def run_in_out_acc_np(in_residues, dssp, g, folder):
dssp.parseDSSP(
'C:\\uday\\gmu\\correlations\\results\\10proteins\\acc\\NP_2IQH.dssp')
residue_acc = dssp.getAllResAccForChain('A', delta=0)
sav_in_network = []
sav_out_network = []
num_edges = []
for key, value in residue_acc.items():
if key in in_residues['np']:
sav_in_network.append(int(value))
num_edges.append(len(get_edges_from_graph(g, 'np', key)))
else:
sav_out_network.append(int(value))
plot_util.plot_in_edges_acc(num_edges, sav_in_network, folder, 'np')
ttest_result = stats.ttest_ind(sav_in_network,
sav_out_network,
equal_var=False)
print('ttest for np ', ttest_result)
if len(sav_in_network) > 0:
avg_in_network = sum(sav_in_network) / len(sav_in_network)
else:
avg_in_network = 0.0
avg_out_network = sum(sav_out_network) / len(sav_out_network)
return avg_in_network, avg_out_network
def run_in_out_acc_ha(in_residues, dssp, g, folder):
dssp.parseDSSP(
'C:\\uday\\gmu\\correlations\\results\\10proteins\\acc\\HA_1RU7.dssp')
residue_acc_a = dssp.getAllResAccForChain('A', delta=13)
residue_acc_b = dssp.getAllResAccForChain('B', delta=-157)
residue_acc = {}
residue_acc.update(residue_acc_a)
residue_acc.update(residue_acc_b)
sav_in_network = []
sav_out_network = []
num_edges = []
for key, value in residue_acc.items():
if key in in_residues['ha']:
sav_in_network.append(int(value))
num_edges.append(len(get_edges_from_graph(g, 'ha', key)))
else:
sav_out_network.append(int(value))
plot_util.plot_in_edges_acc(num_edges, sav_in_network, folder, 'ha')
ttest_result = stats.ttest_ind(sav_in_network,
sav_out_network,
equal_var=False)
print('ttest for ha ', ttest_result)
avg_in_network = sum(sav_in_network) / len(sav_in_network)
avg_out_network = sum(sav_out_network) / len(sav_out_network)
return avg_in_network, avg_out_network
def run_in_out_acc_ha(in_residues, dssp, g, folder):
dssp.parseDSSP('HA_1RU7.dssp')
residue_acc_a = dssp.getAllResAccForChain('A', delta=13)
residue_acc_b = dssp.getAllResAccForChain('B', delta=-157)
residue_acc = {}
residue_acc.update(residue_acc_a)
residue_acc.update(residue_acc_b)
sav_in_network=[]
sav_out_network=[]
num_edges = []
for key, value in residue_acc.items():
if key in in_residues['ha']:
sav_in_network.append(int(value))
num_edges.append(len(get_edges_from_graph(g, 'ha', key)))
else:
sav_out_network.append(int(value))
plot_util.plot_in_edges_acc(num_edges, sav_in_network, folder, 'ha')
ttest_result = stats.ttest_ind(sav_in_network, sav_out_network, equal_var=False)
print('ttest for ha ', ttest_result)
print('average in-network ACC for HA ', sum(sav_in_network)/len(sav_in_network))
print('average out-network ACC for HA ', sum(sav_out_network)/len(sav_out_network))
def run_in_out_acc_np(in_residues, dssp, g, folder):
dssp.parseDSSP('C:\\uday\\gmu\\correlations\\results\\10proteins\\acc\\NP_2IQH.dssp')
residue_acc = dssp.getAllResAccForChain('A', delta=0)
sav_in_network=[]
sav_out_network=[]
num_edges = []
for key, value in residue_acc.items():
if key in in_residues['np']:
sav_in_network.append(int(value))
num_edges.append(len(get_edges_from_graph(g, 'np', key)))
else:
sav_out_network.append(int(value))
plot_util.plot_in_edges_acc(num_edges, sav_in_network, folder, 'np')
ttest_result = stats.ttest_ind(sav_in_network, sav_out_network, equal_var=False)
print('ttest for np ', ttest_result)
if len(sav_in_network) > 0:
avg_in_network = sum(sav_in_network) / len(sav_in_network)
else:
avg_in_network = 0.0
avg_out_network = sum(sav_out_network) / len(sav_out_network)
return avg_in_network, avg_out_network
def run_in_out_acc_ha(in_residues, dssp, g, folder):
dssp.parseDSSP('C:\\uday\\gmu\\correlations\\results\\10proteins\\acc\\HA_1RU7.dssp')
residue_acc_a = dssp.getAllResAccForChain('A', delta=13)
residue_acc_b = dssp.getAllResAccForChain('B', delta=-157)
residue_acc = {}
residue_acc.update(residue_acc_a)
residue_acc.update(residue_acc_b)
sav_in_network=[]
sav_out_network=[]
num_edges = []
for key, value in residue_acc.items():
if key in in_residues['ha']:
sav_in_network.append(int(value))
num_edges.append(len(get_edges_from_graph(g, 'ha', key)))
else:
sav_out_network.append(int(value))
plot_util.plot_in_edges_acc(num_edges, sav_in_network, folder, 'ha')
ttest_result = stats.ttest_ind(sav_in_network, sav_out_network, equal_var=False)
print('ttest for ha ', ttest_result)
avg_in_network = sum(sav_in_network)/len(sav_in_network)
avg_out_network = sum(sav_out_network)/len(sav_out_network)
return avg_in_network, avg_out_network
def run_in_out_acc_ns1(in_residues, dssp, g, folder):
dssp.parseDSSP('NS1_2GX9.dssp')
residue_acc = dssp.getAllResAccForChain('A', delta=0)
sav_in_network=[]
sav_out_network=[]
num_edges = []
for key, value in residue_acc.items():
if key in in_residues['ns1']:
sav_in_network.append(int(value))
num_edges.append(len(get_edges_from_graph(g, 'ns1', key)))
else:
sav_out_network.append(int(value))
plot_util.plot_in_edges_acc(num_edges, sav_in_network, folder, 'ns1')
ttest_result = stats.ttest_ind(sav_in_network, sav_out_network, equal_var=False)
print('ttest for ns1 ', ttest_result)
print('average in-network ACC for NS1 ', sum(sav_in_network)/len(sav_in_network))
print('average out-network ACC for NS1 ', sum(sav_out_network)/len(sav_out_network))
