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
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
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- 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
d8009f1236
docs(03-04): complete subcellular localization evidence layer
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- 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
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- 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
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
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- 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
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- 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
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- 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
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- 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
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- 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
ee27f3ad2f
feat(02-02): add DuckDB loader and CLI evidence command for gnomAD
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- 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
174c4af02d
feat(02-01): add gnomAD transform pipeline and comprehensive tests
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- 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
f33b048635
feat(01-04): add CLI entry point with setup and info commands
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- Create click-based CLI with command group (--config, --verbose options)
- Add 'info' command displaying pipeline version, config hash, data source versions
- Add 'setup' command orchestrating full infrastructure flow:
- Load config -> create store/provenance
- Fetch gene universe (with checkpoint-restart)
- Map Ensembl IDs to HGNC + UniProt
- Validate mapping quality gates
- Save to DuckDB with provenance sidecar
- Update pyproject.toml entry point to usher_pipeline.cli.main:cli
- Add .gitignore for data/, *.duckdb, build artifacts, provenance files
2026-02-11 16:39:50 +08:00
0200395d9e
feat(01-02): create mapping validation gates with tests
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- Add MappingValidator with configurable success rate thresholds (min_success_rate, warn_threshold)
- Add validate_gene_universe for gene count, format, and duplicate checks
- Add save_unmapped_report for manual review output
- Implement 15 comprehensive tests with mocked mygene responses (no real API calls)
- Tests cover: successful mapping, notfound handling, uniprot list parsing, batching, validation gates, universe validation
2026-02-11 16:33:36 +08:00
98a1a750dd
feat(01-03): create provenance tracker with comprehensive tests
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- ProvenanceTracker class for metadata tracking
- Records pipeline version, data source versions, config hash, timestamps
- Sidecar JSON export alongside outputs
- DuckDB _provenance table support
- 13 comprehensive tests (8 DuckDB + 5 provenance)
- All tests pass (12 passed, 1 skipped - pandas)
2026-02-11 16:31:51 +08:00
d51141f7d5
feat(01-03): create DuckDB persistence layer with checkpoint-restart
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- PipelineStore class for DuckDB-based storage
- save_dataframe/load_dataframe for polars and pandas
- Checkpoint system with has_checkpoint and metadata tracking
- Parquet export capability
- Context manager support
2026-02-11 16:30:25 +08:00
4204116772
feat(01-01): create base API client with retry and caching
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- CachedAPIClient with SQLite persistent cache
- Exponential backoff retry on 429/5xx/network errors (tenacity)
- Rate limiting with skip for cached responses
- from_config classmethod for pipeline integration
- 5 passing tests for cache creation, rate limiting, and config integration
2026-02-11 16:25:46 +08:00
4a80a0398e
feat(01-01): create Python package scaffold with config system
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- pyproject.toml: installable package with bioinformatics dependencies
- Pydantic config schema with validation (ensembl_release >= 100, directory creation)
- YAML config loader with override support
- Default config with Ensembl 113, gnomAD v4.1
- 5 passing tests for config validation and hashing
2026-02-11 16:24:35 +08:00
