def pickle_csv(csvfile, pickle_fname=None):
tree_file = csv.reader(open(csvfile, 'rb'))
if pickle_fname is None:
pickle_fname = csvfile + '.pickle'
aplo_list = io_modules.csv.parse_csv(tree_file)
htree = tree.HaplogroupTree(aplo_list=aplo_list)
pickle_file = open(pickle_fname, 'wb')
pickle_file.write(htree.serialize())
def data_parsing(file_file, site_file, bestres_file, haptab_file):
#apro i file di input
#diff = open(diff_file, 'r')
file = open(file_file, 'r')
site = open(site_file, 'r')
bestres = open(bestres_file, 'r')
haptab = open(haptab_file, 'r')
print "Parsing pathogenicity table..."
#dizionario del tabellone pato
# scarto la prima riga (intestazione)
file = file.readlines()[1:]
d = {}
d = fillPathoDict2(file, d, '\t', 2)
print "Parsing variability data..."
#dizionario sitevar
# scarto la prima riga (intestazione)
site = site.readlines()[1:]
g = {}
g = fillSiteVarDict(site, g, '\t', 1)
for pos in g.keys():
# convert variability values (nt and aa, if available) in floats
try:
g[pos][1] = float(g[pos][1])
except:
pass
try:
g[pos][4] = float(g[pos][4])
except:
pass
print "Parsing info about haplogroup-defining sites..."
haplo = {}
htree = tree.HaplogroupTree(
pickle_data=open(data_file +
'/data/phylotree_r17.pickle', 'rb').read())
for haplogroup in htree._aplo_dict.keys():
haplo[haplogroup] = []
# change Transition and Transversion datatypes to SNP_MixIn,
# because Transition and Transversion variants parsed from merged_diff are that type
for event in htree.get_filtered_positions(haplogroup):
if event.mutation_type() in ['Transition', 'Transversion']:
event_new = SNP_MixIn()
event_new.start = event.start
event_new.change = event.change
haplo[haplogroup].append(event_new)
else:
haplo[haplogroup].append(event)
# la funzione di cui sopra sostituisce la procedura qui sotto
#haplo = [line.strip().split('\t') for line in haptab] #lista di liste aplogruppo/variante
# DS .. convert strings of variants (eg '146T') in datatypes.SNP (eg Transition(146))
#for i in haplo[1:]:
# i[1] = pprint2datatype(i[1])
#print haplo[:4]
#hapconto = hapcon.read() #file letto interamente che usero' per contare quante volte e' presente una variante
haplo_sites = []
for haplogroup in haplo.keys():
haplo_sites.extend(haplo[haplogroup])
hapconto = Counter(haplo_sites)
#hapcon = open(haptab_file, 'r')
#hapcont = [line.strip().split('\t') for line in hapcon]
#hapconto = []
#for l in hapcont:
# for e in l:
# hapconto.append(e)
#print hapconto.keys()[:10]
#print "7146A is found %d times in hapconto" % (hapconto.count('7146A'))
print "Parsing info about haplogroup assignments..."
#dizionario best results
# scarto la prima riga (intestazione)
bestres = bestres.readlines()[1:]
best = {}
best = fillDict(bestres, best, ',', 1)
#for s in best.keys():
# best[s] = [best[s][0].split(';')[0]]
#print best
return d, g, haplo, hapconto, best
sys.exit()
elif o == "-i": contig_file = a
elif o == "-m": muscle_exe = a
elif o == "-b": basename = a
elif o == "-s": best_results_file = a
else:
assert False, "Unhandled option."
print "Your best results file is ", best_results_file
# sample name
f = os.path.abspath(contig_file)
#sample_name = f.split('/')[-2].split('_')[-1]
sample_name = contig_file.split('-')[0]
# haplogroup tree parsing
htrees = [(tree.HaplogroupTree(pickle_data=open(data_file + '/phylotree_r15.pickle', 'rb').read()), data_file + '/data/phylotree_r15.pickle')]
# mhcs parsing
mhcs_dict = parse_mhcs.parse2mhcs_dict(data_file + '/data/mhcs.tab')
print "\nLoading contig sequences from file %s" % contig_file
contig_array = load_sequences(contig_file)
contig_array_seqdiff = [] # lista di liste
contig_total_seqdiff = [] # lista di varianti
contig_array_mappings = []
print "\nAligning Contigs to mtDNA reference genome...\n"
# update each contig's SeqDiff
for x,contig in enumerate(contig_array):
if x == 0:
contig_seq_diff = align_sequence(muscle_exe, contig)
def write_old_table(pickle_fname, out_fname):
htree = tree.HaplogroupTree(pickle_data=open(pickle_fname, 'rb').read())
fh = csv.writer(open(out_fname, 'wb'))
for haplo_name in htree:
io_modules.old_table.write_haplogroup(fh, '', htree[haplo_name])
from bioinf.seqs import SeqList
import io_modules.csv
import io_modules.old_table
import io_modules.serialize
import pandas as pd
import os.path
sys.setrecursionlimit(100000)
csvfile, out_fname = sys.argv[1:]
#write pickle file for MToolBox
tree_file = csv.reader(open(csvfile, 'rb'))
pickle_fname = csvfile + '.pickle'
aplo_list = io_modules.csv.parse_csv(tree_file)
htree = tree.HaplogroupTree(aplo_list=aplo_list)
pickle_file = open(pickle_fname, 'wb')
pickle_file.write(htree.serialize())
pickle_file.close()
#write out alleles and haplogroups defined for HmtDB in csv file
pickle_file = pickle_fname
out_file = out_fname + '.csv'
htree = tree.HaplogroupTree(pickle_data=open(pickle_file, 'rb').read())
fh = csv.writer(open(out_file, 'wb'))
for haplo_name in htree:
io_modules.old_table.write_haplogroup(fh, '', htree[haplo_name])
#write haplogrups.txt tab delimited file for MToolBox
out_file2 = out_fname + '.txt'
hap_file = pd.read_csv(out_file, sep=',', header=None)
