Reverso MVP — Sickle Cell Repurposing Pipeline

A minimum viable drug repurposing pipeline for sickle cell disease: build a disease signature from public transcriptomic data, build drug profiles for ~300 small molecules, and rank them by CMap-style connectivity scoring. Validated by a recovery test — do the two known sickle cell drugs (hydroxyurea, L-glutamine) rank near the top?

See PLAN.md for the full specification, locked decisions, and week-by-week build plan.

Quickstart

# Requires Python >=3.11,<3.13 (see note below)
pip install -e .            # or: pip install -e ".[dev]" for test/lint tooling
pytest                      # run unit tests

Python version note: use Python 3.11–3.13 (python3.13 -m venv .venv). Python 3.14 is not yet supported by all pipeline dependencies (pydeseq2, cmapPy).

Project layout

data/         raw (downloaded, never edited) / processed / results — gitignored
notebooks/    01..05, run end-to-end in order
src/          identifiers, disease, drugs, scoring, provenance
tests/        scoring unit tests
docs/         recovery_test_report.md, data_sources.md, known_limitations.md

The deliverable

When complete, the artifact to share is three files:

1. docs/recovery_test_report.md — the 2-page write-up
2. data/results/ranked_candidates_v1.csv — the ranked drug list
3. The signature + drug profile files with provenance

Pipeline

Notebook	Stage	Output
01_setup_identifiers.ipynb	Pin disease/gene IDs	data/processed/identifiers.json
02_disease_signature.ipynb	GEO + differential expression	sickle_cell_signature_v1.json
03_drug_profiles.ipynb	ChEMBL + LINCS	drug_profiles_v1.parquet
04_connectivity_scoring.ipynb	CMap scoring	ranked_candidates_v1.csv
05_recovery_test.ipynb	Validation	docs/recovery_test_report.md

Every persisted artifact carries a confidence tier (A/B/C) and provenance. See PLAN.md §3.