treetime/vcf_utils.py
def read_vcf(vcf_file, ref_file):
    """
    Reads in a vcf/vcf.gz file and associated
    reference sequence fasta (to which the VCF file is mapped).

    Parses mutations, insertions, and deletions and stores them in a nested dict,
    see 'returns' for the dict structure.

    Calls with heterozygous values 0/1, 0/2, etc and no-calls (./.) are
    replaced with Ns at the associated sites.

    Positions are stored to correspond the location in the reference sequence
    in Python (numbering is transformed to start at 0)

    Parameters
    ----------
    vcf_file : string
        Path to the vcf or vcf.gz file to be read in
    ref_file : string
        Path to the fasta reference file to be read in

    Returns
    --------
    compress_seq : nested dict
        In the format: ::

            {
            'reference':'AGCTCGA..A',
            'sequences': { 'seq1':{4:'A', 7:'-'}, 'seq2':{100:'C'} },
            'insertions': { 'seq1':{4:'ATT'}, 'seq3':{1:'TT', 10:'CAG'} },
            'positions': [1,4,7,10,100...]
            }

        references : string
            String of the reference sequence read from the Fasta, to which
            the variable sites are mapped
        sequences : nested dict
            Dict containing sequence names as keys which map to dicts
            that have position as key and the single-base mutation (or deletion)
            as values
        insertions : nested dict
            Dict in the same format as the above, which stores insertions and their
            locations. The first base of the insertion is the same as whatever is
            currently in that position (Ref if no mutation, mutation in 'sequences'
            otherwise), so the current base can be directly replaced by the bases held here.
        positions : list
            Python list of all positions with a mutation, insertion, or deletion.

    """

    #Programming Note:
    # Note on VCF Format
    # -------------------
    # 'Insertion where there are also deletions' (special handling)
    #     Ex:
    #       REF     ALT         Seq1    Seq2
    #       GC      GCC,G       1/1     2/2
    #     Insertions formatted differently - don't know how many bp match
    #     the Ref (unlike simple insert below). Could be mutations, also.
    # 'Deletion'
    #     Ex:
    #       REF     ALT
    #       GC      G
    #     Alt does not have to be 1 bp - any length shorter than Ref.
    # 'Insertion'
    #     Ex:
    #       REF     ALT
    #       A       ATT
    #     First base always matches Ref.
    # 'No indel'
    #     Ex:
    #       REF     ALT
    #       A       G

    #define here, so that all sub-functions can access them
    sequences = defaultdict(dict)
    insertions = defaultdict(dict) #Currently not used, but kept in case of future use.

    #TreeTime handles 2-3 base ambig codes, this will allow that.
    def getAmbigCode(bp1, bp2, bp3=""):
        bps = [bp1,bp2,bp3]
        bps.sort()
        key = "".join(bps)

        return {
            'CT': 'Y',
            'AG': 'R',
            'AT': 'W',
            'CG': 'S',
            'GT': 'K',
            'AC': 'M',
            'AGT': 'D',
            'ACG': 'V',
            'ACT': 'H',
            'CGT': 'B'
        }[key]

    #Parses a 'normal' (not hetero or no-call) call depending if insertion+deletion, insertion,
    #deletion, or single bp subsitution
    def parseCall(snps, ins, pos, ref, alt):

        #Insertion where there are also deletions (special handling)
        if len(ref) > 1 and len(alt)>len(ref):
            for i in range(len(ref)):
                #if the pos doesn't match, store in sequences
                if ref[i] != alt[i]:
                    snps[pos+i] = alt[i] if alt[i] != '.' else 'N' #'.' = no-call
                #if about to run out of ref, store rest:
                if (i+1) >= len(ref):
                    ins[pos+i] = alt[i:]
        #Deletion
        elif len(ref) > 1:
            for i in range(len(ref)):
                #if ref is longer than alt, these are deletion positions
                if i+1 > len(alt):
                    snps[pos+i] = '-'
                #if not, there may be mutations
                else:
                    if ref[i] != alt[i]:
                        snps[pos+i] = alt[i] if alt[i] != '.' else 'N' #'.' = no-call
        #Insertion
        elif len(alt) > 1:
            ins[pos] = alt
        #No indel
        else:
            snps[pos] = alt


    #Parses a 'bad' (hetero or no-call) call depending on what it is
    def parseBadCall(snps, ins, pos, ref, ALT):
        #Deletion
        #   REF     ALT     Seq1    Seq2    Seq3
        #   GCC     G       1/1     0/1     ./.
        # Seq1 (processed by parseCall, above) will become 'G--'
        # Seq2 will become 'GNN'
        # Seq3 will become 'GNN'
        if len(ref) > 1:
            #Deleted part becomes Ns
            if gen[0] == '0' or gen[0] == '.':
                if gen[0] == '0':   #if het, get first bp
                    alt = str(ALT[int(gen[2])-1])
                else: #if no-call, there is no alt, so just put Ns after 1st ref base
                    alt = ref[0]
                for i in range(len(ref)):
                    #if ref is longer than alt, these are deletion positions
                    if i+1 > len(alt):
                        snps[pos+i] = 'N'
                    #if not, there may be mutations
                    else:
                        if ref[i] != alt[i]:
                            snps[pos+i] = alt[i] if alt[i] != '.' else 'N' #'.' = no-call

        #If not deletion, need to know call type
        #if het, see if proposed alt is 1bp mutation
        elif gen[0] == '0':
            alt = str(ALT[int(gen[2])-1])
            if len(alt)==1:
                #alt = getAmbigCode(ref,alt) #if want to allow ambig
                alt = 'N' #if you want to disregard ambig
                snps[pos] = alt
            #else a het-call insertion, so ignore.

        #else it's a no-call; see if all alts have a length of 1
        #(meaning a simple 1bp mutation)
        elif len(ALT)==len("".join(ALT)):
            alt = 'N'
            snps[pos] = alt
        #else a no-call insertion, so ignore.


    #House code is *much* faster than pyvcf because we don't care about all info
    #about coverage, quality, counts, etc, which pyvcf goes to effort to parse
    #(and it's not easy as there's no standard ordering). Custom code can completely
    #ignore all of this.
    import gzip
    from Bio import SeqIO
    import numpy as np

    nsamp = 0
    posLoc = 0
    refLoc = 0
    altLoc = 0
    sampLoc = 9

    #Use different openers depending on whether compressed
    opn = gzip.open if vcf_file.endswith(('.gz', '.GZ')) else open

    with opn(vcf_file, mode='rt') as f:
        for line in f:
            if line[0] != '#':
                #actual data - most common so first in 'if-list'!
                line = line.strip()
                dat = line.split('\t')
                POS = int(dat[posLoc])
                REF = dat[refLoc]
                ALT = dat[altLoc].split(',')
                calls = np.array(dat[sampLoc:])

                #get samples that differ from Ref at this site
                recCalls = {}
                for sname, sa in zip(samps, calls):
                    if ':' in sa: #if proper VCF file (followed by quality/coverage info)
                        gt = sa.split(':')[0]
                    else: #if 'pseudo' VCF file (nextstrain output, or otherwise stripped)
                        gt = sa
                    if gt == '0' or gt == '1': #for haploid calls in VCF
                        gt = '0/0' if gt == '0' else '1/1'

                    #ignore if ref call: '.' or '0/0', depending on VCF
                    if ('/' in gt and gt != '0/0') or ('|' in gt and gt != '0|0'):
                        recCalls[sname] = gt

                #store the position and the alt
                for seq, gen in recCalls.items():
                    ref = REF
                    pos = POS-1     #VCF numbering starts from 1, but Reference seq numbering
                                    #will be from 0 because it's python!
                    #Accepts only calls that are 1/1, 2/2 etc. Rejects hets and no-calls
                    if gen[0] != '0' and gen[2] != '0' and gen[0] != '.' and gen[2] != '.':
                        alt = str(ALT[int(gen[0])-1])   #get the index of the alternate
                        if seq not in sequences.keys():
                            sequences[seq] = {}

                        parseCall(sequences[seq],insertions[seq], pos, ref, alt)

                    #If is heterozygote call (0/1) or no call (./.)
                    else:
                        #alt will differ here depending on het or no-call, must pass original
                        parseBadCall(sequences[seq],insertions[seq], pos, ref, ALT)

            elif line[0] == '#' and line[1] == 'C':
                #header line, get all the information
                header = line.strip().split('\t')
                posLoc = header.index("POS")
                refLoc = header.index('REF')
                altLoc = header.index('ALT')
                sampLoc = header.index('FORMAT')+1
                samps = header[sampLoc:]
                samps = [ x.strip() for x in samps ] #ensure no leading/trailing spaces
                nsamp = len(samps)

            #else you are a comment line, ignore.

    #Gather all variable positions
    positions = set()
    for seq, muts in sequences.items():
        positions.update(muts.keys())

    #One or more seqs are same as ref! (No non-ref calls) So haven't been 'seen' yet
    if nsamp > len(sequences):
        missings = set(samps).difference(sequences.keys())
        for s in missings:
            sequences[s] = {}

    refSeq = SeqIO.read(ref_file, format='fasta')
    refSeq = refSeq.upper() #convert to uppercase to avoid unknown chars later
    refSeqStr = str(refSeq.seq)

    compress_seq = {'reference':refSeqStr,
                    'sequences': sequences,
                    'insertions': insertions,
                    'positions': sorted(positions)}

    return compress_seq
def read_vcf(vcf_file, ref_file):
    """
    Reads in a vcf/vcf.gz file and associated
    reference sequence fasta (to which the VCF file is mapped).

    Parses mutations, insertions, and deletions and stores them in a nested dict,
    see 'returns' for the dict structure.

    Calls with heterozygous values 0/1, 0/2, etc and no-calls (./.) are
    replaced with Ns at the associated sites.

    Positions are stored to correspond the location in the reference sequence
    in Python (numbering is transformed to start at 0)

    Parameters
    ----------
    vcf_file : string
        Path to the vcf or vcf.gz file to be read in
    ref_file : string
        Path to the fasta reference file to be read in

    Returns
    --------
    compress_seq : nested dict
        In the format: ::

            {
            'reference':'AGCTCGA..A',
            'sequences': { 'seq1':{4:'A', 7:'-'}, 'seq2':{100:'C'} },
            'insertions': { 'seq1':{4:'ATT'}, 'seq3':{1:'TT', 10:'CAG'} },
            'positions': [1,4,7,10,100...]
            }

        references : string
            String of the reference sequence read from the Fasta, to which
            the variable sites are mapped
        sequences : nested dict
            Dict containing sequence names as keys which map to dicts
            that have position as key and the single-base mutation (or deletion)
            as values
        insertions : nested dict
            Dict in the same format as the above, which stores insertions and their
            locations. The first base of the insertion is the same as whatever is
            currently in that position (Ref if no mutation, mutation in 'sequences'
            otherwise), so the current base can be directly replaced by the bases held here.
        positions : list
            Python list of all positions with a mutation, insertion, or deletion.

    """

    #Programming Note:
    # Note on VCF Format
    # -------------------
    # 'Insertion where there are also deletions' (special handling)
    #     Ex:
    #       REF     ALT         Seq1    Seq2
    #       GC      GCC,G       1/1     2/2
    #     Insertions formatted differently - don't know how many bp match
    #     the Ref (unlike simple insert below). Could be mutations, also.
    # 'Deletion'
    #     Ex:
    #       REF     ALT
    #       GC      G
    #     Alt does not have to be 1 bp - any length shorter than Ref.
    # 'Insertion'
    #     Ex:
    #       REF     ALT
    #       A       ATT
    #     First base always matches Ref.
    # 'No indel'
    #     Ex:
    #       REF     ALT
    #       A       G

    #define here, so that all sub-functions can access them
    sequences = defaultdict(dict)
    insertions = defaultdict(dict) #Currently not used, but kept in case of future use.

    #TreeTime handles 2-3 base ambig codes, this will allow that.
    def getAmbigCode(bp1, bp2, bp3=""):
        bps = [bp1,bp2,bp3]
        bps.sort()
        key = "".join(bps)

        return {
            'CT': 'Y',
            'AG': 'R',
            'AT': 'W',
            'CG': 'S',
            'GT': 'K',
            'AC': 'M',
            'AGT': 'D',
            'ACG': 'V',
            'ACT': 'H',
            'CGT': 'B'
        }[key]

    #Parses a 'normal' (not hetero or no-call) call depending if insertion+deletion, insertion,
    #deletion, or single bp subsitution
    def parseCall(snps, ins, pos, ref, alt):

        #Insertion where there are also deletions (special handling)
        if len(ref) > 1 and len(alt)>len(ref):
            for i in range(len(ref)):
                #if the pos doesn't match, store in sequences
                if ref[i] != alt[i]:
                    snps[pos+i] = alt[i] if alt[i] != '.' else 'N' #'.' = no-call
                #if about to run out of ref, store rest:
                if (i+1) >= len(ref):
                    ins[pos+i] = alt[i:]
        #Deletion
        elif len(ref) > 1:
            for i in range(len(ref)):
                #if ref is longer than alt, these are deletion positions
                if i+1 > len(alt):
                    snps[pos+i] = '-'
                #if not, there may be mutations
                else:
                    if ref[i] != alt[i]:
                        snps[pos+i] = alt[i] if alt[i] != '.' else 'N' #'.' = no-call
        #Insertion
        elif len(alt) > 1:
            ins[pos] = alt
        #No indel
        else:
            snps[pos] = alt


    #Parses a 'bad' (hetero or no-call) call depending on what it is
    def parseBadCall(snps, ins, pos, ref, ALT):
        #Deletion
        #   REF     ALT     Seq1    Seq2    Seq3
        #   GCC     G       1/1     0/1     ./.
        # Seq1 (processed by parseCall, above) will become 'G--'
        # Seq2 will become 'GNN'
        # Seq3 will become 'GNN'
        if len(ref) > 1:
            #Deleted part becomes Ns
            if gen[0] == '0' or gen[0] == '.':
                if gen[0] == '0':   #if het, get first bp
                    alt = str(ALT[int(gen[2])-1])
                else: #if no-call, there is no alt, so just put Ns after 1st ref base
                    alt = ref[0]
                for i in range(len(ref)):
                    #if ref is longer than alt, these are deletion positions
                    if i+1 > len(alt):
                        snps[pos+i] = 'N'
                    #if not, there may be mutations
                    else:
                        if ref[i] != alt[i]:
                            snps[pos+i] = alt[i] if alt[i] != '.' else 'N' #'.' = no-call

        #If not deletion, need to know call type
        #if het, see if proposed alt is 1bp mutation
        elif gen[0] == '0':
            alt = str(ALT[int(gen[2])-1])
            if len(alt)==1:
                #alt = getAmbigCode(ref,alt) #if want to allow ambig
                alt = 'N' #if you want to disregard ambig
                snps[pos] = alt
            #else a het-call insertion, so ignore.

        #else it's a no-call; see if all alts have a length of 1
        #(meaning a simple 1bp mutation)
        elif len(ALT)==len("".join(ALT)):
            alt = 'N'
            snps[pos] = alt
        #else a no-call insertion, so ignore.


    #House code is *much* faster than pyvcf because we don't care about all info
    #about coverage, quality, counts, etc, which pyvcf goes to effort to parse
    #(and it's not easy as there's no standard ordering). Custom code can completely
    #ignore all of this.
    import gzip
    from Bio import SeqIO
    import numpy as np

    nsamp = 0
    posLoc = 0
    refLoc = 0
    altLoc = 0
    sampLoc = 9

    #Use different openers depending on whether compressed
    opn = gzip.open if vcf_file.endswith(('.gz', '.GZ')) else open

    with opn(vcf_file, mode='rt') as f:
        for line in f:
            if line[0] != '#':
                #actual data - most common so first in 'if-list'!
                line = line.strip()
                dat = line.split('\t')
                POS = int(dat[posLoc])
                REF = dat[refLoc]
                ALT = dat[altLoc].split(',')
                calls = np.array(dat[sampLoc:])

                #get samples that differ from Ref at this site
                recCalls = {}
                for sname, sa in zip(samps, calls):
                    if ':' in sa: #if proper VCF file (followed by quality/coverage info)
                        gt = sa.split(':')[0]
                    else: #if 'pseudo' VCF file (nextstrain output, or otherwise stripped)
                        gt = sa
                    if gt == '0' or gt == '1': #for haploid calls in VCF
                        gt = '0/0' if gt == '0' else '1/1'

                    #ignore if ref call: '.' or '0/0', depending on VCF
                    if ('/' in gt and gt != '0/0') or ('|' in gt and gt != '0|0'):
                        recCalls[sname] = gt

                #store the position and the alt
                for seq, gen in recCalls.items():
                    ref = REF
                    pos = POS-1     #VCF numbering starts from 1, but Reference seq numbering
                                    #will be from 0 because it's python!
                    #Accepts only calls that are 1/1, 2/2 etc. Rejects hets and no-calls
                    if gen[0] != '0' and gen[2] != '0' and gen[0] != '.' and gen[2] != '.':
                        alt = str(ALT[int(gen[0])-1])   #get the index of the alternate
                        if seq not in sequences.keys():
                            sequences[seq] = {}

                        parseCall(sequences[seq],insertions[seq], pos, ref, alt)

                    #If is heterozygote call (0/1) or no call (./.)
                    else:
                        #alt will differ here depending on het or no-call, must pass original
                        parseBadCall(sequences[seq],insertions[seq], pos, ref, ALT)

            elif line[0] == '#' and line[1] == 'C':
                #header line, get all the information
                header = line.strip().split('\t')
                posLoc = header.index("POS")
                refLoc = header.index('REF')
                altLoc = header.index('ALT')
                sampLoc = header.index('FORMAT')+1
                samps = header[sampLoc:]
                samps = [ x.strip() for x in samps ] #ensure no leading/trailing spaces
                nsamp = len(samps)

            #else you are a comment line, ignore.

    #Gather all variable positions
    positions = set()
    for seq, muts in sequences.items():
        positions.update(muts.keys())

    #One or more seqs are same as ref! (No non-ref calls) So haven't been 'seen' yet
    if nsamp > len(sequences):
        missings = set(samps).difference(sequences.keys())
        for s in missings:
            sequences[s] = {}

    refSeq = SeqIO.read(ref_file, format='fasta')
    refSeq = refSeq.upper() #convert to uppercase to avoid unknown chars later
    refSeqStr = str(refSeq.seq)

    compress_seq = {'reference':refSeqStr,
                    'sequences': sequences,
                    'insertions': insertions,
                    'positions': sorted(positions)}

    return compress_seq
def read_vcf ( vcf_file , ref_file ) : #Programming Note:
 # Note on VCF Format
 # -------------------
 # 'Insertion where there are also deletions' (special handling)
 #     Ex:
 #       REF     ALT         Seq1    Seq2
 #       GC      GCC,G       1/1     2/2
 #     Insertions formatted differently - don't know how many bp match
 #     the Ref (unlike simple insert below). Could be mutations, also.
 # 'Deletion'
 #     Ex:
 #       REF     ALT
 #       GC      G
 #     Alt does not have to be 1 bp - any length shorter than Ref.
 # 'Insertion'
 #     Ex:
 #       REF     ALT
 #       A       ATT
 #     First base always matches Ref.
 # 'No indel'
 #     Ex:
 #       REF     ALT
 #       A       G
 #define here, so that all sub-functions can access them
 sequences = defaultdict ( dict ) insertions = defaultdict ( dict ) #Currently not used, but kept in case of future use.
 #TreeTime handles 2-3 base ambig codes, this will allow that.
 def getAmbigCode ( bp1 , bp2 , bp3 = "" ) : bps = [ bp1 , bp2 , bp3 ] bps . sort ( ) key = "" . join ( bps ) return { 'CT' : 'Y' , 'AG' : 'R' , 'AT' : 'W' , 'CG' : 'S' , 'GT' : 'K' , 'AC' : 'M' , 'AGT' : 'D' , 'ACG' : 'V' , 'ACT' : 'H' , 'CGT' : 'B' } [ key ] #Parses a 'normal' (not hetero or no-call) call depending if insertion+deletion, insertion,
 #deletion, or single bp subsitution
 def parseCall ( snps , ins , pos , ref , alt ) : #Insertion where there are also deletions (special handling)
 if len ( ref ) > 1 and len ( alt ) > len ( ref ) : for i in range ( len ( ref ) ) : #if the pos doesn't match, store in sequences
 if ref [ i ] != alt [ i ] : snps [ pos + i ] = alt [ i ] if alt [ i ] != '.' else 'N' #'.' = no-call
 #if about to run out of ref, store rest:
 if ( i + 1 ) >= len ( ref ) : ins [ pos + i ] = alt [ i : ] #Deletion
 elif len ( ref ) > 1 : for i in range ( len ( ref ) ) : #if ref is longer than alt, these are deletion positions
 if i + 1 > len ( alt ) : snps [ pos + i ] = '-' #if not, there may be mutations
 else : if ref [ i ] != alt [ i ] : snps [ pos + i ] = alt [ i ] if alt [ i ] != '.' else 'N' #'.' = no-call
 #Insertion
 elif len ( alt ) > 1 : ins [ pos ] = alt #No indel
 else : snps [ pos ] = alt #Parses a 'bad' (hetero or no-call) call depending on what it is
 def parseBadCall ( snps , ins , pos , ref , ALT ) : #Deletion
 #   REF     ALT     Seq1    Seq2    Seq3
 #   GCC     G       1/1     0/1     ./.
 # Seq1 (processed by parseCall, above) will become 'G--'
 # Seq2 will become 'GNN'
 # Seq3 will become 'GNN'
 if len ( ref ) > 1 : #Deleted part becomes Ns
 if gen [ 0 ] == '0' or gen [ 0 ] == '.' : if gen [ 0 ] == '0' : #if het, get first bp
 alt = str ( ALT [ int ( gen [ 2 ] ) - 1 ] ) else : #if no-call, there is no alt, so just put Ns after 1st ref base
 alt = ref [ 0 ] for i in range ( len ( ref ) ) : #if ref is longer than alt, these are deletion positions
 if i + 1 > len ( alt ) : snps [ pos + i ] = 'N' #if not, there may be mutations
 else : if ref [ i ] != alt [ i ] : snps [ pos + i ] = alt [ i ] if alt [ i ] != '.' else 'N' #'.' = no-call
 #If not deletion, need to know call type
 #if het, see if proposed alt is 1bp mutation
 elif gen [ 0 ] == '0' : alt = str ( ALT [ int ( gen [ 2 ] ) - 1 ] ) if len ( alt ) == 1 : #alt = getAmbigCode(ref,alt) #if want to allow ambig
 alt = 'N' #if you want to disregard ambig
 snps [ pos ] = alt #else a het-call insertion, so ignore.
 #else it's a no-call; see if all alts have a length of 1
 #(meaning a simple 1bp mutation)
 elif len ( ALT ) == len ( "" . join ( ALT ) ) : alt = 'N' snps [ pos ] = alt #else a no-call insertion, so ignore.
 #House code is *much* faster than pyvcf because we don't care about all info
 #about coverage, quality, counts, etc, which pyvcf goes to effort to parse
 #(and it's not easy as there's no standard ordering). Custom code can completely
 #ignore all of this.
 import gzip from Bio import SeqIO import numpy as np nsamp = 0 posLoc = 0 refLoc = 0 altLoc = 0 sampLoc = 9 #Use different openers depending on whether compressed
 opn = gzip . open if vcf_file . endswith ( ( '.gz' , '.GZ' ) ) else open with opn ( vcf_file , mode = 'rt' ) as f : for line in f : if line [ 0 ] != '#' : #actual data - most common so first in 'if-list'!
 line = line . strip ( ) dat = line . split ( '\t' ) POS = int ( dat [ posLoc ] ) REF = dat [ refLoc ] ALT = dat [ altLoc ] . split ( ',' ) calls = np . array ( dat [ sampLoc : ] ) #get samples that differ from Ref at this site
 recCalls = { } for sname , sa in zip ( samps , calls ) : if ':' in sa : #if proper VCF file (followed by quality/coverage info)
 gt = sa . split ( ':' ) [ 0 ] else : #if 'pseudo' VCF file (nextstrain output, or otherwise stripped)
 gt = sa if gt == '0' or gt == '1' : #for haploid calls in VCF
 gt = '0/0' if gt == '0' else '1/1' #ignore if ref call: '.' or '0/0', depending on VCF
 if ( '/' in gt and gt != '0/0' ) or ( '|' in gt and gt != '0|0' ) : recCalls [ sname ] = gt #store the position and the alt
 for seq , gen in recCalls . items ( ) : ref = REF pos = POS - 1 #VCF numbering starts from 1, but Reference seq numbering
 #will be from 0 because it's python!
 #Accepts only calls that are 1/1, 2/2 etc. Rejects hets and no-calls
 if gen [ 0 ] != '0' and gen [ 2 ] != '0' and gen [ 0 ] != '.' and gen [ 2 ] != '.' : alt = str ( ALT [ int ( gen [ 0 ] ) - 1 ] ) #get the index of the alternate
 if seq not in sequences . keys ( ) : sequences [ seq ] = { } parseCall ( sequences [ seq ] , insertions [ seq ] , pos , ref , alt ) #If is heterozygote call (0/1) or no call (./.)
 else : #alt will differ here depending on het or no-call, must pass original
 parseBadCall ( sequences [ seq ] , insertions [ seq ] , pos , ref , ALT ) elif line [ 0 ] == '#' and line [ 1 ] == 'C' : #header line, get all the information
 header = line . strip ( ) . split ( '\t' ) posLoc = header . index ( "POS" ) refLoc = header . index ( 'REF' ) altLoc = header . index ( 'ALT' ) sampLoc = header . index ( 'FORMAT' ) + 1 samps = header [ sampLoc : ] samps = [ x . strip ( ) for x in samps ] #ensure no leading/trailing spaces
 nsamp = len ( samps ) #else you are a comment line, ignore.
 #Gather all variable positions
 positions = set ( ) for seq , muts in sequences . items ( ) : positions . update ( muts . keys ( ) ) #One or more seqs are same as ref! (No non-ref calls) So haven't been 'seen' yet
 if nsamp > len ( sequences ) : missings = set ( samps ) . difference ( sequences . keys ( ) ) for s in missings : sequences [ s ] = { } refSeq = SeqIO . read ( ref_file , format = 'fasta' ) refSeq = refSeq . upper ( ) #convert to uppercase to avoid unknown chars later
 refSeqStr = str ( refSeq . seq ) compress_seq = { 'reference' : refSeqStr , 'sequences' : sequences , 'insertions' : insertions , 'positions' : sorted ( positions ) } return compress_seq
Reads in a vcf/vcf.gz file and associated
    reference sequence fasta (to which the VCF file is mapped).

    Parses mutations, insertions, and deletions and stores them in a nested dict,
    see 'returns' for the dict structure.

    Calls with heterozygous values 0/1, 0/2, etc and no-calls (./.) are
    replaced with Ns at the associated sites.

    Positions are stored to correspond the location in the reference sequence
    in Python (numbering is transformed to start at 0)

    Parameters
    ----------
    vcf_file : string
        Path to the vcf or vcf.gz file to be read in
    ref_file : string
        Path to the fasta reference file to be read in

    Returns
    --------
    compress_seq : nested dict
        In the format: ::

            {
            'reference':'AGCTCGA..A',
            'sequences': { 'seq1':{4:'A', 7:'-'}, 'seq2':{100:'C'} },
            'insertions': { 'seq1':{4:'ATT'}, 'seq3':{1:'TT', 10:'CAG'} },
            'positions': [1,4,7,10,100...]
            }

        references : string
            String of the reference sequence read from the Fasta, to which
            the variable sites are mapped
        sequences : nested dict
            Dict containing sequence names as keys which map to dicts
            that have position as key and the single-base mutation (or deletion)
            as values
        insertions : nested dict
            Dict in the same format as the above, which stores insertions and their
            locations. The first base of the insertion is the same as whatever is
            currently in that position (Ref if no mutation, mutation in 'sequences'
            otherwise), so the current base can be directly replaced by the bases held here.
        positions : list
            Python list of all positions with a mutation, insertion, or deletion.
Reads in a vcf / vcf . gz file and associated reference sequence fasta ( to which the VCF file is mapped ) . Parses mutations insertions and deletions and stores them in a nested dict see returns for the dict structure . Calls with heterozygous values 0 / 1 0 / 2 etc and no - calls ( . / . ) are replaced with Ns at the associated sites . Positions are stored to correspond the location in the reference sequence in Python ( numbering is transformed to start at 0 ) Parameters ---------- vcf_file : string Path to the vcf or vcf . gz file to be read in ref_file : string Path to the fasta reference file to be read in Returns -------- compress_seq : nested dict In the format : :: { reference : AGCTCGA .. A sequences : { seq1 : { 4 : A 7 : - } seq2 : { 100 : C } } insertions : { seq1 : { 4 : ATT } seq3 : { 1 : TT 10 : CAG } } positions : [ 1 4 7 10 100 ... ] } references : string String of the reference sequence read from the Fasta to which the variable sites are mapped sequences : nested dict Dict containing sequence names as keys which map to dicts that have position as key and the single - base mutation ( or deletion ) as values insertions : nested dict Dict in the same format as the above which stores insertions and their locations . The first base of the insertion is the same as whatever is currently in that position ( Ref if no mutation mutation in sequences otherwise ) so the current base can be directly replaced by the bases held here . positions : list Python list of all positions with a mutation insertion or deletion .