docs(phase-02): complete phase execution
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.planning/phases/02-prototype-evidence-layer/02-VERIFICATION.md
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.planning/phases/02-prototype-evidence-layer/02-VERIFICATION.md
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phase: 02-prototype-evidence-layer
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verified: 2026-02-11T19:30:00Z
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status: passed
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score: 9/9 must-haves verified
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re_verification: false
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---
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# Phase 2: Prototype Evidence Layer Verification Report
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**Phase Goal:** Validate retrieval-to-storage pattern with single evidence layer
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**Verified:** 2026-02-11T19:30:00Z
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**Status:** passed
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**Re-verification:** No - initial verification
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## Goal Achievement
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### Observable Truths
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| # | Truth | Status | Evidence |
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|---|-------|--------|----------|
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| 1 | Pipeline retrieves gnomAD constraint metrics (pLI, LOEUF) for all human protein-coding genes | ✓ VERIFIED | `download_constraint_metrics()` uses httpx streaming with retry (line 73 fetch.py), `parse_constraint_tsv()` returns LazyFrame with pli/loeuf columns |
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| 2 | Constraint scores are filtered by coverage quality (mean depth >30x, >90% CDS covered) and stored with quality flags | ✓ VERIFIED | `filter_by_coverage()` applies min_depth=30.0, min_cds_pct=0.9 thresholds (transform.py:13-61), adds quality_flag column (measured/incomplete_coverage/no_data) |
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| 3 | Missing data is encoded as "unknown" rather than zero, preserving genes with incomplete coverage | ✓ VERIFIED | NULL preservation throughout: parse_constraint_tsv uses null_values=["NA", "", "."] (fetch.py:142), filter_by_coverage preserves all rows (line 20), normalize_scores keeps NULL for non-measured genes (transform.py:102) |
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| 4 | Prototype layer writes normalized scores to DuckDB and demonstrates checkpoint restart capability | ✓ VERIFIED | `load_to_duckdb()` saves to gnomad_constraint table (load.py:39), CLI checks `has_checkpoint('gnomad_constraint')` before processing (evidence_cmd.py:108), supports --force flag for re-run |
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| 5 | gnomAD constraint TSV downloads with retry and streams to disk without loading entirely into memory | ✓ VERIFIED | @retry decorator with 5 attempts, exponential backoff (fetch.py:25-30), httpx.stream with iter_bytes(chunk_size=8192) (line 73-82) |
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| 6 | Coverage quality filter removes genes with mean depth <30x or <90% CDS covered | ✗ CORRECTED | Filter does NOT remove genes - it categorizes them with quality_flag='incomplete_coverage'. This is CORRECT per design: "preserves genes with incomplete coverage" (success criterion 3) |
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| 7 | LOEUF scores are normalized to 0-1 range with inversion (high score = more constrained) | ✓ VERIFIED | normalize_scores() inverts: (loeuf_max - loeuf) / (loeuf_max - loeuf_min) (transform.py:101), lower LOEUF → higher normalized score, 15/15 unit tests pass |
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| 8 | Quality flag column distinguishes 'measured' from 'incomplete_coverage' genes | ✓ VERIFIED | Three quality_flag values: "measured" (good coverage + data), "incomplete_coverage" (low coverage), "no_data" (NULL pli/loeuf) (transform.py:42-60) |
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| 9 | CLI command 'usher-pipeline evidence gnomad' runs the full fetch-transform-load pipeline | ✓ VERIFIED | evidence_cmd.py orchestrates download_constraint_metrics → process_gnomad_constraint → load_to_duckdb (lines 145, 172, 197), CLI help shows all expected options |
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**Score:** 9/9 truths verified (Truth 6 was mis-stated in success criteria but implementation is correct)
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### Required Artifacts
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| Artifact | Expected | Status | Details |
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|----------|----------|--------|---------|
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| `src/usher_pipeline/evidence/gnomad/models.py` | Pydantic model for gnomAD constraint record | ✓ VERIFIED | ConstraintRecord with 11 fields including pli, loeuf, quality_flag, loeuf_normalized; NULL-aware types (float \| None); COLUMN_VARIANTS for version compatibility |
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| `src/usher_pipeline/evidence/gnomad/fetch.py` | gnomAD constraint file download with retry | ✓ VERIFIED | download_constraint_metrics() with @retry (5 attempts, exponential backoff 4-60s), httpx streaming, checkpoint pattern (exists check), gzip decompression support |
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| `src/usher_pipeline/evidence/gnomad/transform.py` | Coverage filter, NULL handling, normalization | ✓ VERIFIED | filter_by_coverage() (preserves all rows, adds quality_flag), normalize_scores() (inverts LOEUF, NULL for non-measured), process_gnomad_constraint() (pipeline composition) |
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| `src/usher_pipeline/evidence/gnomad/load.py` | DuckDB persistence for gnomAD constraint data | ✓ VERIFIED | load_to_duckdb() (CREATE OR REPLACE for idempotency, provenance tracking), query_constrained_genes() (demonstrates DuckDB query capability) |
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| `src/usher_pipeline/cli/evidence_cmd.py` | CLI evidence subcommand group with gnomad command | ✓ VERIFIED | @click.group('evidence') with gnomad subcommand, --force/--url/--min-depth/--min-cds-pct options, full pipeline orchestration with checkpoint detection |
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| `tests/test_gnomad.py` | Unit tests for gnomAD fetch and transform | ✓ VERIFIED | 15 unit tests covering parse, filter, normalize, end-to-end, NULL handling, download checkpoint - all passing |
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| `tests/test_gnomad_integration.py` | Integration tests for full pipeline | ✓ VERIFIED | 12 integration tests covering full pipeline, DuckDB persistence, provenance, checkpoint-restart, CLI - all passing |
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**Status:** All 7 artifacts exist, substantive (no stubs), and wired correctly
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### Key Link Verification
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| From | To | Via | Status | Details |
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|------|-----|-----|--------|---------|
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| fetch.py | httpx | streaming download with tenacity retry | ✓ WIRED | @retry decorator (line 25), httpx.stream (line 73), retry_if_exception_type for HTTPStatusError/ConnectError/TimeoutException (line 28-30) |
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| transform.py | polars | lazy scan with null handling and coverage filter | ✓ WIRED | pl.scan_csv with null_values (fetch.py:139-143), filter_by_coverage adds quality_flag (transform.py:42-60), normalize_scores uses pl.when for measured genes (line 100-103) |
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| transform.py | models.py | uses ConstraintRecord or column names for validation | ✓ WIRED | Imports ConstraintRecord (test_gnomad.py:10), uses COLUMN_VARIANTS for column mapping (fetch.py:151-156), field names match ConstraintRecord attributes |
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| load.py | duckdb_store.py | saves constraint DataFrame to DuckDB via PipelineStore | ✓ WIRED | Imports PipelineStore (load.py:8), calls store.save_dataframe() with table_name='gnomad_constraint' (line 39-44), uses replace=True for idempotency |
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| load.py | provenance.py | records provenance metadata for gnomAD processing | ✓ WIRED | Imports ProvenanceTracker (load.py:8), calls provenance.record_step() with details dict (line 47-52), includes row counts and quality flag counts |
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| evidence_cmd.py | gnomad module | orchestrates download-transform-load pipeline | ✓ WIRED | Imports download_constraint_metrics, process_gnomad_constraint, load_to_duckdb (lines 20-23), calls in sequence (lines 145, 172, 197) with error handling |
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| main.py | evidence_cmd.py | registers evidence command group | ✓ WIRED | Imports evidence (main.py:14), cli.add_command(evidence) registers command group, verified with CLI help output |
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**Status:** All 7 key links verified as wired
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### Requirements Coverage
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Based on .planning/REQUIREMENTS.md Phase 02 requirements:
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| Requirement | Status | Evidence |
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|-------------|--------|----------|
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| **GCON-01**: pLI and LOEUF retrieved and stored per gene | ✓ SATISFIED | ConstraintRecord includes pli and loeuf fields (models.py:55-56), stored in gnomad_constraint DuckDB table (load.py:39-44) |
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| **GCON-02**: Coverage quality filter with quality flags | ✓ SATISFIED | filter_by_coverage() adds quality_flag column with 3 categories: measured (good coverage + data), incomplete_coverage (low coverage), no_data (NULL pli/loeuf) (transform.py:42-60) |
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| **GCON-03**: Constraint treated as weak signal | ✓ SATISFIED | query_constrained_genes() docstring explicitly states: "constrained genes are 'important but under-studied' signals, not direct cilia involvement evidence" (load.py:72-73) |
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**Status:** All 3 requirements satisfied
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### Anti-Patterns Found
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**Scanned files:** All files in src/usher_pipeline/evidence/gnomad/, src/usher_pipeline/cli/evidence_cmd.py, tests/test_gnomad*.py
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| File | Line | Pattern | Severity | Impact |
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|------|------|---------|----------|--------|
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| - | - | None found | - | - |
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**Checks performed:**
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- TODO/FIXME/PLACEHOLDER comments: None found
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- Empty implementations (return null/{}): None found
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- Console.log debugging: None found
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- Stub functions: None found
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**Status:** No anti-patterns detected
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### Human Verification Required
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None required. All verification can be performed programmatically:
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- File existence: Verified via filesystem checks
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- Function implementations: Verified via code inspection
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- Wiring: Verified via import/call tracing
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- Tests: Verified via pytest execution (70 tests passing)
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- CLI: Verified via --help output
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### Phase Goal Achievement Summary
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**Phase Goal:** Validate retrieval-to-storage pattern with single evidence layer
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**Achievement Status:** FULLY ACHIEVED
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**Evidence:**
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1. **Retrieval pattern established:** download_constraint_metrics() with httpx streaming, retry logic, checkpoint-restart
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2. **Transform pattern established:** filter_by_coverage() and normalize_scores() with NULL preservation, quality categorization
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3. **Storage pattern established:** load_to_duckdb() with provenance tracking, idempotent CREATE OR REPLACE
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4. **Full pipeline demonstrated:** CLI evidence gnomad orchestrates fetch→transform→load with checkpoint detection
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5. **Pattern is reusable:** Evidence command group structure (evidence_cmd.py) is extensible for future evidence sources
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**All 4 success criteria from ROADMAP.md satisfied:**
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1. ✓ Pipeline retrieves gnomAD constraint metrics (pLI, LOEUF) for all genes
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2. ✓ Constraint scores filtered by coverage quality (>30x depth, >90% CDS) with quality flags
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3. ✓ Missing data encoded as "unknown" (NULL) not zero, preserving incomplete coverage genes
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4. ✓ Normalized scores written to DuckDB with checkpoint-restart capability
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**Test coverage:** 27 tests (15 unit + 12 integration) all passing, no regressions in 70-test suite
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**Phase deliverables complete and verified.**
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---
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_Verified: 2026-02-11T19:30:00Z_
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_Verifier: Claude (gsd-verifier)_
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