"""Tests for DepMap CRISPR ETL module. Uses synthetic 5-gene × 4-cell-line matrices to test the full ETL pipeline without requiring actual DepMap downloads (~1 GB). """ import sqlite3 from pathlib import Path import pandas as pd import pytest from negbiodb_depmap.depmap_db import get_connection, run_ge_migrations, refresh_all_ge_pairs from negbiodb_depmap.etl_depmap import ( assign_tier, load_cell_lines, load_depmap_crispr, load_genes_from_header, load_reference_gene_sets, parse_gene_column, ) MIGRATIONS_DIR = Path(__file__).parent.parent / "migrations_depmap" # ── Fixtures ────────────────────────────────────────────────────────────── @pytest.fixture def tmp_db(tmp_path): """Create a temporary GE database with migrations applied.""" db_path = tmp_path / "test_ge.db" run_ge_migrations(db_path, MIGRATIONS_DIR) return db_path @pytest.fixture def conn(tmp_db): c = get_connection(tmp_db) yield c c.close() @pytest.fixture def synthetic_data(tmp_path): """Create synthetic DepMap CSV files for testing. 5 genes × 4 cell lines: - GeneA (1001): clearly non-essential (positive scores) - GeneB (1002): marginal (near threshold) - GeneC (1003): essential (very negative scores) — should be excluded - GeneD (1004): mixed (non-essential in some, essential in others) - GeneE (1005): NaN in all cell lines — should be skipped """ genes = [ "GeneA (1001)", "GeneB (1002)", "GeneC (1003)", "GeneD (1004)", "GeneE (1005)", ] cell_lines = ["ACH-000001", "ACH-000002", "ACH-000003", "ACH-000004"] # Gene effect scores (Chronos: 0 = no effect, -1 = essential) ge_data = { genes[0]: [0.05, 0.10, -0.15, 0.02], # clearly non-essential genes[1]: [-0.45, -0.55, -0.70, -0.48], # marginal genes[2]: [-1.2, -1.5, -0.95, -1.1], # essential genes[3]: [0.01, -0.90, -0.30, 0.05], # mixed genes[4]: [float("nan")] * 4, # NaN } ge_df = pd.DataFrame(ge_data, index=cell_lines) ge_file = tmp_path / "CRISPRGeneEffect.csv" ge_df.to_csv(ge_file, index_label="ModelID") # Dependency probability (0-1) dep_data = { genes[0]: [0.05, 0.10, 0.20, 0.08], # low prob → non-essential genes[1]: [0.40, 0.55, 0.70, 0.45], # marginal genes[2]: [0.95, 0.98, 0.80, 0.90], # high prob → essential genes[3]: [0.10, 0.85, 0.35, 0.05], # mixed genes[4]: [float("nan")] * 4, # NaN } dep_df = pd.DataFrame(dep_data, index=cell_lines) dep_file = tmp_path / "CRISPRGeneDependency.csv" dep_df.to_csv(dep_file, index_label="ModelID") # Model.csv (cell line metadata) model_data = { "ModelID": cell_lines, "CCLEName": ["CELL1_LUNG", "CELL2_BREAST", "CELL3_SKIN", "CELL4_COLON"], "StrippedCellLineName": ["CELL1", "CELL2", "CELL3", "CELL4"], "OncotreeLineage": ["Lung", "Breast", "Skin", "Colon"], "OncotreePrimaryDisease": [ "Non-Small Cell Lung Cancer", "Breast Cancer", "Melanoma", "Colorectal Cancer", ], } model_df = pd.DataFrame(model_data) model_file = tmp_path / "Model.csv" model_df.to_csv(model_file, index=False) # Essential gene set ess_file = tmp_path / "AchillesCommonEssentialControls.csv" ess_file.write_text("GeneC (1003)\n") # Non-essential gene set ne_file = tmp_path / "AchillesNonessentialControls.csv" ne_file.write_text("GeneA (1001)\n") return { "gene_effect_file": ge_file, "dependency_file": dep_file, "model_file": model_file, "essential_file": ess_file, "nonessential_file": ne_file, } # ── Unit tests ──────────────────────────────────────────────────────────── class TestParseGeneColumn: def test_standard_format(self): assert parse_gene_column("TP53 (7157)") == ("TP53", 7157) def test_gene_with_dash(self): assert parse_gene_column("HLA-A (3105)") == ("HLA-A", 3105) def test_extra_spaces(self): # DepMap format has no internal spaces in parens, but outer whitespace is stripped assert parse_gene_column(" BRAF (673) ") == ("BRAF", 673) def test_invalid_format(self): assert parse_gene_column("ModelID") is None def test_no_entrez(self): assert parse_gene_column("UNKNOWN") is None class TestAssignTier: def test_gold_tier(self): assert assign_tier(0.05, 0.1, is_reference_nonessential=True) == "gold" def test_gold_requires_ref_nonessential(self): # Without reference flag → silver assert assign_tier(0.05, 0.1, is_reference_nonessential=False) == "silver" def test_silver_tier(self): assert assign_tier(-0.4, 0.3, is_reference_nonessential=False) == "silver" def test_bronze_tier(self): assert assign_tier(-0.7, 0.45, is_reference_nonessential=False) == "bronze" def test_bronze_low_effect(self): assert assign_tier(-0.75, 0.45, is_reference_nonessential=False) == "bronze" def test_no_dep_prob(self): # dep_prob=None defaults to 1.0 (conservative) assert assign_tier(0.05, None, is_reference_nonessential=True) == "bronze" def test_silver_boundary(self): # Exactly at boundary: > -0.5 assert assign_tier(-0.49, 0.49, is_reference_nonessential=False) == "silver" # ── Cell line loading ───────────────────────────────────────────────────── class TestCellLineLoading: def test_load_cell_lines(self, conn, synthetic_data): result = load_cell_lines(conn, synthetic_data["model_file"]) assert len(result) == 4 assert "ACH-000001" in result assert "ACH-000004" in result def test_cell_line_metadata(self, conn, synthetic_data): load_cell_lines(conn, synthetic_data["model_file"]) row = conn.execute( "SELECT ccle_name, lineage, primary_disease FROM cell_lines WHERE model_id = 'ACH-000001'" ).fetchone() assert row[0] == "CELL1_LUNG" assert row[1] == "Lung" assert row[2] == "Non-Small Cell Lung Cancer" def test_load_idempotent(self, conn, synthetic_data): load_cell_lines(conn, synthetic_data["model_file"]) result = load_cell_lines(conn, synthetic_data["model_file"]) assert len(result) == 4 # no duplicates # ── Gene loading ────────────────────────────────────────────────────────── class TestGeneLoading: def test_load_genes_from_header(self, conn, synthetic_data): result = load_genes_from_header(conn, synthetic_data["gene_effect_file"]) assert len(result) == 5 # 5 genes # Check genes in DB count = conn.execute("SELECT COUNT(*) FROM genes").fetchone()[0] assert count == 5 def test_gene_metadata(self, conn, synthetic_data): load_genes_from_header(conn, synthetic_data["gene_effect_file"]) row = conn.execute( "SELECT gene_symbol, entrez_id FROM genes WHERE gene_symbol = 'GeneA'" ).fetchone() assert row is not None assert row[1] == 1001 class TestReferenceGeneSets: def test_mark_essential(self, conn, synthetic_data): load_genes_from_header(conn, synthetic_data["gene_effect_file"]) load_reference_gene_sets( conn, essential_file=synthetic_data["essential_file"], ) row = conn.execute( "SELECT is_common_essential FROM genes WHERE gene_symbol = 'GeneC'" ).fetchone() assert row[0] == 1 def test_mark_nonessential(self, conn, synthetic_data): load_genes_from_header(conn, synthetic_data["gene_effect_file"]) load_reference_gene_sets( conn, nonessential_file=synthetic_data["nonessential_file"], ) row = conn.execute( "SELECT is_reference_nonessential FROM genes WHERE gene_symbol = 'GeneA'" ).fetchone() assert row[0] == 1 # ── Full pipeline ───────────────────────────────────────────────────────── class TestFullPipeline: def test_load_depmap_crispr(self, tmp_db, synthetic_data): stats = load_depmap_crispr( tmp_db, gene_effect_file=synthetic_data["gene_effect_file"], dependency_file=synthetic_data["dependency_file"], model_file=synthetic_data["model_file"], essential_file=synthetic_data["essential_file"], nonessential_file=synthetic_data["nonessential_file"], depmap_release="test_release", ) assert stats["cell_lines_loaded"] == 4 assert stats["genes_loaded"] == 5 assert stats["pairs_inserted"] > 0 assert stats["pairs_skipped_nan"] == 4 # GeneE in all 4 cell lines def test_essential_genes_excluded(self, tmp_db, synthetic_data): stats = load_depmap_crispr( tmp_db, gene_effect_file=synthetic_data["gene_effect_file"], dependency_file=synthetic_data["dependency_file"], model_file=synthetic_data["model_file"], depmap_release="test_release", ) # GeneC is essential (gene_effect < -0.8 AND dep_prob > 0.5) # ACH-000001: -1.2, 0.95 → skip (effect<-0.8 AND prob>0.5) # ACH-000002: -1.5, 0.98 → skip # ACH-000003: -0.95, 0.80 → skip (effect<-0.8 AND prob>0.5) # ACH-000004: -1.1, 0.90 → skip conn = get_connection(tmp_db) try: genec_id = conn.execute( "SELECT gene_id FROM genes WHERE gene_symbol = 'GeneC'" ).fetchone()[0] count = conn.execute( "SELECT COUNT(*) FROM ge_negative_results WHERE gene_id = ?", (genec_id,), ).fetchone()[0] assert count == 0 finally: conn.close() def test_nan_values_skipped(self, tmp_db, synthetic_data): stats = load_depmap_crispr( tmp_db, gene_effect_file=synthetic_data["gene_effect_file"], dependency_file=synthetic_data["dependency_file"], model_file=synthetic_data["model_file"], depmap_release="test_release", ) assert stats["pairs_skipped_nan"] == 4 def test_tiering_distribution(self, tmp_db, synthetic_data): stats = load_depmap_crispr( tmp_db, gene_effect_file=synthetic_data["gene_effect_file"], dependency_file=synthetic_data["dependency_file"], model_file=synthetic_data["model_file"], essential_file=synthetic_data["essential_file"], nonessential_file=synthetic_data["nonessential_file"], depmap_release="test_release", ) total_tiered = stats["tier_gold"] + stats["tier_silver"] + stats["tier_bronze"] assert total_tiered == stats["pairs_inserted"] def test_screen_record_created(self, tmp_db, synthetic_data): load_depmap_crispr( tmp_db, gene_effect_file=synthetic_data["gene_effect_file"], dependency_file=synthetic_data["dependency_file"], model_file=synthetic_data["model_file"], depmap_release="test_release", ) conn = get_connection(tmp_db) try: row = conn.execute( "SELECT screen_type, algorithm FROM ge_screens WHERE source_db = 'depmap'" ).fetchone() assert row[0] == "crispr" assert row[1] == "Chronos" finally: conn.close() def test_dataset_version_recorded(self, tmp_db, synthetic_data): load_depmap_crispr( tmp_db, gene_effect_file=synthetic_data["gene_effect_file"], dependency_file=synthetic_data["dependency_file"], model_file=synthetic_data["model_file"], depmap_release="test_release", ) conn = get_connection(tmp_db) try: row = conn.execute( "SELECT name, version FROM dataset_versions WHERE name = 'depmap_crispr'" ).fetchone() assert row is not None assert row[1] == "test_release" finally: conn.close() def test_pair_aggregation(self, tmp_db, synthetic_data): load_depmap_crispr( tmp_db, gene_effect_file=synthetic_data["gene_effect_file"], dependency_file=synthetic_data["dependency_file"], model_file=synthetic_data["model_file"], depmap_release="test_release", ) conn = get_connection(tmp_db) try: count = refresh_all_ge_pairs(conn) conn.commit() assert count > 0 # Verify gene_degree and cell_line_degree are set row = conn.execute( "SELECT gene_degree, cell_line_degree FROM gene_cell_pairs LIMIT 1" ).fetchone() assert row[0] is not None assert row[1] is not None finally: conn.close() def test_idempotent_reload(self, tmp_db, synthetic_data): """Running ETL twice should not duplicate records.""" load_depmap_crispr( tmp_db, gene_effect_file=synthetic_data["gene_effect_file"], dependency_file=synthetic_data["dependency_file"], model_file=synthetic_data["model_file"], depmap_release="test_release", ) stats1 = load_depmap_crispr( tmp_db, gene_effect_file=synthetic_data["gene_effect_file"], dependency_file=synthetic_data["dependency_file"], model_file=synthetic_data["model_file"], depmap_release="test_release", ) conn = get_connection(tmp_db) try: count = conn.execute( "SELECT COUNT(*) FROM ge_negative_results" ).fetchone()[0] assert count == stats1["pairs_inserted"] finally: conn.close()