Welcome to SCOOTI: Single-Cell Optimization Objective and Tradeoff Inference.
This guide walks you through setting up the environment and running SCOOTI's MATLAB and Python modules smoothly.
We provide an environment.yml file.
conda env create -f environment.yml
conda activate scooti
This will install all required packages, including numpy, pandas, torch, scanpy, cobra, and others.
If you prefer pip, you can install manually:
pip install -r requirements.txt
Or if installing SCOOTI as a local Python package:
pip install .
Make sure your Python version is 3.10.
python -c "from SCOOTI._version import version; print(version)"
You need MATLAB installed with:
- Optimization Toolbox (
gurobiis required) - Parallel Computing Toolbox (optional, for speedup)
Inside MATLAB:
addpath(genpath('SCOOTI/metabolicModels/'));
addpath(genpath('SCOOTI/metabolicModels/utils/'));
This loads all necessary .m functions (e.g., CFRinterface, run_simulation).
If you are developing SCOOTI (not just using):
- Install in editable mode:
pip install -e .
Now any code changes will take effect immediately without reinstalling.
Before you start, please revise the .json files to access your cobratoolbox:
"COBRA_path": ".YOUR_COBRATOOLBOX_PATH", ...
Example for unconstrained models:
bash ./SCOOTI/run_flux.sh ./SCOOTI/example/unconstrained_demo_config.json
Example for constrained models:
bash ./SCOOTI/run_flux.sh ./SCOOTI/example/constrained_demo_config.json
This will:
- Load a config .json
- Launch CFRinterface(config) to infer fluxes.
Example:
bash example/run_trainer.sh example/demo_trainer_config.json
This will:
- Train regressors with unconstrained and constrained fluxes.
| Issue | Solution |
|---|---|
| ImportError: numpy.dtype size changed | Make sure numpy and numba versions match (use our environment.yml). |
Undefined function (e.g. validate_config) |
Make sure you added ./SCOOTI/metabolicModels/ to MATLAB path. |
| Python package conflicts | Please make sure you installed packages listed in requirements.txt |
SCOOTI/
├── setup.py # Python packaging file
├── environment.yml # Conda environment setup
├── requirements.txt # pip-based dependency list
├── README.md # Project overview and usage
├── setup_instructions.md # Detailed installation and usage guide
│
├── metabolicModels/ # MATLAB modeling code
│ ├── utils/ # Helper MATLAB functions
│ └── (core .m files like CFRinterface.m, multiObj_CBM.m)
│
├── SCOOTI/ # Python modules
│ ├── __init__.py
│ ├── trainer/ # Training scripts (SCOOTI_trainer.py, regressorTraining.py)
│ └── (other Python modules)
│
├── example/ # Example configs and scripts
│ ├── run_flux.sh # Bash script to run MATLAB flux pipeline
│ ├── run_trainer.sh # Bash script to run Python trainer
│ ├── demo_flux_config.json
│ └── demo_trainer_config.json
Please cite this paper if you use SCOOTI in your work.