reffile = name +'Ref'

altfile = name + 'Alt'

[ref, alt] = map(lambda x: glob.json(x, ''), [reffile, altfile])

print "Loaded Ref {0}, Alt {1}".format(len(ref),len(alt))

keys = ref.keys()

complsnps = []

for snppos in keys:

if glob.compl[ref[snppos].upper()] == alt[snppos].upper() or ref[snppos].upper() == alt[snppos].upper():

complsnps.append(snppos)

del ref[snppos]

del alt[snppos]

print len(ref)

print len(alt)

glob.dump(ref, reffile+'T')

glob.dump(alt, altfile+'T')

reffile = name +'RefT'

altfile = name + 'AltT'

hg19 = worldbase.Bio.Seq.Genome.HUMAN.hg19(download = True)

print "Loaded hg19"

ref = glob.json(reffile)

print "Loaded Ref"

alt = glob.json(altfile)

print "Loaded Alt"

flip = []

errors = []

keys = ref.keys()

for snppos in keys:

print snppos + '\t' + name

t = snppos.split('pos')

hg19snp = str(hg19[t[0]][int(t[1])-1]).upper()

refsnp = ref[snppos].upper()

altsnp = alt[snppos].upper()

if hg19snp == refsnp:

continue

elif hg19snp == altsnp:

flip.append(snppos)

else:

print "Error: Neither Ref nor Alt of SNP corresponds to hg19 sequence"

errors.append(snppos)

glob.dump(flip, name+'flips')

glob.dump(errors, name+'errors')

reffile = name +'RefT'

altfile = name + 'AltT'

for snp in flip:

t = ref[snp]

ref[snp] = alt[snp]

alt[snp] = t

glob.dump(ref, reffile+'flipped')

"""flip genotypes based on new ref and alt,

the new genotype allele frequencies are

flipped 0->2, 2->0 based on list of snp positions

inputed as flip list

"""

file = open(genofile)

lines = file.readlines()

newgeno = open(genofile+'flippedfast', 'w')

newgeno.write(lines[0])

#newlines = []

i=0

flipset = set(flip)

for l in lines[1:]:

t = l.split('\t')

i+=1

print i

if t[0] in flipset:

newg = map(lambda x: 2-int(x), t[1].strip('\n').strip(',').split(','))

newl = t[0] +'\t'

newl = reduce(lambda x,y: x+str(y) + ',', [newl]+newg)

newgeno.write(newl.strip(',') + '\n')

#newlines.append(newl)

elif t[0] not in errors:

#newlines.append(l)

newgeno.write(l.strip('\n').strip(',') + '\n')

#for l in newlines:

"""flip array snp frequencies (hash)

1-freq for those in snp list inputed as flip

input is constructed in the original getarraysnps() function

"""

try:

arrayfreq = glob.json(arrayname+'freq')

except:

"No array snp frequency file"

for snp in flip:

arrayfreq[snp] = 1 - arrayfreq[snp]

for snp in error:

del arrayfreq[snp]

"""take out those that are 0

"""

freq = glob.json(arrayname+'freq')

for snp in freq.keys():

if freq[snp] == 0 or math.isnan(freq[snp]):

del freq[snp]

"""output will be analyzed by R to find cell line frequencies

"""

output = open(arrayname+'Rinput', 'w')

freq = glob.json(arrayname+'freq')

for snp in freq.keys():

output.write(snp + '\t')

file = open(vcffile)

outputfile = open(outputname+'Geno', 'w')

ref = {}

alt = {}

lines = file.readlines(1000000)

while(lines != []):

for l in lines:

if l.startswith('#CHROM'):

g = reduce(lambda x,y: x+','+y, l.strip('\n').split('\t')[9:])

outputfile.write('\t'+str(g) +'\n')

if not l.startswith('#'):

tokens = l.strip('\n').split('\t')

f = filter(lambda x: 'GP' in x, tokens[7].split(';'))

if f != []:

pos = 'chr'+f[0].split('=')[1].split(':')[0]+'pos'+f[0].split('=')[1].split(':')[1]

ref[pos] = tokens[3]

alt[pos] = tokens[4]

m=pos +'\t'

for t in tokens[9:]:

m = m + str(int(t[0]) + int(t[2])) + ','

outputfile.write(m.strip(',')+'\n')

lines = file.readlines(1000000)

glob.dump(ref, outputname+'Ref')

import parsehapmapgenotypes

ref = {}

alt = {}

genotype = open('hapmapGeno','w')

for c in range(1,23):

"here"

[r,a] = parsehapmapgenotypes.parsehapmapchrom(c)

ref.update(r)

alt.update(a)

with open('../genotypes/hapmapchr'+str(c)+'genotype') as g:

lines = g.readlines()

map(lambda l: genotype.write(l), lines)

genotype.close()

glob.dump(ref, '../genotypes/hapmapRef')

reffile = '../genotypes/CEUlowcovRef'

altfile = '../genotypes/CEUlowcovAlt'

ref = simplejson.load(open(reffile))

print "loaded ref"

alt = simplejson.load(open(altfile))

print "all loaded"

keys = ref.keys()

for snppos in keys: