def _stream2SSfile(self, RefSNPdict):
"""
Makes simple SNP file for analysis by SNPhylo tree maker
**
- SNPhylo is case-sensitive
- Also requires single genotype mutation, represent single alleles different from the ref only
### BASIC FORMAT:
#chrNum position Ref SampleID1 ...
1 1000 A A T
"""
F = open(self.outputPath, 'w')
F.write('#Chrom\tPos\tRef\tSampleID1\n')
for chr in self.chrList:
positions = RefSNPdict[chr].keys()
positions.sort()
for pos in positions:
refGenotype = RefSNPdict[chr][pos][GENOTYPE].upper()
if pos in self.genome[chr]:
if len(self.genome[chr][refPos][GENOTYPE]) > 1:
if refGenotype.lower() == self.genome[chr][refPos][GENOTYPE][0].lower():
sample = self.genome[chr][refPos][GENOTYPE][1]
else:
sample = self.genome[chr][refPos][GENOTYPE][0]
else:
sample = self.genome[chr][refPos][GENOTYPE]
F.write('%s\t%s\t%s\t%s\n' % (chr, pos, refGenotype, sample))
F.close()
parseNstream.printMsg("Completed streaming to Simple SNP file format (path=%s)" % self.outputPath)
def _stream2SRSIDfile(self):
"""
Streams input data containing SNP rsid's to an output (filename) file
containing just the RSID values in each line.
"""
F = open(self.outputPath, 'w')
for chr in self.genome:
for pos in self.genome[chr]:
F.write('%s\n' % self.genome[chr][pos][RSID])
F.close()
parseNstream.printMsg("Completed streaming to simple RSID file format (path=%s)" % self.outputPath)
def __init__(self, chrom=""):
if chrom == "":
printMsg("Enter chromosome (1, 2, ..., or 23 (X), 24 (Y), 25 (MT))")
chrom = raw_input('---> ')
self.num = int(chrom)
self.chrLengths = [248956422, 242193529, 198295559, 190214555, 181538259, \
170805979, 159345973, 145138636, 138394717, 133797422, 135086622, \
133275309, 114364328, 107043718, 101991189, 90338345, 83257441, \
80373285, 58617616, 64444167, 46709983, 50818468, 156040895, 57227415, 16569]
self.positions = []
self.minSNP = 0
self.maxSNP = 0
def addUserScoredData_toDB(file, userObjID='', streamStatus=''):
"""
Adds every single SNP inside the _scoredAllelesObject to the DB.
_scoredAllelesObject queries the DB and outputs a dictionary containing all
SNPs that don't already exist in the DB
file: a file output from scoreAlleles().
userObjID: a user id from the users_collection.users
"_id": {
"$oid": "555a83687a349b6910bdff6c"
}
"""
COUNT = 0
k = 0
if userObjID == '':
userObjID = raw_input('Please enter a user ID: ')
assert(userObjID != '')
# Date/time stamp for start of run
parseNstream.printMsg(datetime.datetime.now().ctime())
newNumSNPs = 0
if os.path.exists(file):
# Implement assertion for file type, ensure all column headers are accurate
ScoredSNPdict = parseNstream._scoredAllelesObject(file, userObjID)
alreadyinDB = {}
alreadyinDB['total'] = 0
alreadyinDB['ids'] = []
signal = 0
for chr in parseNstream.CHROMOSOME_LIST:
alreadyinDB[chr] = 0
collect_signals = []
if any(chr == x for x in ['1', '2', '3', '4', '5']):
signal += 1
collection = db_model.CollectbyChromosome_1to5
elif any(chr == x for x in ['6', '7', '8', '9', '10', '11']):
signal += 1
collection = db_model.CollectbyChromosome_6to11
elif any(chr == x for x in ['12', '13', '14', '15', '16', '17']):
signal += 1
collection = db_model.CollectbyChromosome_12to17
elif any(chr == x for x in ['18', '19', '20', '21', '22', '23', '24', '25']):
signal += 1
collection = db_model.CollectbyChromosome_18to25
collect_signals.append(str(signal))
positions = ScoredSNPdict[chr].keys()
positions.sort()
# Iterates through each chromosomal position adding new RSIDS to DB in ascending order
for position in positions:
# if not UsersSNPCollection.find({'_id': rsid}).count():
data = ScoredSNPdict[chr][position]
if newNumSNPs == 0:
parseNstream.printMsg("Sample data object:")
print data
# Insert into DB
if streamStatus == 'empty':
collection.insert(data)
newNumSNPs += 1
if streamStatus != 'empty':
if not collection.find({'_id': data[RSID]}).count():
collection.insert(data)
newNumSNPs += 1
else:
alreadyinDB['total'] += 1
alreadyinDB[chr] += 1
alreadyinDB['ids'] += [data[RSID]]
if newNumSNPs == db_model.CHECKLIST[k]:
print "[x] Check %s-th complete. %s SNPs parsed so far. %s new SNPs added in total. %s parsed SNPs were already in the DB." % (k+1, db_model.CHECKLIST[k], newNumSNPs, COUNT-newNumSNPs)
k += 1
if collect_signals == ['1', '2', '3', '4', '5']:
parseNstream.printMsg("Interval 1 complete: (1-5)")
elif collect_signals == ['6', '7', '8', '9', '10', '11']:
parseNstream.printMsg("Interval 1 complete: (6-11)")
elif collect_signals == ['12', '13', '14', '15', '16', '17']:
parseNstream.printMsg("Interval 1 complete: (12-17)")
else:
if collect_signals == ['18', '19', '20', '21', '22', '23', '24', '25']:
parseNstream.printMsg("Interval 1 complete: (18-25)")
for chr in alreadyinDB:
print alreadyinDB[chr]
print "[x] Last check complete. %s total SNPs added to the UsersSNPCollection." % (db_model.CHECKLIST[k])
# Date/time stamp for end of run
parseNstream.printMsg(datetime.datetime.now().ctime())
print alreadyinDB['ids']
parseNstream.printMsg('SNPS ALREADY IN DB: %s' % alreadyinDB['total'])
for chr in alreadyinDB:
print alreadyinDB[chr]
else:
print "Path <%s> not found" % file
... etc.
"""
# Make dict of all SNP positions. Keys = Chromosome #, Values = lst of positions
for chrom in ChromosomeDict:
ChromosomePositions[chrom] = ChromosomeDict[chrom].keys()
ChromosomePositions[chrom].sort() # Could go without
Chromosomes[chrom] = Chromosome(chrom=chrom)
Chromosomes[chrom].positions = ChromosomePositions[chrom]
ChromosomePositions[chrom] = np.array(ChromosomePositions[chrom],dtype=np.float64)
# Output min and max values
for chrom in ChromosomePositions:
Chromosomes[chrom].minSNP = ChromosomePositions[chrom].min()
Chromosomes[chrom].maxSNP = ChromosomePositions[chrom].max()
printMsg("Chr%s: lowest chromosome position, highest chromosome position = (%s, %s)" % (chrom, Chromosomes[chrom].minSNP, Chromosomes[chrom].maxSNP))
ChromosomeSizes = []
for chrom in Chromosomes:
ChromosomeSizes.append(Chromosomes[chrom].size())
print Chromosomes[chrom].size()
ChromosomeSizes.sort()
ChromosomeSizes.reverse()
ChromosomeSizes = np.array(ChromosomeSizes)
largest_size = ChromosomeSizes.max()
smallest_size = ChromosomeSizes.min()
largest_chrom = ""
smallest_chrom = ""
printMsg("Chromosomes By Size")
index = 1
def concatenateSNPs(RefSNPFile, UserSNPFile):
"""
Structure of RefSNPdict and UserSNPdict:
key = chromosome string as '1', '2', ..., '23' (X), '24' (Y), '25', (MT/M)
(*) Reference allele is only ONE letter.
- Genotype is a string of len=2, the original allele representations from the 23andme file
- Variant(s) represents any letters different from the Reference, if none then given '-'
- Match Score (0,1,2): the SNP is given a score of ...
- 2 (homozygous) if both letters are the same as the Reference
- 1 (heterozygous) if one letter is the same as the Reference
- 0 (recessive) if neither match the reference
(*) Variants given a match score of 0 may need to be switched to the
opposite letters (A to T, C to G and vice versa); must check to
confirm which are minus vs. plus strands)
### BASIC FORMAT:
#chrNum position Ref Genotype Variant Matches(0,1,2)
1 1000 A AA -
RETURNS: none, streams to file...
"""
RefSNPdict = parseNstream._referenceObject(RefSNPFile, 'CHROMOSOME')
UserSNPdict = parseNstream._23andmeObject(UserSNPFile, 'CHROMOSOME')
nonMatchedRSIDs = []
numMatchedRSIDs = 0
snpsConcatenated = 0
indel = {}
F = open(DEFAULT_OUTPUT_FILEPATH, 'w')
for chr in parseNstream.CHROMOSOME_LIST:
positions = RefSNPdict[chr].keys()
positions.sort()
indel[chr] = {}
for pos in positions:
refAllele = RefSNPdict[chr][pos][GENOTYPE].upper()
rsid = RefSNPdict[chr][pos][RSID]
# Check allele cases for ref in the user's snps
if pos in UserSNPdict[chr]:
if rsid != UserSNPdict[chr][pos][RSID]:
nonMatchedRSIDs += [(rsid, UserSNPdict[chr][pos][RSID])]
if isIndel(UserSNPdict[chr][pos][GENOTYPE]):
indel[chr][pos] = {
RSID: UserSNPdict[chr][pos][RSID],
GENOTYPE: UserSNPdict[chr][pos][GENOTYPE]
}
else:
numMatchedRSIDs += 1
sampleAllele = UserSNPdict[chr][pos][GENOTYPE] # 3
# Chromosomes 1-22 will have an allele pair, hence str len of 2
if len(sampleAllele) == 2:
if sampleAllele[0] == '-' and sampleAllele[1] == '-':
variant = '-'
score = '-'
elif sampleAllele[0].lower() == refAllele.lower() and sampleAllele[1].lower() == refAllele.lower():
variant = '-'
score = 2
elif sampleAllele[0].lower() == refAllele.lower():
variant = sampleAllele[1]
score = 1
elif sampleAllele[1].lower() == refAllele.lower():
variant = sampleAllele[0]
score = 1
else:
variant = sampleAllele
score = 0
# Mitochondria, X, and Y chromosome alleles are of length 1
elif len(sampleAllele) == 1:
if sampleAllele == '-':
variant = '-'
score = '-'
elif sampleAllele.lower() == refAllele.lower():
variant = '-'
score = 1
else:
variant = sampleAllele
score = 0
if score != '-':
snpsConcatenated += 1
if variant == '-':
F.write('%s' % sampleAllele[0])
else:
F.write('%s' % variant)
F.close()
parseNstream.printMsg("Completed scoring user SNPs to REF SNPs. Streamed to a .FASTA file (path=%s)" % DEFAULT_OUTPUT_FILEPATH)
parseNstream.printMsg('Number of matched rsid values: %s' % numMatchedRSIDs)
print "Only the RSID's of the user that existed in the reference data base were used. Also, INDELs were not concatenated."
parseNstream.printMsg('Number of unmatched rsid values: %s' % len(nonMatchedRSIDs))
parseNstream.printMsg('Number of SNPs concatenated: %s' % snpsConcatenated)
def scoreAlleles(RefSNPFile, UserSNPFile):
"""
Structure of RefSNPdict and UserSNPdict:
key = chromosome string as '1', '2', ..., '23' (X), '24' (Y), '25', (MT/M)
(*) Reference allele is only ONE letter.
- Genotype is a string of len=2, the original allele representations from the 23andme file
- Variant(s) represents any letters different from the Reference, if none then given '-'
- Match Score (0,1,2): the SNP is given a score of ...
- 2 (homozygous) if both letters are the same as the Reference
- 1 (heterozygous) if one letter is the same as the Reference
- 0 (recessive) if neither match the reference
(*) Variants given a match score of 0 may need to be switched to the
opposite letters (A to T, C to G and vice versa); must check to
confirm which are minus vs. plus strands)
### BASIC FORMAT:
#chrNum position Ref Genotype Variant Matches(0,1,2)
1 1000 A AA -
RETURNS: none, streams to file...
"""
RefSNPdict = parseNstream._referenceObject(RefSNPFile, 'CHROMOSOME')
UserSNPdict = parseNstream._23andmeObject(UserSNPFile, 'CHROMOSOME')
# Keep track of RSIDs in the that do not match in position and rsid value in tuples (ref rsid, user rsid)
nonMatchedRSIDs = []
# Count number of RSIDs whose positions in a chr match for both ref and user, and report it at the end.
numMatchedRSIDs = 0
# Keep track of indels
indel = {}
F = open(DEFAULT_OUTPUT_FILEPATH, 'w')
F.write('#Chrom\tRSID\tPos\tRef\tGenotype\tVariant(s)\tMatch Score\n')
for chr in parseNstream.CHROMOSOME_LIST:
positions = RefSNPdict[chr].keys()
positions.sort()
indel[chr] = {}
for pos in positions:
refAllele = RefSNPdict[chr][pos][GENOTYPE].upper()
rsid = RefSNPdict[chr][pos][RSID]
# Check allele cases for ref in the user's snps
if pos in UserSNPdict[chr]:
if rsid != UserSNPdict[chr][pos][RSID]:
nonMatchedRSIDs += [(rsid, UserSNPdict[chr][pos][RSID])]
if isIndel(UserSNPdict[chr][pos][GENOTYPE]):
indel[chr][pos] = {
RSID: UserSNPdict[chr][pos][RSID],
GENOTYPE: UserSNPdict[chr][pos][GENOTYPE]
}
else:
numMatchedRSIDs += 1
sampleAllele = UserSNPdict[chr][pos][GENOTYPE] # 3
# Chromosomes 1-22 will have an allele pair, hence str len of 2
if len(sampleAllele) == 2:
# No base call at the current rsid. [BLANK]
if sampleAllele[0] == '-' and sampleAllele[1] == '-':
variant = '-'
score = '-'
# Score 2, no variants. Both letters are homologous to the reference. [GRAY - default]
elif sampleAllele[0].lower() == refAllele.lower() and sampleAllele[1].lower() == refAllele.lower():
variant = '-'
score = 2
# Score 1, one variant. Second letter is homologous to the reference. [GREEN - success]
elif sampleAllele[0].lower() == refAllele.lower():
variant = sampleAllele[1]
score = 1
# Score 1, one variant. First letter is homologous to the reference. [GREEN - success]
elif sampleAllele[1].lower() == refAllele.lower():
variant = sampleAllele[0]
score = 1
# Score 0, two variants. No homology to the reference. [ORANGE - primary]
else:
variant = sampleAllele
score = 0
# Mitochondria, X, and Y chromosome alleles are of length 1
elif len(sampleAllele) == 1:
# No base call at the current rsid. [BLANK]
if sampleAllele == '-':
variant = '-'
score = '-'
# Score 1, no variants. Only letter is homologous to the reference. [GRAY - default]
elif sampleAllele.lower() == refAllele.lower():
variant = '-'
score = 1
else:
variant = sampleAllele
score = 0
F.write('%s\t%s\t%s\t%s\t%s\t%s\t%s\n' % (chr, rsid, pos, refAllele, sampleAllele, variant, score))
F.close()
parseNstream.printMsg("Completed scoring user SNPs to REF SNPs. Streamed to a .teyden (LOL) file format (path=%s)" % DEFAULT_OUTPUT_FILEPATH)
parseNstream.printMsg('Number of matched rsid values: %s' % numMatchedRSIDs)
parseNstream.printMsg('Number of unmatched rsid values: %s' % len(nonMatchedRSIDs))
return indel
