# The file in which the preassembled statements will be saved
pre_stmts_file = prefixed_pkl('preassembled')
if reassemble:
# Load various files that were previously produced
sources = [
'indradb', 'trips', 'bel', 'biopax', 'phosphosite', 'r3', 'sparser'
]
stmts = []
for source in sources:
stmts += ac.load_statements(prefixed_pkl(source))
stmts = ac.filter_no_hypothesis(stmts)
# Fix grounding and filter to grounded entities and for proteins,
# filter to the human ones
stmts = ac.map_grounding(stmts)
stmts = ac.filter_grounded_only(stmts)
stmts = ac.filter_human_only(stmts)
# Combinatorially expand protein families
stmts = ac.expand_families(stmts)
# Apply a strict filter to statements based on the gene names
stmts = ac.filter_gene_list(stmts, gene_names, 'all')
# Fix errors in references to protein sequences
stmts = ac.map_sequence(stmts)
# Run preassembly and save result
stmts = ac.run_preassembly(stmts, return_toplevel=False)
ac.dump_statements(stmts, pre_stmts_file)
# Load the preassembled statements
stmts = ac.load_statements(pre_stmts_file)
# Run assembly into a PySB model
assemble_pysb.assemble_pysb(stmts, gene_names, contextualize=True)
reading_stmts = reach_stmts + extra_stmts
reading_stmts = ac.map_grounding(reading_stmts,
save=pjoin(outf,
'gmapped_reading.pkl'))
stmts = prior_stmts + reading_stmts + extra_stmts
stmts = ac.filter_grounded_only(stmts)
stmts = ac.filter_genes_only(stmts, specific_only=False)
stmts = ac.filter_human_only(stmts)
stmts = ac.expand_families(stmts)
stmts = ac.filter_gene_list(stmts, data_genes, 'one')
stmts = ac.map_sequence(stmts, save=pjoin(outf, 'smapped.pkl'))
#stmts = ac.load_statements(pjoin(outf, 'smapped.pkl'))
stmts = ac.run_preassembly(stmts,
return_toplevel=False,
save=pjoin(outf, 'preassembled.pkl'),
poolsize=4)
### PySB assembly
if 'pysb' in assemble_models:
pysb_model = assemble_pysb(stmts, data_genes,
pjoin(outf, 'korkut_model_pysb.py'))
### SIF assembly
if 'sif' in assemble_models:
sif_str = assemble_sif(stmts, data, pjoin(outf,
'PKN-korkut_all_ab.sif'))
### CX assembly
if 'cx' in assemble_models:
for network_type in ('high_belief', 'direct'):
cxa = assemble_cx(stmts, pjoin(outf, 'korkut_full'), network_type)
save=pjoin(outf, 'gmapped_prior.pkl'))
reading_stmts = ac.load_statements(pjoin(outf, 'phase3_stmts.pkl'))
reading_stmts = ac.map_grounding(reading_stmts,
save=pjoin(outf, 'gmapped_reading.pkl'))
stmts = prior_stmts + reading_stmts
stmts = ac.filter_grounded_only(stmts)
stmts = ac.filter_genes_only(stmts, specific_only=False)
stmts = ac.filter_human_only(stmts)
stmts = ac.expand_families(stmts)
stmts = ac.filter_gene_list(stmts, data_genes, 'one')
stmts = ac.map_sequence(stmts, save=pjoin(outf, 'smapped.pkl'))
stmts = ac.run_preassembly(stmts, return_toplevel=False,
save=pjoin(outf, 'preassembled.pkl'))
assemble_models = []
assemble_models.append('sif')
assemble_models.append('pysb')
assemble_models.append('cx')
### PySB assembly
if 'pysb' in assemble_models:
pysb_model = assemble_pysb(stmts, data_genes,
pjoin(outf, 'korkut_model_pysb.py'))
### SIF assembly
if 'sif' in assemble_models:
sif_str = assemble_sif(stmts, data, pjoin(outf, 'PKN-korkut_all_ab.sif'))
### CX assembly
if 'cx' in assemble_models:
cxa = assemble_cx(stmts, pjoin(outf, 'korkut_full_high_belief.cx'))