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gbanyan a0388cf4e1 docs(02-02): complete gnomAD evidence layer integration plan

- DuckDB persistence: gnomad_constraint table with CREATE OR REPLACE (idempotent)
- CLI evidence command: usher-pipeline evidence gnomad with checkpoint-restart
- Provenance tracking: records processing steps, saves sidecar JSON
- Query helpers: query_constrained_genes validates GCON-03 interpretation
- 12 integration tests: end-to-end pipeline, checkpoint, provenance, CLI
- Phase 2 complete: Evidence layer pattern established for future sources
- Duration: 4 min, 2 tasks, 5 files, 70 tests passing

Phase 2 (Prototype Evidence Layer) complete.

2026-02-11 18:23:32 +08:00

3.6 KiB

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Project State

Project Reference

See: .planning/PROJECT.md (updated 2026-02-11)

Core value: Produce a high-confidence, multi-evidence-backed ranked list of under-studied cilia/Usher candidate genes that is fully traceable — every gene's inclusion is explainable by specific evidence, and every gap is documented. Current focus: Phase 1 complete — ready for Phase 2

Current Position

Phase: 2 of 6 (Prototype Evidence Layer) Plan: 2 of 2 in current phase (phase complete) Status: Phase 2 complete - ready for Phase 3 Last activity: 2026-02-11 — Completed 02-02: gnomAD evidence layer integration (DuckDB persistence, CLI, checkpoint-restart)

Progress: [█████░░░░░] 33.3% (2/6 phases complete)

Performance Metrics

Velocity:

Total plans completed: 6
Average duration: 3.7 min
Total execution time: 0.37 hours

By Phase:

Phase	Plans	Total	Avg/Plan
01 - Data Infrastructure	4/4	14 min	3.5 min/plan
02 - Prototype Evidence Layer	2/2	8 min	4.0 min/plan

Accumulated Context

Decisions

Decisions are logged in PROJECT.md Key Decisions table. Recent decisions affecting current work:

Python over R/Bioconductor for rich data integration ecosystem
Weighted rule-based scoring over ML for explainability
Public data only for reproducibility
Modular CLI scripts for flexibility during development
Virtual environment required for dependency isolation (01-01: PEP 668 externally-managed Python)
Auto-creation of directories on config load (01-01: data_dir, cache_dir field validators)
[01-02]: Warn on gene count outside 19k-22k range but don't fail (allows for Ensembl version variations)
[01-02]: HGNC success rate is primary validation gate (UniProt mapping tracked but not used for pass/fail)
[01-02]: Take first UniProt accession when multiple exist (simplifies data model)
[01-02]: Mock mygene in tests (avoids rate limits, ensures reproducibility)
[01-03]: DuckDB over SQLite for DataFrame storage (native polars/pandas integration, better analytics)
[01-03]: Provenance sidecar files alongside outputs (co-located metadata, bioinformatics standard pattern)
[01-04]: Click for CLI framework (standard Python CLI library with excellent UX)
[01-04]: Setup command uses checkpoint-restart pattern (gene universe fetch can take minutes)
[01-04]: Mock mygene in integration tests (avoids external API dependency, reproducible)
[02-01]: httpx over requests for streaming downloads (async-native, cleaner API)
[02-01]: structlog for structured logging (JSON-formatted, context-aware)
[02-01]: LOEUF normalization with inversion (lower LOEUF = more constrained = higher 0-1 score)
[02-01]: Quality flags instead of filtering (preserve all genes with measured/incomplete_coverage/no_data categorization)
[02-01]: NULL preservation pattern (unknown constraint != zero constraint, must not be conflated)
[02-01]: Lazy polars evaluation (LazyFrame until final collect() for query optimization)
[02-02]: load_to_duckdb uses CREATE OR REPLACE for idempotency (safe to re-run)
[02-02]: CLI evidence command group for extensibility (future evidence sources follow same pattern)
[02-02]: Checkpoint at table level (has_checkpoint checks DuckDB table existence)
[02-02]: Integration tests with synthetic fixtures (no external downloads, fast, reproducible)

Pending Todos

None yet.

Blockers/Concerns