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>
49 lines
2.0 KiB
Markdown
49 lines
2.0 KiB
Markdown
# Reverso MVP — Sickle Cell Repurposing Pipeline
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A minimum viable drug repurposing pipeline for **sickle cell disease**: build a disease
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signature from public transcriptomic data, build drug profiles for ~300 small molecules,
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and rank them by CMap-style connectivity scoring. Validated by a recovery test — do the two
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known sickle cell drugs (hydroxyurea, L-glutamine) rank near the top?
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See [`PLAN.md`](PLAN.md) for the full specification, locked decisions, and week-by-week build plan.
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## Quickstart
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```bash
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# Requires Python >=3.11,<3.13 (see note below)
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pip install -e . # or: pip install -e ".[dev]" for test/lint tooling
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pytest # run unit tests
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```
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> **Python version note:** use Python 3.11–3.13 (`python3.13 -m venv .venv`). Python 3.14 is
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> not yet supported by all pipeline dependencies (`pydeseq2`, `cmapPy`).
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## Project layout
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```
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data/ raw (downloaded, never edited) / processed / results — gitignored
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notebooks/ 01..05, run end-to-end in order
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src/ identifiers, disease, drugs, scoring, provenance
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tests/ scoring unit tests
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docs/ recovery_test_report.md, data_sources.md, known_limitations.md
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```
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## The deliverable
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When complete, the artifact to share is three files:
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1. `docs/recovery_test_report.md` — the 2-page write-up
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2. `data/results/ranked_candidates_v1.csv` — the ranked drug list
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3. The signature + drug profile files with provenance
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## Pipeline
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| Notebook | Stage | Output |
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|---|---|---|
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| `01_setup_identifiers.ipynb` | Pin disease/gene IDs | `data/processed/identifiers.json` |
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| `02_disease_signature.ipynb` | GEO + differential expression | `sickle_cell_signature_v1.json` |
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| `03_drug_profiles.ipynb` | ChEMBL + LINCS | `drug_profiles_v1.parquet` |
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| `04_connectivity_scoring.ipynb` | CMap scoring | `ranked_candidates_v1.csv` |
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| `05_recovery_test.ipynb` | Validation | `docs/recovery_test_report.md` |
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Every persisted artifact carries a **confidence tier** (A/B/C) and provenance. See `PLAN.md` §3.
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