Populating FORMAT/AF, and dropping variants with AF<min_allele_fraction

    Strelka2 doesn't report exact AF for a variant, however it can be calculated as alt_counts/dp from existing fields:
    somatic
      snps:    GT:DP:FDP:SDP:SUBDP:AU:CU:GU:TU                 dp=DP                {ALT}U[0] = alt_counts(tier1,tier2)
      indels:  GT:DP:DP2:TAR:TIR:TOR:DP50:FDP50:SUBDP50:BCN50  dp=DP                TIR = alt_counts(tier1,tier2)
    germline
      snps:    GT:GQ:GQX:DP:DPF:AD:ADF:ADR:SB:FT:PL(:PS)       dp=sum(alt_counts)   AD = ref_count,alt_counts
      indels:  GT:GQ:GQX:DPI:AD:ADF:ADR:FT:PL(:PS)             dp=sum(alt_counts)   AD = ref_count,alt_counts

def _af_annotate_and_filter(paired, items, in_file, out_file):
    """Populating FORMAT/AF, and dropping variants with AF<min_allele_fraction

    Strelka2 doesn't report exact AF for a variant, however it can be calculated as alt_counts/dp from existing fields:
    somatic
      snps:    GT:DP:FDP:SDP:SUBDP:AU:CU:GU:TU                 dp=DP                {ALT}U[0] = alt_counts(tier1,tier2)
      indels:  GT:DP:DP2:TAR:TIR:TOR:DP50:FDP50:SUBDP50:BCN50  dp=DP                TIR = alt_counts(tier1,tier2)
    germline
      snps:    GT:GQ:GQX:DP:DPF:AD:ADF:ADR:SB:FT:PL(:PS)       dp=sum(alt_counts)   AD = ref_count,alt_counts
      indels:  GT:GQ:GQX:DPI:AD:ADF:ADR:FT:PL(:PS)             dp=sum(alt_counts)   AD = ref_count,alt_counts
    """
    data = paired.tumor_data if paired else items[0]
    min_freq = float(utils.get_in(data["config"], ("algorithm", "min_allele_fraction"), 10)) / 100.0
    logger.debug("Filtering Strelka2 calls with allele fraction threshold of %s" % min_freq)
    ungz_out_file = "%s.vcf" % utils.splitext_plus(out_file)[0]
    if not utils.file_exists(ungz_out_file) and not utils.file_exists(ungz_out_file + ".gz"):
        with file_transaction(data, ungz_out_file) as tx_out_file:
            vcf = cyvcf2.VCF(in_file)
            vcf.add_format_to_header({
                'ID': 'AF',
                'Description': 'Allele frequency, as calculated in bcbio: AD/DP (germline), <ALT>U/DP (somatic snps), '
                               'TIR/DPI (somatic indels)',
                'Type': 'Float',
                'Number': '.'})
            vcf.add_filter_to_header({
                'ID': 'MinAF',
                'Description': 'Allele frequency is lower than %s%% ' % (min_freq*100) + (
                    '(configured in bcbio as min_allele_fraction)'
                    if utils.get_in(data["config"], ("algorithm", "min_allele_fraction"))
                    else '(default threshold in bcbio; override with min_allele_fraction in the algorithm section)')})
            w = cyvcf2.Writer(tx_out_file, vcf)
            tumor_index = vcf.samples.index(data['description'])
            for rec in vcf:
                if paired:  # somatic?
                    if rec.is_snp:  # snps?
                        alt_counts = rec.format(rec.ALT[0] + 'U')[:,0]  # {ALT}U=tier1_depth,tier2_depth
                    else:  # indels
                        alt_counts = rec.format('TIR')[:,0]  # TIR=tier1_depth,tier2_depth
                    dp = rec.format('DP')[:,0]
                elif rec.format("AD") is not None:  # germline?
                    alt_counts = rec.format('AD')[:,1:]  # AD=REF,ALT1,ALT2,...
                    dp = np.sum(rec.format('AD')[:,0:], axis=1)[:, None]
                else: # germline gVCF record
                    alt_counts, dp = (None, None)
                if dp is not None:
                    with np.errstate(divide='ignore', invalid='ignore'):  # ignore division by zero and put AF=.0
                        af = np.true_divide(alt_counts, dp)
                        af[~np.isfinite(af)] = .0  # -inf inf NaN -> .0
                    rec.set_format('AF', af)
                    if paired and np.all(af[tumor_index] < min_freq):
                        vcfutils.cyvcf_add_filter(rec, 'MinAF')
                w.write_record(rec)
            w.close()
    return vcfutils.bgzip_and_index(ungz_out_file, data["config"])