def setUp(self): # pylint; disable-msg=C0103
"""test fixture"""
self.search_distances = {'upstream': (-20, 150)}
self.scan_distances = {'upstream': (-30, 250)}
self.ratio_matrix = dm.create_from_csv('example_data/hal/halo_ratios5.tsv',
filters=[dm.nochange_filter, dm.center_scale_filter])
self.organism = testutil.make_halo(self.search_distances, self.scan_distances,
self.ratio_matrix)
self.config_params = {'memb.min_cluster_rows_allowed': 3,
'memb.max_cluster_rows_allowed': 70,
'multiprocessing': False,
'num_cores': None,
'memb.clusters_per_row': 2,
'memb.clusters_per_col': int(round(43 * 2.0 / 3.0)),
'num_clusters': 43,
'output_dir': 'out',
'remap_network_nodes': False,
'use_BSCM': False,
'num_iterations': 2000,
'debug': {},
'search_distances': {'upstream': (-20, 150)},
'Columns': {'schedule': lambda i: True },
'Rows': {'schedule': lambda i: True, 'scaling': ('scaling_const', 6.0) },
'Motifs': {'schedule': lambda i: True,
'scaling': ('scaling_rvec', 'seq(0, 1, length=num_iterations*3/4)')},
'MEME': {'version': '4.3.0',
'global_background': False,
'schedule': lambda i: True,
'nmotifs_rvec': 'c(rep(1, num_iterations/3), rep(2, num_iterations/3))',
'max_width': 24, 'arg_mod': 'zoops',
'background_order': 3, 'use_revcomp': 'True'},
'Networks': {'schedule': lambda i: True, 'scaling': ('scaling_rvec', 'seq(1e-5, 0.5, length=num_iterations*3/4)')}}
self.membership = self.__read_members() # relies on config_params
self.iteration_result = { 'iteration': 51, 'score_means': {} }
def test_motif_scoring(self):
"""tests the motif scoring in integration"""
search_distances = {'upstream': (-20, 150)}
scan_distances = {'upstream': (-30, 250)}
matrix_factory = dm.DataMatrixFactory([dm.nochange_filter, dm.center_scale_filter])
infile = util.read_dfile('example_data/hal/halo_ratios5.tsv',
has_header=True, quote='\"')
ratio_matrix = matrix_factory.create_from(infile)
organism = testutil.make_halo(search_distances, scan_distances, ratio_matrix)
membership = FakeMembership()
config_params = {'memb.min_cluster_rows_allowed': 3,
'memb.max_cluster_rows_allowed': 70,
'multiprocessing': False,
'num_clusters': 1,
'output_dir': 'out',
'debug': {},
'search_distances': {'upstream': (-20, 150)},
'num_iterations': 2000,
'MEME': {'schedule': lambda i: True,
'version': '4.3.0',
'global_background': False,
'arg_mod': 'zoops',
'nmotifs_rvec': 'c(rep(1, num_iterations/3), rep(2, num_iterations/3))',
'use_revcomp': 'True', 'max_width': 24, 'background_order': 3},
'Motifs': {'schedule': lambda i: True, 'scaling': ('scaling_const', 1.0)}}
func = motif.MemeScoringFunction(organism, membership, ratio_matrix,
config_params=config_params)
iteration_result = { 'iteration': 100 }
matrix = func.compute(iteration_result)
def setUp(self): # pylint; disable-msg=C0103
"""test fixture"""
self.search_distances = {'upstream': (-20, 150)}
self.scan_distances = {'upstream': (-30, 250)}
matrix_factory = dm.DataMatrixFactory(
[dm.nochange_filter, dm.center_scale_filter])
infile = util.read_dfile('example_data/hal/halo_ratios5.tsv',
has_header=True,
quote='\"')
self.ratio_matrix = matrix_factory.create_from(infile)
self.organism = testutil.make_halo(self.search_distances,
self.scan_distances,
self.ratio_matrix)
self.config_params = {
'memb.min_cluster_rows_allowed': 3,
'memb.max_cluster_rows_allowed': 70,
'multiprocessing': False,
'memb.clusters_per_row': 2,
'memb.clusters_per_col': int(round(43 * 2.0 / 3.0)),
'num_clusters': 43,
'num_iterations': 2000
}
self.membership = self.__read_members() # relies on config_params
self.iteration_result = {'iteration': 51}
def test_motif_scoring(self):
"""tests the motif scoring in integration"""
search_distances = {"upstream": (-20, 150)}
scan_distances = {"upstream": (-30, 250)}
matrix_factory = dm.DataMatrixFactory([dm.nochange_filter, dm.center_scale_filter])
infile = util.read_dfile("example_data/hal/halo_ratios5.tsv", has_header=True, quote='"')
ratio_matrix = matrix_factory.create_from(infile)
organism = testutil.make_halo(search_distances, scan_distances, ratio_matrix)
membership = FakeMembership()
config_params = {
"memb.min_cluster_rows_allowed": 3,
"memb.max_cluster_rows_allowed": 70,
"multiprocessing": False,
"num_clusters": 1,
"output_dir": "out",
"debug": {},
"search_distances": {"upstream": (-20, 150)},
"num_iterations": 2000,
"MEME": {
"schedule": lambda i: True,
"version": "4.3.0",
"global_background": False,
"arg_mod": "zoops",
"nmotifs_rvec": "c(rep(1, num_iterations/3), rep(2, num_iterations/3))",
"use_revcomp": "True",
"max_width": 24,
"background_order": 3,
},
"Motifs": {"schedule": lambda i: True, "scaling": ("scaling_const", 1.0)},
}
func = motif.MemeScoringFunction(organism, membership, ratio_matrix, config_params=config_params)
iteration_result = {"iteration": 100}
matrix = func.compute(iteration_result)
def test_motif_scoring(self):
"""tests the motif scoring in integration"""
search_distances = {'upstream': (-20, 150)}
scan_distances = {'upstream': (-30, 250)}
matrix_factory = dm.DataMatrixFactory(
[dm.nochange_filter, dm.center_scale_filter])
infile = util.read_dfile('example_data/hal/halo_ratios5.tsv',
has_header=True,
quote='\"')
ratio_matrix = matrix_factory.create_from(infile)
organism = testutil.make_halo(search_distances, scan_distances,
ratio_matrix)
membership = FakeMembership()
config_params = {
'memb.min_cluster_rows_allowed': 3,
'memb.max_cluster_rows_allowed': 70,
'multiprocessing': False,
'num_clusters': 1,
'output_dir': 'out',
'debug': {},
'search_distances': {
'upstream': (-20, 150)
},
'num_iterations': 2000,
'MEME': {
'schedule': lambda i: True,
'version': '4.3.0',
'global_background': False,
'arg_mod': 'zoops',
'nmotifs_rvec':
'c(rep(1, num_iterations/3), rep(2, num_iterations/3))',
'use_revcomp': 'True',
'max_width': 24,
'background_order': 3
},
'Motifs': {
'schedule': lambda i: True,
'scaling': ('scaling_const', 1.0)
}
}
func = motif.MemeScoringFunction(organism,
membership,
ratio_matrix,
config_params=config_params)
iteration_result = {'iteration': 100}
matrix = func.compute(iteration_result)
def setUp(self): # pylint; disable-msg=C0103
"""test fixture"""
self.search_distances = {'upstream': (-20, 150)}
self.scan_distances = {'upstream': (-30, 250)}
self.ratio_matrix = dm.create_from_csv('example_data/hal/halo_ratios5.tsv',
filters=[dm.nochange_filter, dm.center_scale_filter])
self.organism = testutil.make_halo(self.search_distances, self.scan_distances,
self.ratio_matrix)
self.config_params = {'memb.min_cluster_rows_allowed': 3,
'memb.max_cluster_rows_allowed': 70,
'multiprocessing': False,
'memb.clusters_per_row': 2,
'memb.clusters_per_col': int(round(43 * 2.0 / 3.0)),
'num_clusters': 43,
'num_iterations': 2000}
self.membership = self.__read_members() # relies on config_params
self.iteration_result = { 'iteration': 51 }
def test_get_one_sequence(self):
"""get one simple sequence"""
search_distances = {'upstream': (-20, 150)}
scan_distances = {'upstream': (-30, 250)}
halo = testutil.make_halo(search_distances, scan_distances)
print("------")
print("VNG1551G: ", halo.features_for_genes(['VNG1551G']))
print("VNG1550G: ", halo.features_for_genes(['VNG1550G']))
print("VNG1561C: ", halo.features_for_genes(['VNG1561C']))
print("------")
seq = halo.sequences_for_genes_search(['VNG1551G'], 'upstream')
self.assertTrue('NP_280354.1' in seq)
print("FINAL LOC: ", seq['NP_280354.1'][0])
"""
operon_map = halo.operon_map()
for key, value in operon_map.items():
print("'%s' -> '%s'" % (key, value))
print("OPERON MAPPED TO: ", halo.operon_map()['NP_280354.1'])
"""
self.assertEquals('GTGATTCGACCATTACTGCAAGTTCAGACGACCCCAATTCAAGTAGTTTTGTGTAACCGCCGGCGTCGGGGGCGCTCGCGCCCATCTAAGAAAGCTCACTTTCCCTAATACAATCAAAATTGTTTTGGGTGCTTCTGACGTTGTGCCACCGATGGCACAGACACAGCTCC',
seq['NP_280354.1'][1])
def test_get_one_sequence(self):
"""get one simple sequence"""
search_distances = {'upstream': (-20, 150)}
scan_distances = {'upstream': (-30, 250)}
halo = testutil.make_halo(search_distances, scan_distances)
print "------"
print "VNG1551G: ", halo.features_for_genes(['VNG1551G'])
print "VNG1550G: ", halo.features_for_genes(['VNG1550G'])
print "VNG1561C: ", halo.features_for_genes(['VNG1561C'])
print "------"
seq = halo.sequences_for_genes_search(['VNG1551G'], 'upstream')
self.assertTrue('NP_280354.1' in seq)
print "FINAL LOC: ", seq['NP_280354.1'][0]
"""
operon_map = halo.operon_map()
for key, value in operon_map.items():
print "'%s' -> '%s'" % (key, value)
print "OPERON MAPPED TO: ", halo.operon_map()['NP_280354.1']
"""
self.assertEquals(
'GTGATTCGACCATTACTGCAAGTTCAGACGACCCCAATTCAAGTAGTTTTGTGTAACCGCCGGCGTCGGGGGCGCTCGCGCCCATCTAAGAAAGCTCACTTTCCCTAATACAATCAAAATTGTTTTGGGTGCTTCTGACGTTGTGCCACCGATGGCACAGACACAGCTCC',
seq['NP_280354.1'][1])
def setUp(self): # pylint; disable-msg=C0103
"""test fixture"""
self.search_distances = {'upstream': (-20, 150)}
self.scan_distances = {'upstream': (-30, 250)}
matrix_factory = dm.DataMatrixFactory([dm.nochange_filter, dm.center_scale_filter])
infile = util.read_dfile('example_data/hal/halo_ratios5.tsv',
has_header=True, quote='\"')
self.ratio_matrix = matrix_factory.create_from(infile)
self.organism = testutil.make_halo(self.search_distances, self.scan_distances,
self.ratio_matrix)
self.config_params = {'memb.min_cluster_rows_allowed': 3,
'memb.max_cluster_rows_allowed': 70,
'multiprocessing': False,
'num_cores': None,
'memb.clusters_per_row': 2,
'memb.clusters_per_col': int(round(43 * 2.0 / 3.0)),
'num_clusters': 43,
'output_dir': 'out',
'remap_network_nodes': False,
'use_BSCM': False,
'num_iterations': 2000,
'debug': {},
'search_distances': {'upstream': (-20, 150)},
'Columns': {'schedule': lambda i: True },
'Rows': {'schedule': lambda i: True, 'scaling': ('scaling_const', 6.0) },
'Motifs': {'schedule': lambda i: True,
'scaling': ('scaling_rvec', 'seq(0, 1, length=num_iterations*3/4)')},
'MEME': {'version': '4.3.0',
'global_background': False,
'schedule': lambda i: True,
'nmotifs_rvec': 'c(rep(1, num_iterations/3), rep(2, num_iterations/3))',
'max_width': 24, 'arg_mod': 'zoops',
'background_order': 3, 'use_revcomp': 'True'},
'Networks': {'schedule': lambda i: True, 'scaling': ('scaling_rvec', 'seq(1e-5, 0.5, length=num_iterations*3/4)')}}
self.membership = self.__read_members() # relies on config_params
self.iteration_result = { 'iteration': 51, 'score_means': {} }