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biology
chemistry
drug-discovery
clinical-trials
protein-protein-interaction
gene-essentiality
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| """Tests for IntAct negative PPI ETL.""" | |
| from pathlib import Path | |
| import pytest | |
| from negbiodb_ppi.etl_intact import ( | |
| _parse_mi_id, | |
| _parse_mi_term, | |
| _parse_miscore, | |
| _parse_pubmed, | |
| _parse_taxon_id, | |
| _parse_uniprot_id, | |
| classify_tier, | |
| parse_mitab_line, | |
| run_intact_etl, | |
| ) | |
| from negbiodb_ppi.ppi_db import get_connection, run_ppi_migrations | |
| MIGRATIONS_DIR = Path(__file__).resolve().parent.parent / "migrations_ppi" | |
| def ppi_db(tmp_path): | |
| db_path = tmp_path / "test_ppi.db" | |
| run_ppi_migrations(db_path, MIGRATIONS_DIR) | |
| return db_path | |
| def _make_mitab_line( | |
| uniprot_a="uniprotkb:P00001", | |
| uniprot_b="uniprotkb:P00002", | |
| detection="psi-mi:\"MI:0019\"(coimmunoprecipitation)", | |
| pubmed="pubmed:12345678", | |
| taxon_a="taxid:9606(Homo sapiens)", | |
| taxon_b="taxid:9606(Homo sapiens)", | |
| interaction_type="psi-mi:\"MI:0914\"(association)", | |
| interaction_id="EBI-12345", | |
| confidence="intact-miscore:0.56", | |
| negative="true", | |
| ): | |
| """Build a mock PSI-MI TAB 2.7 line (36+ columns).""" | |
| cols = [""] * 42 | |
| cols[0] = uniprot_a | |
| cols[1] = uniprot_b | |
| cols[6] = detection | |
| cols[8] = pubmed | |
| cols[9] = taxon_a | |
| cols[10] = taxon_b | |
| cols[11] = interaction_type | |
| cols[13] = interaction_id | |
| cols[14] = confidence | |
| cols[35] = negative | |
| return "\t".join(cols) | |
| class TestParseUniprotId: | |
| def test_basic(self): | |
| assert _parse_uniprot_id("uniprotkb:P12346") == "P12346" | |
| def test_isoform(self): | |
| assert _parse_uniprot_id("uniprotkb:P12346-2") == "P12346" | |
| def test_multi_value(self): | |
| assert _parse_uniprot_id("uniprotkb:P12346|chebi:12345") == "P12346" | |
| def test_non_uniprotkb(self): | |
| assert _parse_uniprot_id("chebi:12345") is None | |
| def test_empty(self): | |
| assert _parse_uniprot_id("") is None | |
| def test_dash_only(self): | |
| assert _parse_uniprot_id("-") is None | |
| class TestParseTaxonId: | |
| def test_human(self): | |
| assert _parse_taxon_id("taxid:9606(Homo sapiens)") == 9606 | |
| def test_mouse(self): | |
| assert _parse_taxon_id("taxid:10090(mouse)") == 10090 | |
| def test_empty(self): | |
| assert _parse_taxon_id("-") is None | |
| class TestParseMiId: | |
| def test_basic(self): | |
| assert _parse_mi_id('psi-mi:"MI:0018"(two hybrid)') == "MI:0018" | |
| def test_coip(self): | |
| assert _parse_mi_id('psi-mi:"MI:0019"(coimmunoprecipitation)') == "MI:0019" | |
| def test_no_match(self): | |
| assert _parse_mi_id("-") is None | |
| class TestParseMiTerm: | |
| def test_basic(self): | |
| assert _parse_mi_term('psi-mi:"MI:0018"(two hybrid)') == "two hybrid" | |
| def test_coip(self): | |
| assert ( | |
| _parse_mi_term('psi-mi:"MI:0019"(coimmunoprecipitation)') | |
| == "coimmunoprecipitation" | |
| ) | |
| class TestParsePubmed: | |
| def test_basic(self): | |
| assert _parse_pubmed("pubmed:12345678") == 12345678 | |
| def test_multi(self): | |
| assert _parse_pubmed("pubmed:12345678|pubmed:99999") == 12345678 | |
| def test_no_pubmed(self): | |
| assert _parse_pubmed("-") is None | |
| class TestParseMiscore: | |
| def test_basic(self): | |
| assert _parse_miscore("intact-miscore:0.56") == pytest.approx(0.56) | |
| def test_no_score(self): | |
| assert _parse_miscore("-") is None | |
| class TestClassifyTier: | |
| def test_gold_coip(self): | |
| assert classify_tier("MI:0019") == "gold" | |
| def test_gold_pulldown(self): | |
| assert classify_tier("MI:0096") == "gold" | |
| def test_gold_xray(self): | |
| assert classify_tier("MI:0114") == "gold" | |
| def test_gold_crosslink(self): | |
| assert classify_tier("MI:0030") == "gold" | |
| def test_silver_y2h(self): | |
| assert classify_tier("MI:0018") == "silver" | |
| def test_silver_unknown(self): | |
| assert classify_tier("MI:9999") == "silver" | |
| def test_silver_none(self): | |
| assert classify_tier(None) == "silver" | |
| class TestParseMitabLine: | |
| def test_valid_negative(self): | |
| line = _make_mitab_line() | |
| result = parse_mitab_line(line) | |
| assert result is not None | |
| assert result["uniprot_a"] == "P00001" | |
| assert result["uniprot_b"] == "P00002" | |
| assert result["detection_method_id"] == "MI:0019" | |
| assert result["taxon_a"] == 9606 | |
| def test_positive_rejected(self): | |
| line = _make_mitab_line(negative="false") | |
| assert parse_mitab_line(line) is None | |
| def test_short_line_rejected(self): | |
| line = "\t".join(["a", "b", "c"]) # Only 3 columns | |
| assert parse_mitab_line(line) is None | |
| def test_non_uniprot_rejected(self): | |
| line = _make_mitab_line(uniprot_a="chebi:12345") | |
| assert parse_mitab_line(line) is None | |
| def test_pubmed_parsed(self): | |
| line = _make_mitab_line(pubmed="pubmed:99999") | |
| result = parse_mitab_line(line) | |
| assert result["pubmed_id"] == 99999 | |
| class TestRunIntactEtl: | |
| def intact_data_dir(self, tmp_path): | |
| data_dir = tmp_path / "intact" | |
| data_dir.mkdir() | |
| # Mock intact_negative.txt with 3 lines: 2 human, 1 mouse | |
| lines = [ | |
| _make_mitab_line( | |
| uniprot_a="uniprotkb:P00001", | |
| uniprot_b="uniprotkb:P00002", | |
| detection='psi-mi:"MI:0019"(coimmunoprecipitation)', | |
| interaction_id="EBI-001", | |
| ), | |
| _make_mitab_line( | |
| uniprot_a="uniprotkb:P00003", | |
| uniprot_b="uniprotkb:P00004", | |
| detection='psi-mi:"MI:0018"(two hybrid)', | |
| interaction_id="EBI-002", | |
| ), | |
| _make_mitab_line( | |
| uniprot_a="uniprotkb:P00005", | |
| uniprot_b="uniprotkb:P00006", | |
| taxon_a="taxid:10090(mouse)", | |
| taxon_b="taxid:10090(mouse)", | |
| interaction_id="EBI-003", | |
| ), | |
| ] | |
| (data_dir / "intact_negative.txt").write_text("\n".join(lines) + "\n") | |
| return data_dir | |
| def test_basic_etl(self, ppi_db, intact_data_dir): | |
| stats = run_intact_etl(db_path=ppi_db, data_dir=intact_data_dir) | |
| # 3 lines total, 2 human, 1 mouse filtered | |
| assert stats["lines_total"] == 3 | |
| assert stats["lines_parsed"] == 2 | |
| assert stats["lines_skipped_non_human"] == 1 | |
| assert stats["pairs_gold"] == 1 # MI:0019 = gold | |
| assert stats["pairs_silver"] == 1 # MI:0018 = silver | |
| assert stats["pairs_inserted"] == 2 | |
| def test_db_contents(self, ppi_db, intact_data_dir): | |
| run_intact_etl(db_path=ppi_db, data_dir=intact_data_dir) | |
| conn = get_connection(ppi_db) | |
| try: | |
| # 4 human proteins | |
| protein_count = conn.execute( | |
| "SELECT COUNT(*) FROM proteins" | |
| ).fetchone()[0] | |
| assert protein_count == 4 | |
| # 2 negative results | |
| result_count = conn.execute( | |
| "SELECT COUNT(*) FROM ppi_negative_results" | |
| ).fetchone()[0] | |
| assert result_count == 2 | |
| # Both gold and silver tiers present | |
| tiers = { | |
| row[0] | |
| for row in conn.execute( | |
| "SELECT DISTINCT confidence_tier FROM ppi_negative_results" | |
| ).fetchall() | |
| } | |
| assert tiers == {"gold", "silver"} | |
| # Dataset version recorded | |
| dv = conn.execute( | |
| "SELECT name FROM dataset_versions WHERE name = 'intact_negative'" | |
| ).fetchone() | |
| assert dv is not None | |
| finally: | |
| conn.close() | |
| def test_human_only_false(self, ppi_db, intact_data_dir): | |
| """With human_only=False, mouse interactions are included.""" | |
| stats = run_intact_etl( | |
| db_path=ppi_db, data_dir=intact_data_dir, human_only=False | |
| ) | |
| assert stats["lines_parsed"] == 3 | |
| assert stats["pairs_inserted"] == 3 | |
| def test_etl_idempotent(self, ppi_db, intact_data_dir): | |
| """Running ETL twice should not duplicate records.""" | |
| stats1 = run_intact_etl(db_path=ppi_db, data_dir=intact_data_dir) | |
| stats2 = run_intact_etl(db_path=ppi_db, data_dir=intact_data_dir) | |
| assert stats1["pairs_inserted"] == stats2["pairs_inserted"] | |
| conn = get_connection(ppi_db) | |
| try: | |
| count = conn.execute( | |
| "SELECT COUNT(*) FROM ppi_negative_results" | |
| ).fetchone()[0] | |
| assert count == stats1["pairs_inserted"] | |
| dv_count = conn.execute( | |
| "SELECT COUNT(*) FROM dataset_versions " | |
| "WHERE name = 'intact_negative'" | |
| ).fetchone()[0] | |
| assert dv_count == 1 | |
| finally: | |
| conn.close() | |
| def test_comment_lines_skipped(self, ppi_db, tmp_path): | |
| """Comment/header lines starting with # are counted and skipped.""" | |
| data_dir = tmp_path / "intact_comment" | |
| data_dir.mkdir() | |
| lines = [ | |
| "#" + "\t".join(["col" + str(i) for i in range(42)]), | |
| _make_mitab_line( | |
| uniprot_a="uniprotkb:P00001", | |
| uniprot_b="uniprotkb:P00002", | |
| interaction_id="EBI-100", | |
| ), | |
| ] | |
| (data_dir / "intact_negative.txt").write_text( | |
| "\n".join(lines) + "\n" | |
| ) | |
| stats = run_intact_etl(db_path=ppi_db, data_dir=data_dir) | |
| assert stats["lines_total"] == 2 | |
| assert stats["lines_skipped_comment"] == 1 | |
| assert stats["lines_parsed"] == 1 | |
| def test_dash_interaction_id_generates_unique(self, ppi_db, tmp_path): | |
| """Dash '-' in interaction_id column generates per-pair ID.""" | |
| data_dir = tmp_path / "intact_dash" | |
| data_dir.mkdir() | |
| lines = [ | |
| _make_mitab_line( | |
| uniprot_a="uniprotkb:P00001", | |
| uniprot_b="uniprotkb:P00002", | |
| interaction_id="-", | |
| ), | |
| _make_mitab_line( | |
| uniprot_a="uniprotkb:P00003", | |
| uniprot_b="uniprotkb:P00004", | |
| interaction_id="-", | |
| ), | |
| ] | |
| (data_dir / "intact_negative.txt").write_text( | |
| "\n".join(lines) + "\n" | |
| ) | |
| stats = run_intact_etl(db_path=ppi_db, data_dir=data_dir) | |
| assert stats["pairs_inserted"] == 2 | |
| # Each pair should have its own experiment record | |
| conn = get_connection(ppi_db) | |
| try: | |
| exp_count = conn.execute( | |
| "SELECT COUNT(*) FROM ppi_experiments WHERE source_db = 'intact'" | |
| ).fetchone()[0] | |
| assert exp_count == 2 | |
| finally: | |
| conn.close() | |