def process_output(output_file,source='S', sink='T', species_name='',debug=False,de_file=None,mcf=False):
'''
Run the standard post-processing steps for responseNet
'''
if not os.path.exists(output_file+'.txt'):
print 'Output file missing'
return dict(),dict(),0.0,set(),set(),set()
##Calculate node flow for ranking of signaling proteins
(node_flow,comm_flow,total)=calculate_node_flow(open(output_file+'.txt','r').readlines(),mcf)#returns a dictionary of node flow
#calculate enrichment statistic if mRNA are used?
#visualize
if total==0.0:
print 'No flow'
return total,node_flow,comm_flow,set(),set(),set()
phens,prots,tfs,mrnas=write_sif_file(output_file, source, sink,node_flow,comm_flow,debug,de_file,mcf)
##MODIFIED by SGOSLINE: added this to do identifer matching for the sif files
if(species_name.lower==''):
print 'No identifier matching, moving on...'
idfile=''
else:
# if(species_name.lower()=='mouse'):
# idfile=pickle.load(open(id_directory+'/10090protein.aliases.v9.0_geneName.pkl','r'))
# elif(species_name.lower()=='human'):
# idfile=pickle.load(open(id_directory+'/9606protein.aliases.v9.0_geneName.pkl','r'))
# elif(species_name.lower()=='yeast'):
# idfile=pickle.load(open(id_directory+'/4932protein.aliases.v9.0_geneName.pkl','r'))
# elif(species_name.lower()=='humaniref'):
# idfile=pickle.load(open(id_directory+'/9606mitab.01192011.uniq_miscore-localirefindex3-20110831.geneMapping.pkl','r'))
if species_name.lower()=='human':
idfile=pickle.load(open(id_directory+'/humanUniprotHugoEntryMapping.pkl','r'))
elif(species_name.lower()=='mouseiref'):
idfile=pickle.load(open(id_directory+'/mouse_genename_to_9606mitabiref.pkl','r'))
else:
idfile=''
if idfile!='':
print "Matching identifiers"
identifier_matching.parseSifFileFromStringToGeneName(open(output_file+'_all.sif','r'),output_file+'_all_symbol.sif',idfile)
identifier_matching.parseSifFileFromStringToGeneName(open(output_file+'_mcfs.sif','r'),output_file+'_mcfs_symbol.sif',idfile)
identifier_matching.parseSifFileFromStringToGeneName(open(output_file+'_no_mrna.sif','r'),output_file+'_no_mrna_symbol.sif',idfile)
#also for the edge attribute files
identifier_matching.parseAttrFileFromStringToGeneName(open(output_file+'_ppi_attributes.eda','r'),output_file+'_ppi_attributes_symbol.eda',idfile)
identifier_matching.parseAttrFileFromStringToGeneName(open(output_file+'_edge_commodity.eda','r'),output_file+'_edge_commodity_symbol.eda',idfile)
identifier_matching.parseAttrFileFromStringToGeneName(open(output_file+'_edge_type.eda','r'),output_file+'_edge_type_symbol.eda',idfile)
identifier_matching.parseTabFileFromStringToGeneName(open(output_file+'_node_comm_flow.noa','r'),output_file+'_node_comm_flow_symbol.noa',idfile)
##created new function for node attributes
identifier_matching.parseNodeAttrFileFromStringToGeneName(open(output_file+'_node_type.noa','r'),output_file+'_node_type_symbol.noa',idfile,True)
identifier_matching.parseNodeAttrFileFromStringToGeneName(open(output_file+'_node_flow.noa','r'),output_file+'_node_flow_symbol.noa',idfile,False)
if len(de_file)>0:
identifier_matching.parseNodeAttrFileFromStringToGeneName(open(output_file+'_DiffExpr.noa','r'),output_file+'_DiffExpr.noa',idfile,False)
return total,node_flow,comm_flow,phens,prots,tfs,mrnas
def process_output(output_file,source='S', sink='T', idfname='',debug=False,de_file=None,mcf=False):
'''
Run the standard post-processing steps for responseNet
'''
if not os.path.exists(output_file+'.txt'):
print 'Output file missing'
return 0.0,dict(),dict(),set(),set(),set(),set()
##Calculate node flow for ranking of signaling proteins
(node_flow,comm_flow,total)=calculate_node_flow(open(output_file+'.txt','r').readlines(),mcf)#returns a dictionary of node flow
#calculate enrichment statistic if mRNA are used?
#visualize
if total==0.0:
print 'No flow'
return total,node_flow,comm_flow,set(),set(),set(),set()
phens,prots,tfs,mrnas=write_sif_file(output_file, source, sink,node_flow,comm_flow,debug,de_file,mcf)
##MODIFIED by SGOSLINE: added this to do identifer matching for the sif files
if(idfname==''):
print 'No identifier matching, moving on...'
else:
print idfname
idfile=pickle.load(open(idfname,'r'))
if idfname!='':
print "Matching identifiers with "+idfname
identifier_matching.parseSifFileFromStringToGeneName(open(output_file+'_all.sif','r'),output_file+'_all_symbol.sif',idfile)
identifier_matching.parseSifFileFromStringToGeneName(open(output_file+'_mcfs.sif','r'),output_file+'_mcfs_symbol.sif',idfile)
identifier_matching.parseSifFileFromStringToGeneName(open(output_file+'_no_mrna.sif','r'),output_file+'_no_mrna_symbol.sif',idfile)
#also for the edge attribute files
identifier_matching.parseAttrFileFromStringToGeneName(open(output_file+'_ppi_attributes.eda','r'),output_file+'_ppi_attributes_symbol.eda',idfile)
identifier_matching.parseAttrFileFromStringToGeneName(open(output_file+'_edge_commodity.eda','r'),output_file+'_edge_commodity_symbol.eda',idfile)
identifier_matching.parseAttrFileFromStringToGeneName(open(output_file+'_edge_type.eda','r'),output_file+'_edge_type_symbol.eda',idfile)
identifier_matching.parseTabFileFromStringToGeneName(open(output_file+'_node_comm_flow.noa','r'),output_file+'_node_comm_flow_symbol.noa',idfile)
##created new function for node attributes
identifier_matching.parseNodeAttrFileFromStringToGeneName(open(output_file+'_node_type.noa','r'),output_file+'_node_type_symbol.noa',idfile,True)
identifier_matching.parseNodeAttrFileFromStringToGeneName(open(output_file+'_node_flow.noa','r'),output_file+'_node_flow_symbol.noa',idfile,False)
if len(de_file)>0:
identifier_matching.parseNodeAttrFileFromStringToGeneName(open(output_file+'_DiffExpr.noa','r'),output_file+'_DiffExpr.noa',idfile,False)
return total,node_flow,comm_flow,phens,prots,tfs,mrnas
def process_output(output_file,
source='S',
sink='T',
idfname='',
debug=False,
de_file=None,
mcf=False):
'''
Run the standard post-processing steps for responseNet
'''
if not os.path.exists(output_file + '.txt'):
print 'Output file missing'
return 0.0, dict(), dict(), set(), set(), set(), set()
##Calculate node flow for ranking of signaling proteins
(node_flow, comm_flow, total) = calculate_node_flow(
open(output_file + '.txt', 'r').readlines(),
mcf) #returns a dictionary of node flow
#calculate enrichment statistic if mRNA are used?
#visualize
if total == 0.0:
print 'No flow'
return total, node_flow, comm_flow, set(), set(), set(), set()
phens, prots, tfs, mrnas = write_sif_file(output_file, source, sink,
node_flow, comm_flow, debug,
de_file, mcf)
##MODIFIED by SGOSLINE: added this to do identifer matching for the sif files
if (idfname == ''):
print 'No identifier matching, moving on...'
else:
print idfname
idfile = pickle.load(open(idfname, 'r'))
if idfname != '':
print "Matching identifiers with " + idfname
identifier_matching.parseSifFileFromStringToGeneName(
open(output_file + '_all.sif', 'r'),
output_file + '_all_symbol.sif', idfile)
identifier_matching.parseSifFileFromStringToGeneName(
open(output_file + '_mcfs.sif', 'r'),
output_file + '_mcfs_symbol.sif', idfile)
identifier_matching.parseSifFileFromStringToGeneName(
open(output_file + '_no_mrna.sif', 'r'),
output_file + '_no_mrna_symbol.sif', idfile)
#also for the edge attribute files
identifier_matching.parseAttrFileFromStringToGeneName(
open(output_file + '_ppi_attributes.eda', 'r'),
output_file + '_ppi_attributes_symbol.eda', idfile)
identifier_matching.parseAttrFileFromStringToGeneName(
open(output_file + '_edge_commodity.eda', 'r'),
output_file + '_edge_commodity_symbol.eda', idfile)
identifier_matching.parseAttrFileFromStringToGeneName(
open(output_file + '_edge_type.eda', 'r'),
output_file + '_edge_type_symbol.eda', idfile)
identifier_matching.parseTabFileFromStringToGeneName(
open(output_file + '_node_comm_flow.noa', 'r'),
output_file + '_node_comm_flow_symbol.noa', idfile)
##created new function for node attributes
identifier_matching.parseNodeAttrFileFromStringToGeneName(
open(output_file + '_node_type.noa', 'r'),
output_file + '_node_type_symbol.noa', idfile, True)
identifier_matching.parseNodeAttrFileFromStringToGeneName(
open(output_file + '_node_flow.noa', 'r'),
output_file + '_node_flow_symbol.noa', idfile, False)
if len(de_file) > 0:
identifier_matching.parseNodeAttrFileFromStringToGeneName(
open(output_file + '_DiffExpr.noa', 'r'),
output_file + '_DiffExpr.noa', idfile, False)
return total, node_flow, comm_flow, phens, prots, tfs, mrnas