Fasta alignment from a multi sample VCF - a less terrible method

May 19 2020


I previously posted a method to extract all the snps from a vcf with many samples to a fasta file. It turns out to have been pretty rubbish. Use this method instead. This was mainly because I didn’t properly read the documentation for pyvcf which does this perfectly easily and rapidly. It also shows the disadvantages of using the first solution you come across on biostars or stackoverflow. Though this was meant as a placeholder solution at the time. I have left the previous post up as it serves as a comparison to this page. That solution did not scale well since it used pyfaidx to randomly access the reference fasta file at every site for each sample. This isn’t necessary at all since the reference allele is (obviously) stored in the vcf file anyway.


import sys,os
import pandas as pd
from Bio import SeqIO
import vcf


This function returns a list of SeqRecord objects and a matrix of the sites in the form of a pandas DataFrame. It iterates over all records, each of which has a samples object. Then it simply adds the sample.gt_bases value to a list, one for each sample. This can be made into a SeqRecord object and then saved to a fasta file. In only return the matrix for my own purposes and it may not be required.

def fasta_alignment_from_vcf(vcf_file):
    """Get snp site alt bases as sequences from all samples in a vcf file"""

    import vcf
    from collections import defaultdict
    vcf_reader = vcf.Reader(open(vcf_file, 'rb'))  
    def default():
        return []
    result = defaultdict(default)
    sites = []
    for record in vcf_reader:
        ref = record.REF
        for sample in record.samples:
            name = sample.sample
            if sample.gt_bases != None:
    print ('found %s sites' %len(sites))
    recs = []
    for sample in result:
        seq = ''.join(result[sample])
        seqrec = SeqRecord(Seq(seq),id=sample)

    smat = pd.DataFrame(result)
    smat.index = sites
    return recs, smat