BATMAN
Version: 1.2.12.1
Short Description
Bayesian AuTomated Metabolite Analyser for NMR spectra (BATMAN).
Description
BATMAN: open source software for batch metabolites NMR resonance peak fitting.
BATMAN deconvolves resonance peaks from NMR spectra of complex mixtures and obtains concentration estimates for the corresponding metabolites automatically. This is achieved through a database of spectral profiles for known metabolites and a Bayesian Markov Chain Monte Carlo algorithm.
Users have the options to specify the multiplet ppm position, position shift range, peak width range and so on. Parallel processing is available if processing several spectra. The installation and testing instructions can be found at: http://batman.r-forge.r-project.org/.
Key features
- NMR Processing
Functionality
- Annotation / NMR
- Post-processing
Approaches
- Metabolomics / Targeted
?
Instrument Data Types
- NMR / 1D NMR
Screenshots
Screen shots obtained from the original BATMAN page.
Tool Authors
- Jie Hao (Imperial College London)
- William Astle
- Maria De Iorio (University College London)
- Timothy Ebbels (Imperial College London)
Container Contributors
- Jianliang Gao (Imperial College London)
Website
- http://batman.r-forge.r-project.org/
Git Repository
- https://github.com/phnmnl/container-batman.git
Installation
For local individual installation:
docker pull docker-registry.phenomenal-h2020.eu/phnmnl/batman
Usage Instructions
For direct docker usage:
docker run docker-registry.phenomenal-h2020.eu/phnmnl/batman ...
More detail can be found at:
- https://jianlianggao.github.io/batman
Publications
-
Hao, J., et al., BATMAN - an R package for the automated quantification of metabolites from nuclear magnetic resonance spectra using a Bayesian model. Bioinformatics, 2012. 28(15): p. 2088-90. http://bioinformatics.oxfordjournals.org/content/28/15/2088
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Astle, W., et al., A Bayesian Model of NMR Spectra for the Deconvolution and Quantification of Metabolites in Complex Biological Mixtures. Journal of the American Statistical Association, 2012. 107(500): p. 1259-1271. http://www.tandfonline.com/doi/abs/10.1080/01621459.2012.695661#.UgEf-hbZa4k.