# 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`](PLAN.md) for the full specification, locked decisions, and week-by-week build plan.

## Quickstart

```bash
# 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.