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6d1bbc7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 | """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"
@pytest.fixture
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:
@pytest.fixture
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()
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