2ab25ef5c2
feat(05-03): implement CLI report command
...
- Create report_cmd.py following established CLI pattern
- Orchestrate full output pipeline: tiering, evidence summary, dual-format output, visualizations, reproducibility reports
- Support --output-dir, --force, --skip-viz, --skip-report flags
- Configurable tier thresholds (--high-threshold, --medium-threshold, --low-threshold, --min-evidence-high, --min-evidence-medium)
- Register report command in main.py CLI entry point
- Follow score_cmd.py pattern: config load, store init, checkpoint check, pipeline steps, summary display, cleanup
- CLI now has 5 commands: setup, evidence, score, report, info
2026-02-12 04:05:52 +08:00
5f14dc2e64
docs(05-02): complete visualization and reproducibility report plan
...
- Plan 05-02 executed successfully
- 2 tasks completed with 2 commits
- 13 tests passing (6 visualization + 7 reproducibility)
- 4 files created, 2 files modified
- Duration: 5 minutes
- Updated STATE.md with progress (17/20 plans complete, 85%)
2026-02-12 04:03:08 +08:00
434c79c0a8
docs(05-01): complete output generation core plan
...
- Add 05-01-SUMMARY.md with performance metrics and decisions
- Update STATE.md to Phase 5, Plan 1 of 3 (80% overall progress)
- Record key decisions: configurable tiers, dual-format output, YAML provenance
- Document deviation: pl.count() -> pl.len() deprecation fix
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-02-12 04:01:24 +08:00
5af63eab46
feat(05-02): implement reproducibility report module with JSON and Markdown output
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- Create ReproducibilityReport dataclass with all metadata fields
- Implement generate_reproducibility_report function
- Extract parameters from PipelineConfig (scoring weights, data versions)
- Capture software environment (Python, polars, duckdb versions)
- Build filtering steps from ProvenanceTracker
- Compute tier statistics from tiered DataFrame
- Support optional validation metrics
- to_json: write as indented JSON for machine-readable format
- to_markdown: write with tables and headers for human-readable format
- 7 tests covering all report fields, formats, and edge cases
2026-02-12 04:00:21 +08:00
4e46b488f1
feat(05-01): add dual-format writer with provenance and tests
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- Implement TSV+Parquet writer with deterministic output sorting
- Generate YAML provenance sidecar with statistics and metadata
- Add comprehensive unit tests (9 tests covering all functionality)
- Fix deprecated pl.count() -> pl.len() usage
2026-02-12 03:59:26 +08:00
150417ffcc
feat(05-02): implement visualization module with matplotlib/seaborn plots
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- Add matplotlib>=3.8.0 and seaborn>=0.13.0 to dependencies
- Create visualizations.py with 3 plot functions and orchestrator
- plot_score_distribution: histogram colored by confidence tier
- plot_layer_contributions: bar chart of evidence layer coverage
- plot_tier_breakdown: pie chart of tier distribution
- Use Agg backend for headless/CLI safety
- All plots saved at 300 DPI with proper figure cleanup
- 6 tests covering file creation, edge cases, and return values
2026-02-12 03:57:50 +08:00
d2ef3a2b84
feat(05-01): implement tiering logic and evidence summary module
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- Add confidence tier classification (HIGH/MEDIUM/LOW) based on composite_score and evidence_count
- Add supporting_layers and evidence_gaps columns per gene
- Use vectorized polars expressions for performance
- Configurable thresholds for tier assignment
2026-02-12 03:56:42 +08:00
6ab7fd1378
docs(05-output-cli): create phase plan
2026-02-11 21:14:37 +08:00
1799906138
docs(05): research phase output-cli domain
2026-02-11 21:07:56 +08:00
de678858cd
docs(phase-04): complete phase execution
2026-02-11 21:01:50 +08:00
386fbf51b2
docs(04-03): complete CLI score command and tests plan
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- SUMMARY.md: CLI orchestration with checkpoint-restart + 10 comprehensive tests
- STATE.md: Updated position (Phase 4 complete), progress (75%), velocity, decisions
- Duration: 3 minutes, 2 tasks, 4 files (3 created, 1 modified)
2026-02-11 20:56:31 +08:00
a6ad6c6d19
test(04-03): add unit and integration tests for scoring module
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- test_scoring.py: 7 unit tests for known genes, weight validation, NULL preservation
- test_scoring_integration.py: 3 integration tests for end-to-end pipeline with synthetic data
- Tests verify NULL handling (genes with no evidence get NULL composite score)
- Tests verify known genes rank highly when given high scores
- Tests verify QC detects missing data above thresholds
- All tests use synthetic data (no external API calls, fast, reproducible)
2026-02-11 20:54:39 +08:00
d57a5f2826
feat(04-03): add CLI score command with checkpoint-restart
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- Created score_cmd.py following evidence_cmd.py pattern
- Orchestrates full scoring pipeline: known genes -> composite scores -> QC -> validation
- Options: --force, --skip-qc, --skip-validation for flexible iteration
- Registered score command in main CLI group
- Displays comprehensive summary with quality flag distribution
2026-02-11 20:52:37 +08:00
c501951b0f
docs(04-02): complete QC and validation plan
...
- Add SUMMARY for quality control and positive control validation
- Update STATE.md: Plan 2 of 3 in Phase 04 complete
- Progress: 70% (14/20 plans complete)
- Decisions: scipy MAD outlier detection, PERCENT_RANK validation
2026-02-11 20:50:00 +08:00
70a5d6eff8
feat(04-02): implement positive control validation
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- Create validation.py with known gene ranking validation
- validate_known_gene_ranking: PERCENT_RANK window function over all genes
- Computes median percentile, top quartile count/fraction for known genes
- generate_validation_report: human-readable text output with formatted table
- Update __init__.py to export run_qc_checks, validate_known_gene_ranking, generate_validation_report
2026-02-11 20:47:59 +08:00
ba2f97ac55
feat(04-02): implement QC checks for scoring results
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- Add scipy>=1.14 dependency for MAD-based outlier detection
- Create quality_control.py with 4 QC functions
- compute_missing_data_rates: NULL rate detection with warn/error thresholds
- compute_distribution_stats: mean/median/std per layer with anomaly detection
- detect_outliers: MAD-based robust outlier detection (>3 MAD)
- run_qc_checks: orchestrator with composite score percentiles
2026-02-11 20:46:57 +08:00
71c4e8f736
docs(04-01): complete known gene compilation and weighted scoring plan
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- Known genes: 38 (10 OMIM Usher + 28 SYSCILIA SCGS v2 core)
- ScoringWeights.validate_sum() enforcing weight sum = 1.0
- NULL-preserving weighted average (weighted_sum / available_weight)
- Quality flags based on evidence_count thresholds
- Per-layer contributions for explainability
- 2 tasks, 4 files, 4 min duration
2026-02-11 20:44:09 +08:00
f441e8c1ad
feat(04-01): implement multi-evidence weighted scoring integration
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- Create join_evidence_layers() with LEFT JOIN preserving NULLs from all 6 evidence tables
- Implement compute_composite_scores() with NULL-preserving weighted average (weighted_sum / available_weight)
- Add quality_flag classification based on evidence_count (sufficient/moderate/sparse/no_evidence)
- Include per-layer contribution columns for explainability
- Add persist_scored_genes() to save scored_genes table to DuckDB
- Log summary stats: coverage, mean/median scores, quality distribution, NULL rates
2026-02-11 20:41:44 +08:00
0cd2f7c9dd
feat(04-01): implement known gene compilation and ScoringWeights validation
...
- Create scoring module with OMIM_USHER_GENES (10 genes) and SYSCILIA_SCGS_V2_CORE (28 genes)
- Implement compile_known_genes() returning DataFrame with gene_symbol, source, confidence
- Add load_known_genes_to_duckdb() to persist known genes table
- Add ScoringWeights.validate_sum() method enforcing weight sum constraint (1.0 ± 1e-6)
2026-02-11 20:41:31 +08:00
ed21f18a98
fix(03-05): handle NULL columns and deprecated polars API in animal models
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- Add NULL/empty column checks in fetch_ortholog_mapping
- Fix NULL handling in filter_sensory_phenotypes with is_not_null guard
- Replace deprecated str.concat with str.join
- Add explicit schema to empty DataFrames for consistency
2026-02-11 20:38:36 +08:00
a52724aff4
docs(04): create phase plan for scoring and integration
2026-02-11 20:31:55 +08:00
32988c631f
docs(04): research multi-evidence weighted scoring with NULL preservation
2026-02-11 20:24:42 +08:00
190bedaa80
docs(phase-03): complete phase execution
2026-02-11 19:18:12 +08:00
e72c516669
docs(03-06): complete literature evidence layer
...
- Created SUMMARY.md with full implementation details
- Updated STATE.md: progress 60%, 12/20 plans complete, Phase 3 complete
- Documented 4 key decisions (tier priority, bias mitigation, context weights, rate limiting)
- All verification criteria met: 17/17 tests pass, CLI functional, bias mitigation validated
- Self-check PASSED: all files and commits verified
Key accomplishments:
- PubMed evidence layer queries per gene across cilia/sensory/cytoskeleton/polarity contexts
- Quality tier classification: direct_experimental > hts_hit > functional_mention > incidental
- Bias mitigation via log2(total_pubmed_count) prevents well-studied gene dominance
- Novel genes with 10 total/5 cilia publications score higher than TP53-like genes with 100K total/5 cilia
- Biopython Entrez integration with rate limiting (3/sec default, 10/sec with API key)
2026-02-11 19:13:26 +08:00
0e89bf0dd6
docs(03-02): complete expression evidence layer plan
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- Create 03-02-SUMMARY.md with performance metrics, decisions, and deviations
- Update STATE.md: 5 of 6 plans complete in Phase 03 (03-06 remaining)
- Update progress: 55% complete (11/20 plans across all phases)
- Add key decisions: Tau calculation, expression scoring, CellxGene optional
- Record duration: 12 min for 2 tasks (9 files modified)
- Self-check passed: all files and commits verified
Expression layer provides:
- HPA/GTEx tissue expression with Tau specificity index
- Usher-tissue enrichment scoring (retina, inner ear, cilia)
- Optional CellxGene single-cell integration
- CLI command with checkpoint-restart
- 11 passing unit and integration tests
2026-02-11 19:12:18 +08:00
cfe4b830e6
docs(03-03): complete protein features plan with SUMMARY and STATE updates
2026-02-11 19:10:03 +08:00
053f0d926b
docs(03-05): complete animal model phenotype evidence layer plan
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- SUMMARY.md: Ortholog-mapped animal evidence from MGI/ZFIN/IMPC
- Confidence-weighted scoring (mouse +0.4, zebrafish +0.3, IMPC +0.3)
- 14/14 tests passing: ortholog confidence, keyword filtering, NULL preservation
- Deviations: Schema mismatches, NULL handling, polars deprecations auto-fixed
- Duration: 10 minutes, 2 tasks, 8 files, 2 commits
2026-02-11 19:08:45 +08:00
d8009f1236
docs(03-04): complete subcellular localization evidence layer
...
- Created SUMMARY.md with full implementation details
- Updated STATE.md: progress 40%, 8/20 plans complete
- Documented 4 key decisions (evidence terminology, NULL semantics, embedded proteomics, evidence weighting)
- All verification criteria met: 17/17 tests pass, CLI functional, DuckDB integration complete
2026-02-11 19:08:01 +08:00
46059874f2
feat(03-03): implement protein evidence layer with UniProt/InterPro integration
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- Create protein features data model with domain, coiled-coil, TM, cilia motifs
- Implement fetch.py with UniProt REST API and InterPro API queries
- Implement transform.py with feature extraction, motif detection, normalization
- Implement load.py with DuckDB persistence and provenance tracking
- Add CLI protein command following evidence layer pattern
- Add comprehensive unit and integration tests (all passing)
- Handle NULL preservation and List(Null) edge case
- Add get_steps() method to ProvenanceTracker for test compatibility
2026-02-11 19:07:30 +08:00
bcd3c4ffbe
feat(03-05): add animal model DuckDB loader, CLI, and comprehensive tests
...
- load.py: DuckDB persistence with provenance tracking, ortholog confidence distribution stats
- CLI animal-models command: checkpoint-restart pattern, top scoring genes display
- 10 unit tests: ortholog confidence scoring, keyword filtering, multi-organism bonus, NULL preservation
- 4 integration tests: full pipeline, checkpoint-restart, provenance tracking, empty phenotype handling
- All tests pass (14/14): validates fetch->transform->load->CLI flow
- Fixed polars deprecations: str.join replaces str.concat, pl.len replaces pl.count
2026-02-11 19:06:49 +08:00
99bc975a2c
docs(03-01): complete annotation completeness plan
2026-02-11 19:05:56 +08:00
942aaf2ec3
feat(03-04): add localization CLI command and comprehensive tests
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- Add localization subcommand to evidence command group
- Implement checkpoint-restart pattern for HPA download
- Display summary with evidence type distribution
- Create 17 unit and integration tests (all pass)
- Test HPA parsing, evidence classification, scoring, and DuckDB persistence
- Fix evidence type terminology (computational vs predicted) for consistency
- Mock HTTP calls in integration tests for reproducibility
2026-02-11 19:05:22 +08:00
d70239c4ce
feat(03-01): add annotation DuckDB loader, CLI command, and tests
...
- Create load_to_duckdb with provenance tracking and tier distribution stats
- Add query_poorly_annotated helper to find under-studied genes
- Register `evidence annotation` CLI command with checkpoint-restart pattern
- Add comprehensive unit tests (9 tests) covering GO extraction, NULL handling, tier classification, score normalization, weighting
- Add integration tests (6 tests) for pipeline, idempotency, checkpoint-restart, provenance, queries
- All 15 tests pass with proper NULL preservation and schema validation
2026-02-11 19:03:10 +08:00
0e389c7e41
feat(03-05): implement animal model evidence fetch and transform
...
- models.py: AnimalModelRecord with ortholog confidence, phenotype flags, and normalized scoring
- fetch.py: Retrieve orthologs from HCOP, phenotypes from MGI/ZFIN/IMPC with retry
- transform.py: Filter sensory/cilia-relevant phenotypes, score with confidence weighting
- Ortholog confidence: HIGH (8+ sources), MEDIUM (4-7), LOW (1-3)
- Scoring: mouse +0.4, zebrafish +0.3, IMPC +0.3, weighted by confidence
- NULL preservation: no ortholog = NULL score (not zero)
2026-02-11 19:00:24 +08:00
8aa66987f8
feat(03-06): implement literature evidence models, PubMed fetch, and scoring
...
- Create LiteratureRecord pydantic model with context-specific counts
- Implement PubMed query via Biopython Entrez with rate limiting (3/sec default, 10/sec with API key)
- Define SEARCH_CONTEXTS for cilia, sensory, cytoskeleton, cell_polarity queries
- Implement evidence tier classification: direct_experimental > functional_mention > hts_hit > incidental > none
- Implement quality-weighted scoring with bias mitigation via log2(total_pubmed_count) normalization
- Add biopython>=1.84 dependency to pyproject.toml
- Support checkpoint-restart for long-running PubMed queries (estimated 3-11 hours for 20K genes)
2026-02-11 19:00:20 +08:00
6645c59b0b
feat(03-04): create localization evidence data model and processing
...
- Define LocalizationRecord model with HPA and proteomics fields
- Implement fetch_hpa_subcellular to download HPA bulk data
- Implement fetch_cilia_proteomics with curated reference gene sets
- Implement classify_evidence_type (experimental vs computational)
- Implement score_localization with cilia proximity scoring
- Implement process_localization_evidence end-to-end pipeline
- Create load_to_duckdb for persistence with provenance
2026-02-11 19:00:09 +08:00
adbb74b965
feat(03-01): implement annotation evidence fetch and transform modules
...
- Create AnnotationRecord model with GO counts, UniProt scores, tier classification
- Implement fetch_go_annotations using mygene.info batch queries
- Implement fetch_uniprot_scores using UniProt REST API
- Add classify_annotation_tier with 3-tier system (well/partial/poor)
- Add normalize_annotation_score with weighted composite (GO 50%, UniProt 30%, Pathway 20%)
- Implement process_annotation_evidence end-to-end pipeline
- Follow NULL preservation pattern from gnomAD (unknown != zero)
- Use lazy polars evaluation where applicable
2026-02-11 18:58:45 +08:00
0d252da348
docs(03): create phase plan
2026-02-11 18:46:28 +08:00
3354cfe006
docs(phase-03): research core evidence layers domain
2026-02-11 18:37:14 +08:00
ffb4963d2b
docs(phase-02): complete phase execution
2026-02-11 18:28:13 +08:00
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
56e04e68c2
test(02-02): add comprehensive gnomAD integration tests
...
- 12 integration tests covering full pipeline: fetch->transform->load->query
- test_full_pipeline_to_duckdb: End-to-end pipeline verification with DuckDB storage
- test_checkpoint_restart_skips_processing: Checkpoint detection works correctly
- test_provenance_recorded: Provenance step records expected details
- test_provenance_sidecar_created: JSON sidecar file creation and structure
- test_query_constrained_genes_filters_correctly: Query returns only measured genes below threshold
- test_null_loeuf_not_in_constrained_results: NULL LOEUF genes excluded from queries
- test_duckdb_schema_has_quality_flag: Schema includes quality_flag with valid values
- test_normalized_scores_in_duckdb: Normalized scores in [0,1] for measured genes, NULL for others
- test_cli_evidence_gnomad_help: CLI help text displays correctly
- test_cli_evidence_gnomad_with_mock: CLI command runs end-to-end with mocked download
- test_idempotent_load_replaces_table: Loading twice replaces table (not appends)
- test_quality_flag_categorization: Quality flags correctly categorize genes
All 70 tests pass (58 existing + 12 new), no regressions
2026-02-11 18:20:59 +08:00
ee27f3ad2f
feat(02-02): add DuckDB loader and CLI evidence command for gnomAD
...
- load_to_duckdb: Saves constraint DataFrame to gnomad_constraint table with provenance tracking
- query_constrained_genes: Queries constrained genes by LOEUF threshold (validates GCON-03 interpretation)
- evidence_cmd.py: CLI command group with gnomad subcommand (fetch->transform->load orchestration)
- Checkpoint-restart: Skips processing if gnomad_constraint table exists (--force to override)
- Full CLI: usher-pipeline evidence gnomad [--force] [--url URL] [--min-depth N] [--min-cds-pct N]
2026-02-11 18:19:07 +08:00
c6198122ac
docs(02-01): complete gnomAD constraint data pipeline plan
2026-02-11 18:16:35 +08:00
174c4af02d
feat(02-01): add gnomAD transform pipeline and comprehensive tests
...
- Implement filter_by_coverage with quality_flag categorization (measured/incomplete_coverage/no_data)
- Add normalize_scores with LOEUF inversion (lower LOEUF = higher score)
- NULL preservation throughout pipeline (unknown != zero constraint)
- process_gnomad_constraint end-to-end pipeline function
- 15 comprehensive unit tests covering edge cases:
- NULL handling and preservation
- Coverage filtering without dropping genes
- Normalization bounds and inversion
- Mixed type handling for robust parsing
- Fix column mapping to handle gnomAD v4.x loeuf/loeuf_upper duplication
- All existing tests continue to pass
2026-02-11 18:14:41 +08:00
a88b0eea60
feat(02-01): add gnomAD constraint data models and download module
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- Create evidence layer package structure
- Define ConstraintRecord Pydantic model with NULL preservation
- Implement streaming download with httpx and tenacity retry
- Add lazy TSV parser with column name variant handling
- Add httpx and structlog dependencies
2026-02-11 18:11:49 +08:00
c7753e7b1c
docs(02): create phase plan
2026-02-11 17:47:23 +08:00
d328467737
docs(phase-02): research prototype evidence layer
2026-02-11 17:41:35 +08:00
34437fdf0a
docs(phase-01): complete phase execution
...
Phase 1 (Data Infrastructure) verified: 5/5 must-haves, 12/12 artifacts,
9/9 key links, 7/7 requirements satisfied. All 4 plans executed across
3 waves with 49 tests passing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-02-11 16:50:30 +08:00
102dcdbe84
docs(01-04): complete CLI integration and end-to-end testing plan
...
- CLI entry point with setup and info commands
- Full infrastructure integration verified
- 6 integration tests with mocked APIs
- Phase 01 Data Infrastructure complete
2026-02-11 16:45:12 +08:00
