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BATMAN / Bayesian AuTomated Metabolite Analyser for NMR data
An R package for estimating metabolite concentrations from Nuclear Magnetic Resonance spectral data using a specialised MCMC algorithm. BATMAN deconvolutes peaks from 1-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 (MCMC) 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.
BQuant / Bayesian Quantification
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.
Identifies metabolites in H-NMR spectra of complex mixtures. MetaboHunter is a web-server application based on two manually curated reference libraries. The software provides three distinct methods: (i) a scoring function, (ii) an iterative greedy selective approach and, (iii) selection approaches with a user adjustable chemical peak drift parameter. There are 4 functional views: (i) a Processing View, (ii) a Search Results View, (iii) a Plot View and, (iv) a Peaks Hit Map view.
Features an evolutionary algorithm for structure elucidation and is available as a graphical user interface (GUI) client or as a stand-alone command-line executable. The SENECA system is an open-source java-based desktop application to perform Computer Assisted Structure Elucidation (CASE) for organic molecules. It takes a molecular formula generated from high resolution mass spectrometry and spectral data from a suite of nuclear magnetic resonance (NMR) experiments and performs a stochastic search in the constitutional space, guided by a fitness function.
HiRes / High Resolution spectroscopy
Combines standard nuclear magnetic resonance (NMR) spectral processing functionalities with techniques for multi-spectral dataset analysis. HiRes contains extensive abilities for data cleansing, such as baseline correction, solvent peak suppression, removal of frequency shifts owing to experimental conditions as well as auxiliary information management. It couples rigorous data pre-processing, artifact removal and identification of metabolic patterns via principal component analysis (PCA).
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