CORPSE is an extension to the CobraPy environment to make some extra functionality - I initiated this because I missed functions for reconstruction of specific models.

The toolset includes functions for:

• mapping gene expression values to reactions
• get essential genes/rxn depending on the global lower and upper and local thresholds
• calculate distances on FVA results for different samples/simulations of the same model
• extract tissue specific models using fastcore

Simply use pip to install the package:

pip install git+https://github.com/Porthmeus/CORPSE.git

Alternatively clone/download the package and install it manually

git clone https://github.com/Porthmeus/CORPSE.git
cd CORPSE
python setup.py install

Here a simple example of how to use fastcore. First we load the E. coli model from cobrapy as a toy model and we take 5 random reactions as a core set.

import cobra.test
from corpse import simpleFastcore
import random

eco = cobra.test.create_test_model("textbook") # load the model
core_eco = random.sample([x.id for x in eco.reactions], 5) # sample 5 reactions

To run fastcore instantiate a fastcore object and call run():

fast_mod = simpleFastcore(model = eco, core_set = core_eco)
core_mod = fast_mod.run()

This will run fastcc and fastcore on the model and return the tissue specific model. One can run also only fastcc or fastcore on the model provided:

# run only fastcc
fast_mod.fastcc()
consist_mod = fast_mod.get_model()

# run only fastcore
fast_mod.fastcore()
core_mod = fast_mod.get_model()

To change the solver for the problems, simply change the solver of the initial model object provided:

eco.solver = "cplex"
fast_mod = simpleFastcore(model = eco, core_set = core_eco)

Write a good documentation with examples how to use the library