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Runbook

End-to-end reproduction in ten commands or fewer.

Before running: the package does not currently import - see the Status section in README.md. The sequence below is the intended flow once those imports are fixed.

Complete run

# 1. Setup
conda env create -f environment.yml && conda activate syndrumnet
pip install -e .

# 2. Build all data (first time only, ~2-4 hours)
python scripts/build_all_data.py --config configs/default.yaml

# 3. Run the full pipeline (~1-2 hours)
python scripts/run_pipeline.py --config configs/default.yaml

# 4. Evaluate against known synergies
python scripts/evaluate.py --config configs/default.yaml

# 5. Generate all figures
python scripts/make_figures.py --config configs/default.yaml

# 6. View results
cat reports/tables/evaluation_summary.csv
ls reports/figures/

Or simply make all, which chains steps 2-5.

Optional:

pytest tests/ -v        # run the test suite
make appendix           # build Appendix_Code.pdf (requires pandoc + xelatex)

Expected runtime

Stage Time
Data download 1-2 hours (one-time)
Data preprocessing 30-60 minutes (one-time)
Pipeline execution 1-2 hours per run
Figure generation 5-10 minutes
First run, total ~3-5 hours
Subsequent runs ~1-2 hours (data cached)

Expected outputs

Path Contents
reports/tables/predictions_<disease>.csv One file per disease, all drug pair scores
reports/tables/evaluation_summary.csv AUC-ROC / AUC-PR per disease
reports/figures/*.png ~15-20 figures at 300 dpi
logs/*.log Detailed execution logs

Troubleshooting

Out of memory. Reduce n_cores in the config, or process diseases one at a time with repeated --diseases flags.

Download failures. Some sources need registration (PhosphoSitePlus). Retry partial downloads with python scripts/build_all_data.py --retry-failed.

Reproducibility. Keep random_seed fixed in the config; data source versions are logged to data/raw/VERSIONS.txt during the build.