Quantitative mutations using qmut

The package qmut contains mainly a class called QuantitativeMutation to enable the simulation of quantitative mutations of whole genome metabolic reconstructions.

Installation

1. Check that you have cobrapy installed in your environment
2. Download and copy the \cobrapy_qmut folder in your working directory, or
3. Download and run pip install path_to_setup.py_parent_folder

Tutorial

In this tutorial we will show the main applications and methods of the QuantiativeMutation objects, briefly:

1. Load a metabolic model and create its QuantitativeMutation object
2. Using Q.optimize() and Q.slim_optimize() to find solutions and biomass production rate, respectively.
3. Generating random media following the protocol of Wang and Zhang and applying it to Q.
4. Compute maximal bounds of Q across a list of media. And save/load them with Q.load_bounds() and Q.save_bounds()
5. Check how gene reaction rules are quantitatively interpreted.
6. Working with relative gene dosages and quantitative mutations.
7. Compute individuals, and populations in a single or in multiple processors.

Reference

If you find this class useful and you use it in your work, please also cite its paper: The limitations of phenotype prediction in metabolism, Pablo Yubero, Alvar A. Lavin, Juan F. Poyatos bioRxiv 2022.05.19.492732; doi: https://doi.org/10.1101/2022.05.19.492732

Contact

If your have any issue with this repo please contact me through github rather than email. Feel free to ask for updated versions of it as perhaps I miss to keep this repo up to date.