def main():
if len(sys.argv)==1:
print ('ERROR: No options provided.\n')
parser.print_help(sys.stderr)
sys.exit(1)
parameters = parser.parse_args()
p_dict= vars(parameters)
if p_dict['debug']:
print ('Parsed parameters:')
print(p_dict)
action = p_dict['ldpred_action']
if action=='coord':
coord_genotypes.main(p_dict)
elif action=='gibbs':
LDpred_gibbs.main(p_dict)
elif action=='inf':
LDpred_inf.main(p_dict)
elif action=='p+t':
LD_pruning_thres.main(p_dict)
elif action=='score':
validate.main(p_dict)
elif action=='ldfile':
ld.get_ld_dict(p_dict['cf'], p_dict['ldf'], p_dict['ldr'],wallaceld=True)
elif action=='all':
pass
def main(p_dict):
#Check parameters
summary_dict = {}
summary_dict[0]={'name':'Coordinated data filename','value':p_dict['cf']}
summary_dict[0.1]={'name':'SNP weights output file (prefix)', 'value':p_dict['out']}
summary_dict[0.2]={'name':'LD data filename (prefix)', 'value':p_dict['ldf']}
summary_dict[1]={'name':'LD radius used','value':str(p_dict['ldr'])}
t0 = time.time()
summary_dict[1.09]={'name':'dash', 'value':'LD information'}
ld_dict = ld.get_ld_dict(p_dict['cf'], p_dict['ldf'], p_dict['ldr'], verbose=p_dict['debug'],
compressed=not p_dict['no_ld_compression'], use_hickle=p_dict['hickle_ld'], summary_dict=summary_dict)
t1 = time.time()
t = (t1 - t0)
summary_dict[1.2]={'name':'Running time for calculating LD information:','value':'%d min and %0.2f secs'% (t / 60, t % 60)}
t0 = time.time()
summary_dict[1.9]={'name':'dash', 'value':'LDpred Gibbs sampler'}
ldpred_genomewide(data_file=p_dict['cf'], out_file_prefix=p_dict['out'], ps=p_dict['f'], ld_radius=p_dict['ldr'],
ld_dict=ld_dict, n=p_dict['N'], num_iter=p_dict['n_iter'], burn_in=p_dict['n_burn_in'],
h2=p_dict['h2'], use_gw_h2=p_dict['use_gw_h2'], verbose=p_dict['debug'], summary_dict=summary_dict)
t1 = time.time()
t = (t1 - t0)
summary_dict[2.2]={'name':'Running time for Gibbs sampler(s):','value':'%d min and %0.2f secs'% (t / 60, t % 60)}
reporting.print_summary(summary_dict, 'Summary of LDpred Gibbs')
def main(p_dict):
ld_dict = ld.get_ld_dict(p_dict['cf'], p_dict['ldf'], p_dict['ldr'])
ldpred_inf_genomewide(data_file=p_dict['cf'],
out_file_prefix=p_dict['out'],
ld_radius=p_dict['ldr'],
ld_dict=ld_dict,
n=p_dict['N'],
h2=p_dict['h2'],
verbose=p_dict['debug'])
def main(p_dict):
ld_dict = ld.get_ld_dict(p_dict['cf'],
p_dict['ldf'],
p_dict['ldr'],
verbose=p_dict['debug'],
compressed=not p_dict['no_ld_compression'],
use_hickle=p_dict['hickle_ld'],
summary_dict={})
ldpred_inf_genomewide(data_file=p_dict['cf'],
out_file_prefix=p_dict['out'],
ld_radius=p_dict['ldr'],
ld_dict=ld_dict,
n=p_dict['N'],
h2=p_dict['h2'],
verbose=p_dict['debug'])
def main(p_dict):
# need change to fix chr by chr.
ld_dict = ld.get_ld_dict(p_dict['cf'], p_dict['ldf'], p_dict['ldr'])
# ldpred_genomewide(data_file=p_dict['cf'], out_file_prefix=p_dict['out'], ps=p_dict['f'], ld_radius=p_dict['ldr'],
# ld_dict=ld_dict, n=p_dict['N'], num_iter=p_dict['n_iter'], burn_in=p_dict['n_burn_in'],
# h2=p_dict['h2'], verbose=p_dict['debug'])
ldpred_genomewide(data_file=p_dict['cf'],
out_file_prefix=p_dict['out'],
ps=p_dict['f'],
ld_radius=p_dict['ldr'],
ld_dict=ld_dict,
n=p_dict['N'],
num_iter=p_dict['n_iter'],
burn_in=p_dict['n_burn_in'],
h2=p_dict['h2'],
verbose=p_dict['debug'],
local_ld_file_prefix=p_dict['ldf'],
scipyInverse=p_dict['scipy'])
def main(p_dict):
summary_dict = {}
summary_dict[0]={'name':'Coordinated data filename','value':p_dict['cf']}
summary_dict[0.1]={'name':'SNP weights output file (prefix)', 'value':p_dict['out']}
summary_dict[0.2]={'name':'LD data filename (prefix)', 'value':p_dict['ldf']}
summary_dict[1]={'name':'LD radius used','value':str(p_dict['ldr'])}
t0 = time.time()
summary_dict[1.09]={'name':'dash', 'value':'LD information'}
ld_dict = ld.get_ld_dict(p_dict['cf'], p_dict['ldf'], p_dict['ldr'], verbose=p_dict['debug'],
compressed=not p_dict['no_ld_compression'], use_hickle=p_dict['hickle_ld'], summary_dict=summary_dict)
t1 = time.time()
t = (t1 - t0)
summary_dict[1.2]={'name':'Running time for calculating LD information:','value':'%d min and %0.2f secs'% (t / 60, t % 60)}
t0 = time.time()
summary_dict[1.9]={'name':'dash', 'value':'LDpred Gibbs sampler'}
ldpred_genomewide(data_file=p_dict['cf'], out_file_prefix=p_dict['out'], ps=p_dict['f'], ld_radius=p_dict['ldr'],
ld_dict=ld_dict, n=p_dict['N'], num_iter=p_dict['n_iter'], burn_in=p_dict['n_burn_in'],
h2=p_dict['h2'], verbose=p_dict['debug'], summary_dict=summary_dict)
t1 = time.time()
t = (t1 - t0)
summary_dict[2.2]={'name':'Running time for Gibbs sampler(s):','value':'%d min and %0.2f secs'% (t / 60, t % 60)}
reporting.print_summary(summary_dict, 'Summary of LDpred Gibbs')
def main(p_dict):
ld_dict = ld.get_ld_dict(p_dict['cf'], p_dict['ldf'], p_dict['ldr'], verbose=p_dict['debug'],
compressed=not p_dict['no_ld_compression'], use_hickle=p_dict['hickle_ld'], summary_dict={})
ldpred_inf_genomewide(data_file=p_dict['cf'], out_file_prefix=p_dict['out'], ld_radius=p_dict['ldr'],
ld_dict = ld_dict, n=p_dict['N'], h2=p_dict['h2'], verbose=p_dict['debug'])