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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.
An extensible web component that can be easily integrated in current web applications and databases, providing NMR processing and visualization functionalities. NMRPro is highly extensible to include new functionalities according to the needs of each application. It integrates server-side processing with client-side interactive visualization through three parts: a python package to efficiently process large NMR datasets on the server-side, a Django App managing server-client interaction, and SpecdrawJS for client-side interactive visualization.
dataChord Spectrum Analyst
Provides a rapid workflow from raw Nuclear Magnetic Resonance (NMR) data to patent and publication quality output. dataChord Spectrum Analyst is a graphic application for small molecule NMR Analysis that provides a variety of analytical tools for interpreting NMR Spectra. It can work in a client server mode with the spectrum server maintaining an archive of annotated raw data. This module can compare multiple spectra with each other and generates reports that include a variety of information, including molecular structures.
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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