def add_pop_to_smartpca(smartpca_inbase,smartpca_outbase,db_name='FULL',prefix='RB'):
td = get_table_as_dict(db_name,suppress_fc_check=True)
pop_lookup = dict([(prefix+d['id'],d['location']) for d in td])
infile = smartpca_inbase+'.ind'
outfile = smartpca_outbase+'.ind'
outfh = open(outfile,'w')
for l in open(infile):
ind = l.strip().split()[0]
newl = '\t'.join(l.split()[:2]+[pop_lookup[ind]+'\n'])
outfh.write(newl)
outfh.close()
open(smartpca_outbase+'.par','w').write('genotypename:\t%s.ancestrymapgeno\n' \
'snpname:\t%s.snp\n' \
'indivname:\t%s.ind\n' \
'evecoutname:\t%s.evec\n' \
'evaloutname:\t%s.eval\n' \
'snpweightoutname:\t%s.snpweightout\n'
'phylipoutname:\t%s.fst\n' % tuple([smartpca_outbase]*7))
ret = os.system('cp %s %s' % (smartpca_inbase+'.ancestrymapgeno',smartpca_outbase+'.ancestrymapgeno'))
if ret != 0:
raise OSError
ret = os.system('cp %s %s' % (smartpca_inbase+'.snp',smartpca_outbase+'.snp'))
if ret != 0:
raise OSError
def wigs_phenotypes_from_DB(db_name,indiv_lists,survive_field='recap1',survive_value='R'):
'''indiv_lists is tuple of lists, one list per pop, of individual ids
'''
td = get_table_as_dict(db_name,suppress_fc_check=True)
phenos = []
for pop_n,indivs in enumerate(indiv_lists):
phenos.append([])
for ind_n,indiv in enumerate(indivs):
phenos[-1].append([int(d[survive_field] == survive_value) for d in td if d['id'] == indiv][0])
return phenos
def indiv_lists_by_enc(vcf_obj,db_name,query_d,prefix='RB',sort_key=None):
'''
see write_wigs_all_simple for example of query_d
'''
td = get_table_as_dict(db_name,suppress_fc_check=True)
vcf_indivs = indivs_in_vcf(vcf_obj)
if 'site' in query_d.keys():
sites = query_d['site']
indiv_lists = tuple([[d['id'] for d in td if d['site'] == this_site and prefix+d['id'] in vcf_indivs and all([d[k] in v for k,v in query_d.items() if k != 'site'])] for this_site in sites])
else:
indiv_lists = tuple([[d['id'] for d in td if prefix+d['id'] in vcf_indivs and all([d[k] in v for k,v in query_d.items()])]])
if sort_key is not None:
indiv_lists = [sorted(l,key=sort_key) for l in indiv_lists]
return indiv_lists
#!/usr/bin/env python
import os,sys
import run_safe
from rtd import preprocess_radtag_lane,overlap_preprocess
#import rtd.overlap_preprocess
recs = preprocess_radtag_lane.get_table_as_dict('DB_adapt_trim_seqs',suppress_fc_check=True)
print >> sys.stderr, recs
#def get_adaptseq(table='DB_adapt_trim_seqs'):
# return dict([(d['adapterstype'],{'r1':d['r1'],'r2':d['r2']}) for d in preprocess_radtag_lane.get_table_as_dict(table,suppress_fc_check=True)])
def get_adaptseq(table='DB_adapt_trim_seqs'):
return dict([(d['adapterstype'],{'r1':d['r1'],'r2':d['r2']}) for d in recs ])
adaptseq = get_adaptseq()
#print >> sys.stderr, 'use adapterstype: %s\nadaptA: %s\nadaptB: %s' % (adapterstype,adaptA,adaptB)
print >> sys.stderr, adaptseq
