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Junior B. b731478f5d Scaffold Reverso MVP pipeline structure

Set up the project skeleton per PLAN.md §4:
- src/ package: identifiers, disease, drugs, scoring, provenance
  with pydantic schemas and confidence-tier logic (working);
  data-pull/compute functions stubbed per their build week
- 5 starter notebooks (01-05) with PLAN-referenced steps
- tests/test_scoring.py: tier-assignment tests pass; scoring
  reference test xfail until Week 3
- docs/: recovery_test_report, data_sources, known_limitations skeletons
- pyproject.toml (requires-python >=3.11,<3.14), .gitignore, README
- data/ tree preserved via .gitkeep; raw/processed/results gitignored

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

2026-06-23 20:20:09 +02:00

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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:

docs/recovery_test_report.md — the 2-page write-up
data/results/ranked_candidates_v1.csv — the ranked drug list
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.