print report

file = open(report)

lines = file.readlines()

file.close()

#header = "SNP Name,Sample ID,Allele1 - Top,Allele2 - Top,GC Score,Allele1 - Plus,Allele2 - Plus,Chr,Position,SNP,Theta,R,X,Y,X Raw,Y Raw,B Allele Freq"

#header = "SNP Name,Sample ID,Allele1 - Top,Allele2 - Top,GC Score,Allele1 - Forward,Allele2 - Forward,Allele1 - Plus,Allele2 - Plus,Chr,Position,GT Score,Cluster Sep,SNP,X,Y,X Raw,Y Raw,B Allele,Freq,Log R Ratio,CNV Value,CNV Confidence"

#h = header.split(',')

#h = ['SNP Name', 'Sample ID', 'Allele1 - Top', 'Allele2 - Top', 'GC Score', 'Allele1 - Forward', 'Allele2 - Forward', 'Allele1 - Plus', 'Allele2 - Plus', 'Chr', 'Position', 'GT Score', 'Cluster Sep', 'SNP', 'X', 'Y', 'X Raw', 'Y Raw', 'B Allele Freq', 'Log R Ratio', 'CNV Value', 'CNV Confidence', 'Top Genomic Sequence', 'Plus/Minus Strand', 'Theta', 'R\r\n']

h = 'SNP Name\tSample ID\tAllele1 - Top\tAllele2 - Top\tGC Score\tSNP Index\tAllele1 - Forward\tAllele2 - Forward\tAllele1 - AB\tAllele2 - AB\tAllele1 - Plus\tAllele2 - Plus\tChr\tPosition\tSNP\tILMN Strand\tTop Genomic Sequence\tPlus/Minus Strand\tTheta\tR\tX\tY\tX Raw\tY Raw\tB Allele Freq\r\n'.split('\t')

snpi = h.index("SNP")

chri = h.index("Chr")

posi = h.index("Position")

Yi = h.index("Y")

Xi = h.index("X")

snplist = []

ref = {}

alt = {}

freq = {}

for l in lines:

t = l.split('\t')

try:

if t[chri] not in map(lambda x: str(x), range(1,23)):

continue

else:

snppos = 'chr'+t[chri]+'pos'+t[posi]

snplist.append(snppos)

ref[snppos] = t[snpi].split('/')[0][1]

alt[snppos] = t[snpi].split('/')[1][0]

freq[snppos] = float(t[Yi])/(float(t[Yi])+float(t[Xi]))

except:

continue

glob.dump(snplist, report+'snps')

glob.dump(ref, report+'RefT')

glob.dump(alt, report+'AltT')

def __init__(self, name, ext = "Geno"):

self.name = name

self.genofile = open('./' + name + ext)

self.__genolen__()

def __genolen__(self):

l = self.genofile.readline()

self.ln = len(l.split(','))

lines = filestruc.genofile.readlines()

snppos = map(lambda x: x.split('\t')[0], lines[1:])

inboth = set(snppos) & set(chosenSNPs)

notingeno = set(filter(lambda x: x not in inboth, chosenSNPs))

try:

genos['lines'] = genos['lines'] +lines[0].split('\t')[1].split(',')

except KeyError:

genos['lines'] = lines[0].split('\t')[1].split(',')

print("Number of Lines in Genotype:" + str(len(lines)))

for l in lines[1:]:

t = l.split('\t')

snp = t[0]

if snp in inboth:

try:

genos[snp] = genos[snp].strip(',') + ','+t[1].strip('\n')

except KeyError:

genos[snp] = t[1].strip('\n')

if incarray == 0:

for s in notingeno:

try:

genos[s] = genos[s].strip(',') + ','+('0,' * filestruc.ln)

except KeyError:

genos[s] = '0,' * filestruc.ln

glob.dump(genos, 'tempgenos')

genos = {}

if type(names) is str:

f = Genotypes(names)

genos = getsnpgenos(genos, f, chosenSNPs, incarray)

if type(names) is list:

files = map(lambda x: Genotypes(x), names)

genos = reduce(lambda x,y: getsnpgenos(x, y, chosenSNPs, incarray), [genos]+files)

glob.dump(genos, out+'.json')

genos['lines'] = map(lambda x: x.strip('\n'), genos['lines'])

output = open(out, 'w')

linenames = reduce(lambda x,y: x +',' + y, genos['lines'])

output.write('\t' + linenames +'\n')

for g in genos.keys():

if g != 'lines':

"""the combine genos stuff is predicated on the idea that if a SNP isn't mentioned

it's genotype is 0

in reality, if the snps are genotypes as part of different projects (like 1KG vs. HapMap)

then if a SNP is not present it may be because it was never tested

This functions finds the intersecting set of snps between two genotype files, which can then be

used as part of the "chosen SNPs" to select the ultimate final combined Genos file

"""

snplist = map(lambda x: getsnps(x), genotypes)

print len(snplist)

ineverything = reduce(lambda x,y: set(x) & set(y), snplist)

f = open(genotypefile)

lines = f.readlines()

print len(lines)

f.close()

snppos = map(lambda x: x.split('\t')[0], lines[1:])

"""the purpose of this function is to do a simple genotype file combine, based on select snps, the

assumption is that the files are from two different categories of genotyping projects, so the snps

used are an output of the interset() function

"""

snps = interset(genotypes)

combinedgenos = {}

combinedgenos['lines'] = []

for g in genotypes:

lines = open(g).readlines()

combinedgenos['lines'].append(lines[0].split('\t')[1])

for l in lines[1:]:

t = l.split('\t')

snp = t[0]

if snp in snps:

try:

combinedgenos[snp] = combinedgenos[snp].strip(',') + ','+t[1].strip('\n')

except KeyError:

combinedgenos[snp] = t[1].strip('\n')

output = open(out, 'w')

combinedgenos['lines'] = map(lambda x: x.strip('\n'), combinedgenos['lines'])

linenames = reduce(lambda x,y: x +',' + y, combinedgenos['lines'])

output.write('\t' +linenames + '\n')

for g in combinedgenos.keys():

if g != 'lines':

print "parsing hapmap genotypes chrom files"

parsegenotypes.parsehapmap()

print "now filtering SNPs"

b = parsegenotypes.filterSNPs('../genotypes/hapmap')

print "{0} SNPs filtered out".format(len(b))

[flips, errors] = parsegenotypes.checkRef('../genotypes/hapmap')

print "{0} flips and {1} errors".format(len(flips),len(errors))

#flips = glob.json('../genotypes/hapmapflips')

#errors = glob.json('../genotypes/hapmaperrors')

"""parse genotype files and flip them around according to hg19

"""

for i, n in enumerate(homedirnames):

parsegenotypes.parse1KGvcf(vcffiles[i], names1KG[i])

b = parsegenotypes.filterSNPs(names1KG[i])

print "{0} SNPs filtered out".format(len(b))

c = parsegenotypes.checkRef(n)

print "{0} errors and {1} flipped".format(len(c[1]),len(c[0]))

#parsegenotypes.corrRef(c[0], n)

output = open(out, 'w')

pool = glob.json(pool)

g = open(genofile)

lines = g.readlines()

g.close()

linenames = lines[0]

ln = linenames.split('\t')[1].split(',')

ln = map(lambda x: x.strip('\n'), ln)

print pool

poolinds = map(lambda x: ln.index(x), pool)

nl = [ln[i] for i in poolinds]

newlinenames = ','

newlinenames = reduce(lambda x,y: x + ',' + y, nl)

output.write(newlinenames + '\n')

for l in lines[1:]:

t = l.split('\t')

gs = t[1].split(',')

gs = map(lambda x: x.strip('\n'), gs)

if len(filter(lambda x: int(x)!=0, gs)) >0:

newl = t[0] + ','

newg = []

for i in range(0, len(gs)):

if i in poolinds:

newg.append(gs[i])

newg = reduce(lambda x,y: x + ',' + y, newg)

newl = newl + newg + '\n'

def __init__(self, name):

self.name = name

def makedic(self):

afile = open(self.name+'Rinput')

alines = afile.readlines()

afile.close()

self.dic = {}

for l in alines[1:]:

self.dic[l.split('\t')[0]] = float(l.split('\t')[1].strip('\n'))

pfile = open(poolgenotypefile)

plines = pfile.readlines()

pfile.close()

uarray = Array(uniformarray)

uarray.makedic()

uarraysnps = set(uarray.snps)

arrayobj = map(lambda x: Array(x), arrays)

map(lambda x: x.makedic(), arrayobj)

allarrays = [uarray]

allarrays.extend(arrayobj)

snpsincommon = reduce(lambda x,y: set(x.snps) & set(y.snps), allarrays)

print len(snpsincommon)

output = open(Goutput,'w')

output.write(plines[0])

for g in plines[1:]:

if g.split(',')[0] in snpsincommon:

output.write(g)

output = open(uniformarray+".Uarray.poolRinput", 'w')

for g in plines[1:]:

snp = g.split(',')[0]

if snp in snpsincommon:

output.write(snp +',' + str(uarray.dic[snp]) + '\n')

for a in arrayobj:

a.makedic()

output = open(a.name+'.poolRinput', 'w')

for g in plines[1:]:

snp = g.split(',')[0]

if snp in snpsincommon:

#try:

output.write(snp + ',' + str(a.dic[snp]) + '\n')

#except KeyError:

opts, args = getopt.getopt(argv,"a:ghc:i",["report=", "genonames="])

for opt, arg in opts:

if opt == '-a':

report = arg

print "processing array, getting snps {0}".format(report)

getarraysnps(arg)

[f, e] = parsegenotypes.checkRef(report)

parsegenotypes.flipArray(report, f)

parsegenotypes.filterzeros(report)

parsegenotypes.printtabarray(report)

elif opt == '-g':

processgenotypes()

elif opt == '-h':

processhapmap()

elif opt == '-c':

snps = glob.json('Array251Msnps')

if arg == '':

genofiles = names1KG

else:

genofiles = arg

combinegenos(genofiles, snps)

elif opt == "-i":