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#########################################################################
# MacSyFinder - Detection of macromolecular systems in protein dataset #
# using systems modelling and similarity search. #
# Authors: Sophie Abby, Bertrand Neron #
# Copyright (c) 2014-2024 Institut Pasteur (Paris) and CNRS. #
# See the COPYRIGHT file for details #
# #
# This file is part of MacSyFinder package. #
# #
# MacSyFinder is free software: you can redistribute it and/or modify #
# it under the terms of the GNU General Public License as published by #
# the Free Software Foundation, either version 3 of the License, or #
# (at your option) any later version. #
# #
# MacSyFinder is distributed in the hope that it will be useful, #
# but WITHOUT ANY WARRANTY; without even the implied warranty of #
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
# GNU General Public License for more details . #
# #
# You should have received a copy of the GNU General Public License #
# along with MacSyFinder (COPYING). #
# If not, see <https://www.gnu.org/licenses/>. #
#########################################################################
import os
import argparse
from macsypy.hit import CoreHit, ModelHit
from macsypy.config import Config, MacsyDefaults
from macsypy.gene import CoreGene, ModelGene, Exchangeable, GeneStatus
from macsypy.profile import ProfileFactory
from macsypy.model import Model
from macsypy.registries import ModelLocation
from macsypy.cluster import Cluster
from macsypy.system import OrderedMatchMaker, UnorderedMatchMaker
from macsypy.system import System, RejectedCandidate, LikelySystem, UnlikelySystem
from macsypy.error import MacsypyError
from tests import MacsyTest
class MatchMakerTest(MacsyTest):
def setUp(self) -> None:
args = argparse.Namespace()
args.sequence_db = self.find_data("base", "test_1.fasta")
args.db_type = 'gembase'
args.models_dir = self.find_data('models')
self.cfg = Config(MacsyDefaults(), args)
self.model_name = 'foo'
self.model_location = ModelLocation(path=os.path.join(args.models_dir, self.model_name))
self.profile_factory = ProfileFactory(self.cfg)
self.model = Model("foo/model_A", 10)
c_gene_sctn = CoreGene(self.model_location, "sctN", self.profile_factory)
gene_sctn = ModelGene(c_gene_sctn, self.model)
c_gene_sctn_flg = CoreGene(self.model_location, "sctN_FLG", self.profile_factory)
gene_sctn_flg = Exchangeable(c_gene_sctn_flg, gene_sctn)
gene_sctn.add_exchangeable(gene_sctn_flg)
c_gene_sctj = CoreGene(self.model_location, "sctJ", self.profile_factory)
gene_sctj = ModelGene(c_gene_sctj, self.model)
c_gene_sctj_flg = CoreGene(self.model_location, "sctJ_FLG", self.profile_factory)
gene_sctj_flg = Exchangeable(c_gene_sctj_flg, gene_sctj)
gene_sctj.add_exchangeable(gene_sctj_flg)
c_gene_gspd = CoreGene(self.model_location, "gspD", self.profile_factory)
gene_gspd = ModelGene(c_gene_gspd, self.model)
c_gene_flgb = CoreGene(self.model_location, "flgB", self.profile_factory)
gene_gspd_ex = Exchangeable(c_gene_flgb, gene_gspd)
gene_gspd.add_exchangeable(gene_gspd_ex)
c_gene_abc = CoreGene(self.model_location, "abc", self.profile_factory)
gene_abc = ModelGene(c_gene_abc, self.model)
c_gene_tadz = CoreGene(self.model_location, "tadZ", self.profile_factory)
gene_abc_ex = Exchangeable(c_gene_tadz, gene_abc)
gene_abc.add_exchangeable(gene_abc_ex)
c_gene_toto = CoreGene(self.model_location, "toto", self.profile_factory)
gene_toto = ModelGene(c_gene_toto, self.model)
c_gene_totote = CoreGene(self.model_location, "totote", self.profile_factory)
gene_toto_ex = Exchangeable(c_gene_totote, gene_toto)
gene_toto.add_exchangeable(gene_toto_ex)
self.model.add_mandatory_gene(gene_sctn)
self.model.add_mandatory_gene(gene_sctj)
self.model.add_accessory_gene(gene_gspd)
self.model.add_neutral_gene(gene_toto)
self.model.add_forbidden_gene(gene_abc)
self.c_hits = {
'ch_sctj': CoreHit(c_gene_sctj, "hit_sctj", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20),
'ch_sctj_flg': CoreHit(c_gene_sctj_flg, "hit_sctj_flg", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20),
'ch_sctn': CoreHit(c_gene_sctn, "hit_sctn", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20),
'ch_sctn_flg': CoreHit(c_gene_sctn_flg, "hit_sctn_flg", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20),
'ch_gspd': CoreHit(c_gene_gspd, "hit_gspd", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20),
'ch_gspd_ex': CoreHit(c_gene_flgb, "hit_gspd_an", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20),
'ch_abc': CoreHit(c_gene_abc, "hit_abc", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20),
'ch_abc_ex': CoreHit(c_gene_tadz, "hit_abc_ho", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20),
'ch_toto': CoreHit(c_gene_toto, "hit_toto", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20),
'ch_toto_ex': CoreHit(c_gene_totote, "hit_toto_ho", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20),
}
self.m_hits = {
'mh_sctj': ModelHit(self.c_hits['ch_sctj'], gene_sctj, GeneStatus.MANDATORY),
'mh_sctj_flg': ModelHit(self.c_hits['ch_sctj_flg'], gene_sctj_flg, GeneStatus.MANDATORY),
'mh_sctn': ModelHit(self.c_hits['ch_sctn'], gene_sctn, GeneStatus.MANDATORY),
'mh_sctn_flg': ModelHit(self.c_hits['ch_sctn_flg'], gene_sctn_flg, GeneStatus.MANDATORY),
'mh_gspd': ModelHit(self.c_hits['ch_gspd'], gene_gspd, GeneStatus.ACCESSORY),
'mh_gspd_ex': ModelHit(self.c_hits['ch_gspd_ex'], gene_gspd_ex, GeneStatus.ACCESSORY),
'mh_abc': ModelHit(self.c_hits['ch_abc'], gene_abc, GeneStatus.FORBIDDEN),
'mh_abc_ex': ModelHit(self.c_hits['ch_abc_ex'], gene_abc_ex, GeneStatus.FORBIDDEN),
'mh_toto': ModelHit(self.c_hits['ch_toto'], gene_toto, GeneStatus.NEUTRAL),
'mh_toto_ex': ModelHit(self.c_hits['ch_toto_ex'], gene_toto_ex, GeneStatus.NEUTRAL)
}
def test_sort_hits_by_status(self):
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
mandatory_exp = [self.m_hits['mh_sctn'], self.m_hits['mh_sctj']]
accessory_exp = [self.m_hits['mh_gspd']]
neutral_exp = [self.m_hits['mh_toto']]
forbidden_exp = [self.m_hits['mh_abc']]
mandatory, accessory, neutral, forbidden = ordered_match_maker.sort_hits_by_status(mandatory_exp + accessory_exp + neutral_exp + forbidden_exp)
self.assertListEqual([h.gene.name for h in mandatory_exp], [h.gene.name for h in mandatory])
self.assertListEqual([h.gene.name for h in accessory_exp], [h.gene.name for h in accessory])
self.assertListEqual([h.gene.name for h in neutral_exp], [h.gene.name for h in neutral])
self.assertListEqual([h.gene.name for h in forbidden_exp], [h.gene.name for h in forbidden])
# do the same but with exchangeable
mandatory_exp_exch = [self.m_hits['mh_sctn_flg'], self.m_hits['mh_sctj_flg']]
accessory_exp_exch = [self.m_hits['mh_gspd_ex']]
neutral_exp_exch = [self.m_hits['mh_toto_ex']]
forbidden_exp_exch = [self.m_hits['mh_abc_ex']]
mandatory, accessory, neutral, forbidden = ordered_match_maker.sort_hits_by_status(mandatory_exp_exch +
accessory_exp_exch +
neutral_exp_exch +
forbidden_exp_exch)
self.assertListEqual([h.gene.name for h in mandatory_exp_exch], [h.gene.name for h in mandatory])
self.assertListEqual([h.gene.name for h in accessory_exp_exch], [h.gene.name for h in accessory])
self.assertListEqual([h.gene.name for h in neutral_exp_exch], [h.gene.name for h in neutral])
self.assertListEqual([h.gene.name for h in forbidden_exp_exch], [h.gene.name for h in forbidden])
# test if gene_ref is the ModelGene
# alternate_of return the ModelGene of the function
self.assertListEqual([h.gene.name for h in mandatory_exp], [h.gene_ref.alternate_of().name for h in mandatory])
self.assertListEqual([h.gene.name for h in accessory_exp], [h.gene_ref.alternate_of().name for h in accessory])
self.assertListEqual([h.gene.name for h in neutral_exp], [h.gene_ref.alternate_of().name for h in neutral])
self.assertListEqual([h.gene.name for h in forbidden_exp], [h.gene_ref.alternate_of().name for h in forbidden])
# test if the hit does not refer to gene belonging to the model
model2 = Model("foo/model_B", 10)
cg_fliE = CoreGene(self.model_location, "fliE", self.profile_factory)
ch_fliE = CoreHit(cg_fliE, "hit_fliE", 803, "replicon_id", 1, 1.0, 1.0, 1.0, 1.0, 10, 20)
mg_fliE = ModelGene(cg_fliE, model2)
mh_fliE = ModelHit(ch_fliE, mg_fliE, GeneStatus.NEUTRAL)
with self.assertRaises(MacsypyError) as ctx:
with self.catch_log():
ordered_match_maker.sort_hits_by_status([mh_fliE])
self.assertEqual(str(ctx.exception),
"Gene 'fliE' not found in model 'foo/model_B'")
def test_ordered_match(self):
#####################
# test single locus #
#####################
# it lack one mandatory gene
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 3
c1 = Cluster([self.m_hits['mh_sctj'], self.m_hits['mh_gspd']], self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1])
self.assertIsInstance(res, RejectedCandidate)
self.assertEqual(res.reasons,
["The quorum of mandatory genes required (2) is not reached: 1",
"The quorum of genes required (3) is not reached: 2"])
# all quorum are reached
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
c1 = Cluster([self.m_hits['mh_sctj'], self.m_hits['mh_sctn'], self.m_hits['mh_gspd']], self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1])
self.assertIsInstance(res, System)
# with one mandatory analog
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
c1 = Cluster([self.m_hits['mh_sctj_flg'], self.m_hits['mh_sctn'], self.m_hits['mh_gspd']], self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1])
self.assertIsInstance(res, System)
# with one accessory analog
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
c1 = Cluster([self.m_hits['mh_sctj'], self.m_hits['mh_sctn'], self.m_hits['mh_gspd_ex']], self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1])
self.assertIsInstance(res, System)
# the min_gene_required quorum is not reached
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 4
c1 = Cluster([self.m_hits['mh_sctj'], self.m_hits['mh_sctn_flg'], self.m_hits['mh_gspd']], self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1])
self.assertIsInstance(res, RejectedCandidate)
self.assertListEqual(res.reasons,
["The quorum of genes required (4) is not reached: 3"])
# the min_gene_required quorum is not reached even there is a neutral
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 4
c1 = Cluster([self.m_hits['mh_sctj'], self.m_hits['mh_sctn_flg'], self.m_hits['mh_gspd'], self.m_hits['mh_toto']],
self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1])
self.assertIsInstance(res, RejectedCandidate)
self.assertEqual(res.reasons,
["The quorum of genes required (4) is not reached: 3"])
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 4
c1 = Cluster([self.m_hits['mh_sctj'], self.m_hits['mh_sctn_flg'], self.m_hits['mh_gspd'], self.m_hits['mh_toto_ex']],
self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1])
self.assertIsInstance(res, RejectedCandidate)
self.assertEqual(res.reasons,
["The quorum of genes required (4) is not reached: 3"])
# the cluster contain a forbidden gene
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
c1 = Cluster([self.m_hits['mh_sctj'], self.m_hits['mh_sctn'], self.m_hits['mh_gspd'], self.m_hits['mh_abc']],
self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1])
self.assertIsInstance(res, RejectedCandidate)
self.assertEqual(res.reasons, ["There is 1 forbidden genes occurrence(s): abc"])
# the cluster contain a forbidden gene homolog
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
c1 = Cluster([self.m_hits['mh_sctj'], self.m_hits['mh_sctn'], self.m_hits['mh_gspd'], self.m_hits['mh_abc_ex']],
self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1])
self.assertIsInstance(res, RejectedCandidate)
self.assertEqual(res.reasons, ["There is 1 forbidden genes occurrence(s): tadZ"])
#####################
# test multi loci #
#####################
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
c1 = Cluster([self.m_hits['mh_sctj'], self.m_hits['mh_sctn']], self.model, self.cfg.hit_weights())
c2 = Cluster([self.m_hits['mh_gspd']], self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1, c2])
self.assertIsInstance(res, System)
# with one analog an one homolog
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
c1 = Cluster([self.m_hits['mh_sctj_flg'], self.m_hits['mh_sctn_flg']], self.model, self.cfg.hit_weights())
c2 = Cluster([self.m_hits['mh_gspd_ex']], self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1, c2])
self.assertIsInstance(res, System)
# with one analog an one homolog and one forbidden in 3 clusters
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
c1 = Cluster([self.m_hits['mh_sctj_flg'], self.m_hits['mh_sctn_flg']], self.model, self.cfg.hit_weights())
c2 = Cluster([self.m_hits['mh_gspd']], self.model, self.cfg.hit_weights())
c3 = Cluster([self.m_hits['mh_abc']], self.model, self.cfg.hit_weights())
ordered_match_maker = OrderedMatchMaker(self.model, self.cfg.redundancy_penalty())
res = ordered_match_maker.match([c1, c2, c3])
self.assertEqual(res.reasons, ["There is 1 forbidden genes occurrence(s): abc"])
def test_unordered_match(self):
# it lack one mandatory gene
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 3
hits = [self.m_hits['mh_sctj'], self.m_hits['mh_gspd']]
unordered_match_maker = UnorderedMatchMaker(self.model)
res = unordered_match_maker.match(hits)
self.assertIsInstance(res, UnlikelySystem)
self.assertEqual(res.reasons,
["The quorum of mandatory genes required (2) is not reached: 1",
"The quorum of genes required (3) is not reached: 2"])
# all quorum are reached
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
hits = [self.m_hits['mh_sctj'], self.m_hits['mh_sctn'], self.m_hits['mh_gspd']]
unordered_match_maker = UnorderedMatchMaker(self.model)
res = unordered_match_maker.match(hits)
self.assertIsInstance(res, LikelySystem)
# with one mandatory analog
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
hits = [self.m_hits['mh_sctj_flg'], self.m_hits['mh_sctn'], self.m_hits['mh_gspd']]
unordered_match_maker = UnorderedMatchMaker(self.model)
res = unordered_match_maker.match(hits)
self.assertIsInstance(res, LikelySystem)
# with one accessory analog
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
hits = [self.m_hits['mh_sctj'], self.m_hits['mh_sctn'], self.m_hits['mh_gspd_ex']]
unordered_match_maker = UnorderedMatchMaker(self.model)
res = unordered_match_maker.match(hits)
self.assertIsInstance(res, LikelySystem)
# the min_gene_required quorum is not reached
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 4
hits = [self.m_hits['mh_sctj'], self.m_hits['mh_sctn_flg'], self.m_hits['mh_gspd']]
unordered_match_maker = UnorderedMatchMaker(self.model)
res = unordered_match_maker.match(hits)
self.assertIsInstance(res, UnlikelySystem)
self.assertEqual(res.reasons,
["The quorum of genes required (4) is not reached: 3"])
# the min_gene_required quorum is not reached even there is a neutral
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 4
hits = [self.m_hits['mh_sctj'], self.m_hits['mh_sctn_flg'], self.m_hits['mh_gspd'], self.m_hits['mh_toto']]
unordered_match_maker = UnorderedMatchMaker(self.model)
res = unordered_match_maker.match(hits)
self.assertIsInstance(res, UnlikelySystem)
self.assertEqual(res.reasons,
["The quorum of genes required (4) is not reached: 3"])
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 4
hits = [self.m_hits['mh_sctj'], self.m_hits['mh_sctn_flg'], self.m_hits['mh_gspd'], self.m_hits['mh_toto_ex']]
unordered_match_maker = UnorderedMatchMaker(self.model)
res = unordered_match_maker.match(hits)
self.assertIsInstance(res, UnlikelySystem)
self.assertEqual(res.reasons,
["The quorum of genes required (4) is not reached: 3"])
# the hits contain a forbidden gene
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
allowed_hits = [self.m_hits['mh_sctj'], self.m_hits['mh_sctn'], self.m_hits['mh_gspd']]
forbidden_hits = [self.m_hits['mh_abc']]
unordered_match_maker = UnorderedMatchMaker(self.model)
res = unordered_match_maker.match(allowed_hits + forbidden_hits)
self.assertIsInstance(res, LikelySystem)
self.assertListEqual([(h.id, h.position) for h in res.hits],
[(h.id, h.position) for h in allowed_hits + forbidden_hits])
self.assertListEqual(res._forbidden_hits, [self.m_hits['mh_abc']])
# the hits contain a forbidden gene homolog
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
hits = [self.m_hits['mh_sctj'], self.m_hits['mh_sctn'], self.m_hits['mh_gspd'], self.m_hits['mh_abc_ex']]
unordered_match_maker = UnorderedMatchMaker(self.model)
res = unordered_match_maker.match(hits)
self.assertIsInstance(res, LikelySystem)
self.assertListEqual(res._forbidden_hits, [self.m_hits['mh_abc_ex']])
# only one forbidden hit (no mandatory, accessory, neutral)
self.model._min_mandatory_genes_required = 2
self.model._min_genes_required = 1
allowed_hits = []
forbidden_hits = [self.m_hits['mh_abc']]
unordered_match_maker = UnorderedMatchMaker(self.model)
res = unordered_match_maker.match(allowed_hits + forbidden_hits)
self.assertIsNone(res)
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