Multivariate thermodynamics-based metabolic flux analysis in Python.
Project description
We present multiTFA, a multivariate thermodynamics-based metabolic flux analysis package for Python. The framework takes advantage of the reactions’ Gibbs free energy covariance matrix to tightly constrain metabolic models using thermodynamic constraints. It represents an improvement over a previous thermodynamic metabolic flux analysis (tMFA) method described in [1].
This implementation requires a COBRA model as input, as well as additional compartment conditions and metabolite concentrations. It allows user to perform various thermodynamic analyses on COBRA models, such as thermodynamic metabolic flux analysis, variability analysis, or flux sampling. Please see below for further details.
Install
To install multitfa from PyPI is as simple as: (We recommend using a virtual environment).
pip install multitfa
To install from source,
git clone https://github.com/biosustain/multitfa.git
cd multitfa
pip install .
We highly recommend the installing CPLEX. Although we support GUROBI solver, we noticed that it is slower and often stuck when solving quadratic constraint problems.
Please note, Installation takes upto 3 GB. This is to accomodate equilibrator-api database files.
Install Requirements
Installation requires
cobra
depinfo
optlang<1.4.6
numpy
scipy
pandas
equilibrator-api==0.3.2b7
component-contribution==0.3.2b4
equilibrator-cache==0.3.2b2
Usage
The documentation is available online at readthedocs.
Copyright
Copyright © 2018, Novo Nordisk Foundation Center for Biosustainability.
Free software distributed under the Apache Software License 2.0.
Cite us
If you use multitfa in a scientific publication, please cite doi:10.1101/2020.12.01.407387.
References
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