Indianapolis, IN, USA; Department of Chemistry, Purdue University, West Lafayette, IN, USA; Department of Computer Science, Purdue University, West Lafayette, IN, USA

Funding source(s)

This work was supported by National Institutes of Health (NIH) (grants R01GM085291, 5K23RR019540 and UL1RR025761); Indiana University Signature Center Initiative; Indiana 21st Century Research & Technology Fund; Bisland Dissertation Fellowship from Purdue University.

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