This repository holds the source code for metabomodules, a Linux/macOS command-line toolbox to for automatic metabolite identification in 1D NMR data using unsupervised clustering.
To get a copy of the source code run:
$ git clone --recursive https://github.com/BergmannLab/metabomodules-docker
Either docker or singularity must be installed. Please visit https://www.docker.com or http://singularity.lbl.gov
The tool was tested on Ubuntu Linux 18.04, CentOS Linux 7.5 and macOS Sierra Version 10.12.
To install: ./install.sh
To uninstall: ./uninstall.sh
To get help with running the tool, install then invoke, from any location: metabomodules --help
For example: metabomodules --input=/tmp/input.csv --container=docker
In input, provide pre-processed (aligned) 1D NMR data in a tabular form (peak list)
- firt row: PPM axis
- first column: sample id
- each cell i,j, contains the area under the peak found at PPM i for sample j
The following methods will be applied to the input data in order to automatically identify metabolites
- ISA: Iterative Signature Algorithm
- ACP: Average Correlation Profiles Method
- PCA: Principal Component Analysis
Khalili, Bita & Tomasoni, Mattia & Mattei, Mirjam & Mallol Parera, Roger & Sonmez, Reyhan & Krefl, Daniel & Rueedi, Rico & Bergmann, Sven. (2019). Automated analysis of large-scale NMR data generates metabolomic signatures and links them to candidate metabolites. 10.1101/613935.