Mummichog
=========
Mummichog is a Python program for analyzing data from high throughput, untargeted metabolomics.
It leverages the organization of metabolic networks to predict functional activity directly from feature tables,
bypassing metabolite identification. The features include
* computing significantly enriched metabolic pathways
* identifying significant modules in the metabolic network
* visualization of top networks in web browser
* visualization that also plugs into Cytoscape
* tentative annotations
* metabolic models for different species through plugins
This is mummichog package version 2. Version 3 is under development.
Please note that mummichog-server is a different package/repository.
Installation
------------
Mummichog can be installed using pip (pip Installs Packages), the Python package manager. The command below will install the default (version 2):
pip install mummichog
This is OS independent. To read more on [pip here](https://pip.pypa.io/en/stable/installing/#installing-with-get-pip-py).
One can also run mummichog without installing it. Direct python call on a downloaded copy can work, e.g.
python3 -m mummichog.main -f mummichog/tests/testdata0710.txt -o t2
Use custom metabolic model
--------------------------
The `-n` argument now (v2.6) takes user specified metabolic model in JSON format, e.g.
python3 -m mummichog.main -n mummichog/tests/metabolicModel_RECON3D_20210510.json -f mummichog/tests/testdata0710.txt -o t3
The porting of metabolic model is demonstrated
[here https://github.com/shuzhao-li/Azimuth/blob/master/docs/](https://github.com/shuzhao-li/Azimuth/blob/master/docs/From-GEM-to-metDataModel-20210510.ipynb)
Please note that identifier conversion is a major issue in genome scale models. Users benefit greatly from including chemical formula (neutral_formula) and molecular weight (neutral_mono_mass) in the model.
History
-------
*Python 3 is required for Mummichog version 2.3 and beyond.*
*Mummichog version 2.2 was the last version using Python 2; new branch as mummichog-python2*
The initial paper on mummichog is described in Li et al. Predicting Network Activity from High Throughput Metabolomics. PLoS Computational Biology (2013); doi:10.1371/journal.pcbi.1003123.
More on [project website http://mummichog.org](http://mummichog.org).
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"description": "Mummichog\n=========\n\nMummichog is a Python program for analyzing data from high throughput, untargeted metabolomics.\nIt leverages the organization of metabolic networks to predict functional activity directly from feature tables,\nbypassing metabolite identification. The features include\n\n* computing significantly enriched metabolic pathways\n* identifying significant modules in the metabolic network\n* visualization of top networks in web browser\n* visualization that also plugs into Cytoscape\n* tentative annotations\n* metabolic models for different species through plugins\n\nThis is mummichog package version 2. Version 3 is under development.\n\nPlease note that mummichog-server is a different package/repository.\n\n\nInstallation\n------------\n\nMummichog can be installed using pip (pip Installs Packages), the Python package manager. The command below will install the default (version 2):\n\n pip install mummichog\n\nThis is OS independent. To read more on [pip here](https://pip.pypa.io/en/stable/installing/#installing-with-get-pip-py).\n\nOne can also run mummichog without installing it. Direct python call on a downloaded copy can work, e.g.\n\n python3 -m mummichog.main -f mummichog/tests/testdata0710.txt -o t2\n\n\nUse custom metabolic model\n--------------------------\n\nThe `-n` argument now (v2.6) takes user specified metabolic model in JSON format, e.g.\n\n python3 -m mummichog.main -n mummichog/tests/metabolicModel_RECON3D_20210510.json -f mummichog/tests/testdata0710.txt -o t3\n\nThe porting of metabolic model is demonstrated \n[here https://github.com/shuzhao-li/Azimuth/blob/master/docs/](https://github.com/shuzhao-li/Azimuth/blob/master/docs/From-GEM-to-metDataModel-20210510.ipynb)\n\nPlease note that identifier conversion is a major issue in genome scale models. Users benefit greatly from including chemical formula (neutral_formula) and molecular weight (neutral_mono_mass) in the model.\n\n\nHistory\n-------\n\n*Python 3 is required for Mummichog version 2.3 and beyond.*\n\n*Mummichog version 2.2 was the last version using Python 2; new branch as mummichog-python2*\n\nThe initial paper on mummichog is described in Li et al. Predicting Network Activity from High Throughput Metabolomics. PLoS Computational Biology (2013); doi:10.1371/journal.pcbi.1003123. \n\nMore on [project website http://mummichog.org](http://mummichog.org).\n",
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