Skip to content

Latest commit

 

History

History
19 lines (16 loc) · 2.37 KB

README.md

File metadata and controls

19 lines (16 loc) · 2.37 KB
Raw

Growth Coupling Suite

The Growth Coupling Suite is a framework for computing and analyzing strain designs that couple a target reaction to growth. gcOpt is used as the underlying optimization algorithm for deriving growth-coupled strain design solutions.

Installation

For a detailed installation manual, refer to the "docs" folder in this repository. The Growth Coupling Suite has been tested in Python >3.8. It is recommended to create a virtual python environment with, e.g., conda or virtualenv, for installing and using the Growth Coupling Suite.

  1. Install COBRApy (run pip install cobra) (documentation)
  2. Install the Gurobi solver software under an (academic) license (https://www.gurobi.com/)
  3. Install gurobipy (run pip install gurobipy) (documentation)
  4. If a heterologous reactiond database model needs to be built, install the Equilibrator API (run pip install equilibrator-api) (documentation)
  5. Clone/fork/download this repository
  6. Browse to the main directory of the repository and run python setup.py install or python setup.py develop (for code development purposes)

Use

Refer to and run the example scripts in 'examples' (conduct_gcOpt_optimization_parallel, conduct_gcOpt_optimization_single) for an introduction setting up and using the Growth Coupling Suite.
Once design solutions were found and analyzed with the StrainDesignAnalyzer (part of the Growth Coupling Suite), a summary including unique, valid strain designs and their metadata is saved in an Excel format to the specified location (cf. the parameter 'results_dir' of the 'growth_coupling_summary' function).

Note

The first computation with a new model can be quite time consuming due to the curation of the heterologous reaction database, if heterologous insertions are allowed (num_addins>0 in the gcOpt_config_file). The database will automatically be saved for later applications of that model.
A heterologous reaction database model can be manually built and saved beforehand by using the 'heterologous_reaction_processing' module. Refer to 'tests/create_heterologous_reaction_database_model.ipynb' for a respective example.