def test_no_correlation(self):
"""Test the ``noCorrelation`` relation."""
statement = 'r(HGNC:X) noCorrelation r(HGNC:Y)'
self.parser.relation.parseString(statement)
source = Rna('HGNC', 'X')
target = Rna('HGNC', 'Y')
self.assert_has_two_way_edge(source, target, NO_CORRELATION)
def test_rna_fusion_specified(self):
node = RnaFusion(partner_5p=Rna(namespace='HGNC', name='TMPRSS2'),
range_5p=EnumeratedFusionRange('r', 1, 79),
partner_3p=Rna(namespace='HGNC', name='ERG'),
range_3p=EnumeratedFusionRange('r', 312, 5034))
self.assertEqual(
'r(fus(HGNC:TMPRSS2, "r.1_79", HGNC:ERG, "r.312_5034"))',
str(node))
def test_overlay(self):
"""Test overlaying data in a BEL graph."""
g = BELGraph()
g1 = Gene(HGNC, 'a')
g2 = Gene(HGNC, 'b')
g3 = Gene(HGNC, 'c')
g4 = Gene(HGNC, 'd')
r1 = Rna(HGNC, 'e')
p1 = Protein(HGNC, 'f')
g.add_node_from_data(g1)
g.add_node_from_data(g2)
g.add_node_from_data(g3)
g.add_node_from_data(g4)
g.add_node_from_data(r1)
g.add_node_from_data(p1)
self.assertEqual(6, g.number_of_nodes())
label = 'dgxp'
overlay_type_data(g, {
'a': 1,
'b': 2,
'c': -1
},
Gene,
HGNC,
label=label,
impute=0)
for node in g1, g2, g3, g4:
self.assertIn(label, g.nodes[node])
for node in r1, p1:
self.assertNotIn(label, g.nodes[node])
self.assertEqual(1, g.nodes[g1][label])
self.assertEqual(2, g.nodes[g2][label])
self.assertEqual(-1, g.nodes[g3][label])
self.assertEqual(0, g.nodes[g4][label])
def test_get_tf_pairs(self):
"""Test iterating over transcription factor pairs."""
graph = BELGraph()
p1, p2, p3 = (Protein('test', str(i)) for i in range(1, 4))
r4, r5, r6 = (Rna('test', str(j)) for j in range(4, 7))
g4 = r4.get_gene()
self.assertIsNotNone(g4)
g5 = r5.get_gene()
self.assertIsNotNone(g5)
c14, c25 = ComplexAbundance([p1, g4]), ComplexAbundance([p2, g5])
_tf_up(graph, p1, r4)
_tf_down(graph, p2, r5)
graph.add_correlation(p3, r6, citation=n(), evidence=n())
self.assertEqual({p1, p2, p3, r4, r5, r6, g4, g5, c14, c25},
set(graph))
expected_edges = [
(c14, r4),
(p1, c14),
(g4, c14),
(c25, r5),
(p2, c25),
(g5, c25),
(p3, r6),
(r6, p3),
]
sorted_expected_edges = sorted(expected_edges, key=_bel_pair_key)
sorted_actual_edges = sorted(graph.edges(), key=_bel_pair_key)
self.assertEqual(sorted_expected_edges, sorted_actual_edges)
pairs = set(get_tf_pairs(graph))
expected_pairs = {(p1, r4, +1), (p2, r5, -1)}
self.assertEqual(expected_pairs, pairs)
# -*- coding: utf-8 -*-
"""Tests for PyNPA."""
import unittest
import pandas as pd
from pybel import BELGraph
from pybel.dsl import ComplexAbundance, Gene, Protein, Rna
from pybel.io.pynpa import to_npa_dfs, to_npa_layers
from pybel.struct.getters import get_tf_pairs
from pybel.testing.utils import n
g1 = Gene('hgnc', '1')
r1 = Rna('hgnc', '1')
p1 = Protein('hgnc', '1')
g2 = Gene('hgnc', '2')
r2 = Rna('hgnc', '2')
p2 = Protein('hgnc', '2')
g3 = Gene('hgnc', '3')
p3 = Protein('hgnc', '3')
class TestPyNPA(unittest.TestCase):
"""Tests for PyNPA."""
def setUp(self) -> None:
"""Set up a small test graph."""
self.graph = BELGraph()
self.graph.add_increases(ComplexAbundance([p1, g2]),
r2,
citation=n(),
def test_rna_fusion_unspecified(self):
node = RnaFusion(
partner_5p=Rna(namespace='HGNC', name='TMPRSS2'),
partner_3p=Rna(namespace='HGNC', name='ERG'),
)
self.assertEqual('r(fus(HGNC:TMPRSS2, "?", HGNC:ERG, "?"))', str(node))
import unittest
from pybel import BELGraph
from pybel.constants import (
ASSOCIATION, DECREASES, DIRECTLY_INCREASES, INCREASES, POSITIVE_CORRELATION,
)
from pybel.dsl import Abundance, Gene, MicroRna, Pathology, Protein, Rna
from pybel.testing.utils import n
from pybel_tools.mutation.collapse import collapse_to_protein_interactions
HGNC = 'HGNC'
GO = 'GO'
CHEBI = 'CHEBI'
g1 = Gene(namespace=HGNC, name='1')
r1 = Rna(namespace=HGNC, name='1')
p1 = Protein(HGNC, name='1')
g2 = Gene(HGNC, name='2')
r2 = Rna(HGNC, name='2')
p2 = Protein(HGNC, name='2')
g3 = Gene(namespace=HGNC, name='3')
r3 = Rna(namespace=HGNC, name='3')
p3 = Protein(namespace=HGNC, name='3')
g4 = Gene(namespace=HGNC, name='4')
m4 = MicroRna(namespace=HGNC, name='4')
a5 = Abundance(namespace=CHEBI, name='5')
p5 = Pathology(namespace=GO, name='5')
)
bcr_jak2_protein_fusion = ProteinFusion(
partner_5p=Protein('HGNC', 'BCR'),
range_5p=EnumeratedFusionRange('p', '?', 1875),
partner_3p=Protein('HGNC', 'JAK2'),
range_3p=EnumeratedFusionRange('p', 2626, '?')
)
chchd4_aifm1_protein_fusion = ProteinFusion(
Protein('HGNC', 'CHCHD4'),
Protein('HGNC', 'AIFM1')
)
bcr_jak2_rna_fusion = RnaFusion(
partner_5p=Rna('HGNC', 'BCR'),
range_5p=EnumeratedFusionRange('r', '?', 1875),
partner_3p=Rna('HGNC', 'JAK2'),
range_3p=EnumeratedFusionRange('r', 2626, '?')
)
chchd4_aifm1_rna_fusion = RnaFusion(
partner_5p=Rna('HGNC', 'CHCHD4'),
partner_3p=Rna('HGNC', 'AIFM1')
)
tmprss2_erg_rna_fusion = RnaFusion(
partner_5p=Rna('HGNC', 'TMPRSS2'),
range_5p=EnumeratedFusionRange('r', 1, 79),
partner_3p=Rna('HGNC', 'ERG'),
range_3p=EnumeratedFusionRange('r', 312, 5034)
def _rela(x, y=None):
return {RELATION: x, OBJECT: activity(y)}
def _assoc(y):
return {RELATION: ASSOCIATION, 'association_type': y}
a1 = Abundance('CHEBI', '1')
p1 = Protein('HGNC', '1')
pf1 = Protein('INTERPRO', '1')
d1 = Pathology('MESH', '1')
b1 = BiologicalProcess('GO', '1')
b2 = BiologicalProcess('GO', '2')
m1 = MicroRna('MIRBASE', '1')
r1 = Rna('HGNC', '1')
r2 = Rna('HGNC', '2')
nca1 = NamedComplexAbundance('FPLX', '1')
pop1 = Population('taxonomy', '1')
p2 = Protein('HGNC', identifier='9236')
p3 = Protein('HGNC', identifier='9212')
r3 = p3.get_rna()
g3 = r3.get_gene()
c1 = ComplexAbundance([p2, g3])
c2 = ComplexAbundance([p1, p2])
c3 = ComplexAbundance([a1, p2])
converters_true_list = [
(PartOfNamedComplexConverter, p1, nca1, _rel(PART_OF), ('HGNC:1', 'partOf',
tmprss2_erg_protein_fusion = ProteinFusion(
partner_5p=Protein('HGNC', 'TMPRSS2'),
range_5p=EnumeratedFusionRange('p', 1, 79),
partner_3p=Protein('HGNC', 'ERG'),
range_3p=EnumeratedFusionRange('p', 312, 5034))
bcr_jak2_protein_fusion = ProteinFusion(
partner_5p=Protein('HGNC', 'BCR'),
range_5p=EnumeratedFusionRange('p', '?', 1875),
partner_3p=Protein('HGNC', 'JAK2'),
range_3p=EnumeratedFusionRange('p', 2626, '?'))
chchd4_aifm1_protein_fusion = ProteinFusion(Protein('HGNC', 'CHCHD4'),
Protein('HGNC', 'AIFM1'))
bcr_jak2_rna_fusion = RnaFusion(partner_5p=Rna('HGNC', 'BCR'),
range_5p=EnumeratedFusionRange('r', '?', 1875),
partner_3p=Rna('HGNC', 'JAK2'),
range_3p=EnumeratedFusionRange('r', 2626, '?'))
chchd4_aifm1_rna_fusion = RnaFusion(partner_5p=Rna('HGNC', 'CHCHD4'),
partner_3p=Rna('HGNC', 'AIFM1'))
tmprss2_erg_rna_fusion = RnaFusion(partner_5p=Rna('HGNC', 'TMPRSS2'),
range_5p=EnumeratedFusionRange('r', 1, 79),
partner_3p=Rna('HGNC', 'ERG'),
range_3p=EnumeratedFusionRange(
'r', 312, 5034))
tmprss2_erg_rna_fusion_unspecified = RnaFusion(partner_5p=Rna(
'HGNC', 'TMPRSS2'),
partner_3p=Rna('HGNC', 'ERG'))