def test_filter_mutation_status():
braf_mut = Agent('BRAF', mutations=MutCondition('600', 'V', 'E'))
braf_other_mut = Agent('BRAF', mutations=MutCondition('555', 'K', 'G'))
st1 = Phosphorylation(braf_mut, Agent('a'))
st2 = Phosphorylation(braf_other_mut, Agent('a'))
mutations = {'BRAF': [('V', '600', 'E')]}
deletions = []
st_out = ac.filter_mutation_status([st1, st2], mutations, deletions)
assert(len(st_out) == 1)
mutations = {}
deletions = ['a']
st_out = ac.filter_mutation_status([st1, st2], mutations, deletions)
assert(len(st_out) == 0)
def contextualize_stmts(stmts, cell_line, genes):
"""Contextualize model at the level of INDRA Statements."""
to_remove = []
cell_line_ccle = cell_line + '_SKIN'
# Remove genes with CNA = -2
print('Contextualize by CNA')
cna = cbio_client.get_ccle_cna(genes, [cell_line_ccle])[cell_line_ccle]
for gene in genes:
if cna.get(gene) == -2:
to_remove.append(gene)
print('To remove CNA: %s' % gene)
# Remove genes with transcripts in bottom 5%
print('Contextualize by mRNA')
mrna = cbio_client.get_ccle_mrna(genes, [cell_line_ccle])[cell_line_ccle]
mrna_vals = [v for v in mrna.values() if v]
if mrna_vals:
thresh = numpy.percentile(mrna_vals, 5.0)
for gene, val in mrna.items():
if val and val < thresh:
to_remove.append(gene)
print('To remove mRNA: %s' % gene)
# Remove genes with nonsense mutations
print('Contextualize by nonsense mutations')
variants = read_ccle_variants(genes)
to_remove_nonsense = list(variants['nonsense'][cell_line_ccle].keys())
if to_remove_nonsense:
print('To remove nonsense: %s' % ', '.join(to_remove_nonsense))
to_remove += to_remove_nonsense
# Remove Statements for these genes
new_stmts = []
for stmt in stmts:
any_to_remove = False
for agent in stmt.agent_list():
if agent is not None and agent.name in to_remove:
any_to_remove = True
break
if not any_to_remove:
new_stmts.append(stmt)
# Remove Statements with irrelevant mutations
print('Contextualize by missense mutations')
mutations = variants['missense'][cell_line_ccle]
muts_to_use = {}
for gene, mut_list in mutations.items():
muts_to_use[gene] = []
for mut in mut_list:
muts_to_use[gene].append(mut)
stmts = ac.filter_mutation_status(new_stmts, mutations, [])
return stmts
def preprocess_stmts(stmts, data_genes):
# Filter the INDRA Statements to be put into the model
stmts = ac.filter_mutation_status(stmts,
{'BRAF': [('V', '600', 'E')]}, ['PTEN'])
stmts = ac.filter_by_type(stmts, Complex, invert=True)
stmts = ac.filter_direct(stmts)
stmts = ac.filter_belief(stmts, 0.95)
stmts = ac.filter_top_level(stmts)
stmts = ac.filter_gene_list(stmts, data_genes, 'all')
stmts = ac.filter_enzyme_kinase(stmts)
stmts = ac.filter_mod_nokinase(stmts)
stmts = ac.filter_transcription_factor(stmts)
# Simplify activity types
ml = MechLinker(stmts)
ml.gather_explicit_activities()
ml.reduce_activities()
ml.gather_modifications()
ml.reduce_modifications()
af_stmts = ac.filter_by_type(ml.statements, ActiveForm)
non_af_stmts = ac.filter_by_type(ml.statements, ActiveForm, invert=True)
af_stmts = ac.run_preassembly(af_stmts)
stmts = af_stmts + non_af_stmts
# Replace activations when possible
ml = MechLinker(stmts)
ml.gather_explicit_activities()
ml.replace_activations()
# Require active forms
ml.require_active_forms()
num_stmts = len(ml.statements)
while True:
# Remove inconsequential PTMs
ml.statements = ac.filter_inconsequential_mods(ml.statements,
get_mod_whitelist())
ml.statements = ac.filter_inconsequential_acts(ml.statements,
get_mod_whitelist())
if num_stmts <= len(ml.statements):
break
num_stmts = len(ml.statements)
stmts = ml.statements
return stmts
def test_filter_mutation_status():
braf_mut = Agent('BRAF', mutations=MutCondition('600', 'V', 'E'))
braf_other_mut = Agent('BRAF', mutations=MutCondition('555', 'K', 'G'))
st1 = Phosphorylation(braf_mut, Agent('a'))
st2 = Phosphorylation(braf_other_mut, Agent('a'))
mutations = {'BRAF': [('V', '600', 'E')]}
deletions = []
st_out = ac.filter_mutation_status([st1, st2], mutations, deletions)
assert len(st_out) == 1
mutations = {}
deletions = ['a']
st_out = ac.filter_mutation_status([st1, st2], mutations, deletions)
assert len(st_out) == 0
# Can we filter statements out based on bound conditions?
mutations = {'BRAF': [('V', '600', 'E')]}
deletions = []
braf_good_bound = deepcopy(braf_mut)
braf_good_bound.bound_conditions = [BoundCondition(braf_mut)]
#
braf_bad_bound = deepcopy(braf_mut)
braf_bad_bound.bound_conditions = [BoundCondition(braf_other_mut)]
#
st3 = Phosphorylation(braf_good_bound, Agent('a'))
st4 = Phosphorylation(braf_bad_bound, Agent('a'))
#
st_out = ac.filter_mutation_status([st3], mutations, deletions)
assert len(st_out) == 1
#
st_out = ac.filter_mutation_status([st4], mutations, deletions)
assert len(st_out) == 0
# Can we remove bound conditions based on our filter?
st_out = ac.filter_mutation_status([st3],
mutations,
deletions,
remove_bound=True)
assert len(st_out[0].enz.bound_conditions) == 1
#
st_out = ac.filter_mutation_status([st4],
mutations,
deletions,
remove_bound=True)
assert len(st_out[0].enz.bound_conditions) == 0
def test_filter_mutation_status():
braf_mut = Agent('BRAF', mutations=MutCondition('600', 'V', 'E'))
braf_other_mut = Agent('BRAF', mutations=MutCondition('555', 'K', 'G'))
st1 = Phosphorylation(braf_mut, Agent('a'))
st2 = Phosphorylation(braf_other_mut, Agent('a'))
mutations = {'BRAF': [('V', '600', 'E')]}
deletions = []
st_out = ac.filter_mutation_status([st1, st2], mutations, deletions)
assert len(st_out) == 1
mutations = {}
deletions = ['a']
st_out = ac.filter_mutation_status([st1, st2], mutations, deletions)
assert len(st_out) == 0
# Can we filter statements out based on bound conditions?
mutations = {'BRAF': [('V', '600', 'E')]}
deletions = []
braf_good_bound = deepcopy(braf_mut)
braf_good_bound.bound_conditions = [BoundCondition(braf_mut)]
#
braf_bad_bound = deepcopy(braf_mut)
braf_bad_bound.bound_conditions = [BoundCondition(braf_other_mut)]
#
st3 = Phosphorylation(braf_good_bound, Agent('a'))
st4 = Phosphorylation(braf_bad_bound, Agent('a'))
#
st_out = ac.filter_mutation_status([st3], mutations, deletions)
assert len(st_out) == 1
#
st_out = ac.filter_mutation_status([st4], mutations, deletions)
assert len(st_out) == 0
# Can we remove bound conditions based on our filter?
st_out = ac.filter_mutation_status([st3], mutations, deletions,
remove_bound=True)
assert len(st_out[0].enz.bound_conditions) == 1
#
st_out = ac.filter_mutation_status([st4], mutations, deletions,
remove_bound=True)
assert len(st_out[0].enz.bound_conditions) == 0