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 2 complete — ready for Phase 3

Current Position

Phase: 3 of 6 (Core Evidence Layers) Plan: 3 of 6 in current phase (03-03 complete) Status: In progress — 03-03 complete (protein features) Last activity: 2026-02-11 — Completed 03-03-PLAN.md (Protein Features evidence layer)

Progress: [█████░░░░░] 45.0% (9/20 plans complete across all phases)

Performance Metrics

Velocity:

Total plans completed: 9
Average duration: 5.2 min
Total execution time: 0.78 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
03 - Core Evidence Layers	3/6	27 min	9.0 min/plan
Phase 03 P03	11 min	2 tasks	7 files
Phase 03 P04	8 min	2 tasks	8 files
Phase 03 P05	10 min	2 tasks	8 files

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)
[03-01]: Annotation tier thresholds: Well >= (20 GO AND 4 UniProt), Partial >= (5 GO OR 3 UniProt)
[03-01]: Composite annotation score weighting: GO 50%, UniProt 30%, Pathway 20%
[03-01]: NULL GO counts treated as zero for tier classification but preserved as NULL in data (conservative assumption)
[03-03]: UniProt REST API with batching (100 accessions) over bulk download for flexibility
[03-03]: InterPro API for supplemental domain annotations (10 req/sec rate limit)
[03-03]: Keyword-based cilia motif detection over ML for explainability (IFT, BBSome, ciliary, etc.)
[03-03]: Composite protein score weights: length 15%, domain 20%, coiled-coil 20%, TM 20%, cilia 15%, scaffold 10%
[03-03]: List(Null) edge case handling for proteins with no domains (cast to List(String))
[03-04]: Evidence type terminology standardized to computational (not predicted) for consistency with bioinformatics convention
[03-04]: Proteomics absence stored as False (informative negative) vs HPA absence as NULL (unknown/not tested)
[03-04]: Curated proteomics reference gene sets (CiliaCarta, Centrosome-DB) embedded as Python constants for simpler deployment
[03-04]: Computational evidence (HPA Uncertain/Approved) downweighted to 0.6x vs experimental (Enhanced/Supported, proteomics) at 1.0x
[Phase 03-05]: Ortholog confidence based on HCOP support count (HIGH: 8+, MEDIUM: 4-7, LOW: 1-3)
[Phase 03-05]: NULL score for genes without orthologs (preserves NULL pattern)

Pending Todos

None yet.

Blockers/Concerns