Bio Vcf Basics

Version Compatibility

Reference examples tested with: bcftools 1.19+, numpy 1.26+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

VCF/BCF Basics

View and query variant files using bcftools and cyvcf2.

Format Overview

VCF Format Structure

##fileformat=VCFv4.2
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total Depth">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
#CHROM  POS     ID      REF     ALT     QUAL    FILTER  INFO    FORMAT  SAMPLE1
chr1    1000    rs123   A       G       30      PASS    DP=50   GT:DP   0/1:25

Header Lines (##)

• ##fileformat - VCF version
• ##INFO - INFO field definitions
• ##FORMAT - FORMAT field definitions
• ##FILTER - Filter definitions
• ##contig - Reference contigs
• ##reference - Reference genome

Column Header (#CHROM)

Fixed columns: CHROM, POS, ID, REF, ALT, QUAL, FILTER, INFO, FORMAT Followed by sample columns

Data Columns

Critical Field Interpretation

Understanding what each field actually measures -- and what it does not -- is essential for filtering and interpretation decisions.

QUAL vs GQ: Different Questions

QUAL can be high even when an individual sample's genotype is uncertain. Conversely, a sample may have a confident genotype (high GQ) at a site with moderate QUAL.

AD vs DP Discrepancy

The sum of AD (allelic depth) values is often less than DP (total depth). This is expected behavior, not an error:

• DP counts all reads spanning the position, including uninformative reads (low base quality, ambiguous alignment)
• AD counts only reads that confidently support a specific allele
• INFO/DP (site-level) differs from FORMAT/DP (per-sample) -- site DP is the sum across all samples

Key INFO Annotations for Filtering

PL (Phred-Scaled Likelihoods)

PL encodes the relative likelihood of each possible genotype. For a biallelic site: PL = [P(0/0), P(0/1), P(1/1)]. The most likely genotype always has PL=0; GQ equals the difference between the lowest and second-lowest PL values.

For multiallelic sites with n alleles, PL contains n*(n+1)/2 values covering all possible diploid genotypes.

bcftools view

Goal: View, subset, and convert VCF/BCF files from the command line.

Approach: Use bcftools view with flags for header control, region selection, sample extraction, and format conversion.

"Show me what's in this VCF file" → Display VCF contents with optional filtering by header, region, or sample.

View VCF

bcftools view input.vcf.gz | head

View Header Only

bcftools view -h input.vcf.gz

View Without Header

bcftools view -H input.vcf.gz | head

View Specific Region

bcftools view input.vcf.gz chr1:1000000-2000000

View Specific Samples

bcftools view -s sample1,sample2 input.vcf.gz

Exclude Samples

bcftools view -s ^sample3 input.vcf.gz

bcftools query

Goal: Extract specific fields from a VCF in a custom tabular format.

Approach: Use bcftools query with format specifiers for CHROM, POS, INFO, and FORMAT fields.

"Extract positions and genotypes from my VCF" → Pull specific columns from variant records into a flat text format.

Extract specific fields in custom format.

Basic Query

bcftools query -f '%CHROM\t%POS\t%REF\t%ALT\n' input.vcf.gz

Query with INFO Fields

bcftools query -f '%CHROM\t%POS\t%INFO/DP\t%INFO/AF\n' input.vcf.gz

Query with Sample Fields

bcftools query -f '%CHROM\t%POS[\t%GT]\n' input.vcf.gz

Query Specific Samples

bcftools query -f '%CHROM\t%POS[\t%SAMPLE=%GT]\n' -s sample1,sample2 input.vcf.gz

Include Header

bcftools query -H -f '%CHROM\t%POS\t%REF\t%ALT\n' input.vcf.gz

Common Format Specifiers

Format Conversion

Goal: Convert between VCF, compressed VCF, and BCF formats.

Approach: Use bcftools view with output format flags (-Ov, -Oz, -Ob) and bgzip/index for compression and indexing.

VCF to BCF

bcftools view -Ob -o output.bcf input.vcf.gz

BCF to VCF

bcftools view -Ov -o output.vcf input.bcf

Compress VCF (bgzip)

bgzip input.vcf
# Creates input.vcf.gz

Index VCF/BCF

bcftools index input.vcf.gz
# Creates input.vcf.gz.csi

bcftools index -t input.vcf.gz
# Creates input.vcf.gz.tbi (tabix index)

Output Format Options

Genotype Encoding

Phased vs Unphased

• / separates unphased alleles -- the two chromosomal copies are known, but which came from which parent is not
• | separates phased alleles -- haplotype assignment is known (e.g., from read-backed phasing, trio analysis, or long-read sequencing)
• Phasing matters for compound heterozygosity: two variants on the same gene are pathogenic only if they are on different haplotypes (in trans), not the same haplotype (in cis)

Multiallelic Genotypes

At multiallelic sites (e.g., ALT = G,T), allele indices reference the comma-separated ALT list: 0=REF, 1=first ALT, 2=second ALT. Genotype 1/2 means one copy of each ALT allele. Splitting multiallelic sites into biallelic records with bcftools norm -m- converts 1/2 into two 0/1 records, losing compound heterozygosity information -- see variant-normalization for caveats.

cyvcf2 Python Alternative

Goal: Read, query, and write VCF files programmatically in Python.

Approach: Use cyvcf2's VCF reader to iterate variants, access properties/INFO/FORMAT fields, and write filtered output with Writer.

"Parse this VCF in Python" → Open VCF with cyvcf2 and iterate variant records with attribute-style access to fields.

Open and Iterate

from cyvcf2 import VCF

vcf = VCF('input.vcf.gz')
for variant in vcf:
    print(f'{variant.CHROM}:{variant.POS} {variant.REF}>{variant.ALT[0]}')

Access Variant Properties

from cyvcf2 import VCF

for variant in VCF('input.vcf.gz'):
    print(f'Chrom: {variant.CHROM}')
    print(f'Pos: {variant.POS}')
    print(f'ID: {variant.ID}')
    print(f'Ref: {variant.REF}')
    print(f'Alt: {variant.ALT}')  # List
    print(f'Qual: {variant.QUAL}')
    print(f'Filter: {variant.FILTER}')
    print(f'Type: {variant.var_type}')  # snp, indel, etc.
    break

Access INFO Fields

from cyvcf2 import VCF

for variant in VCF('input.vcf.gz'):
    dp = variant.INFO.get('DP')
    af = variant.INFO.get('AF')
    print(f'{variant.CHROM}:{variant.POS} DP={dp} AF={af}')

Access Genotypes

from cyvcf2 import VCF

vcf = VCF('input.vcf.gz')
samples = vcf.samples  # List of sample names

for variant in vcf:
    gts = variant.gt_types  # 0=HOM_REF, 1=HET, 2=UNKNOWN, 3=HOM_ALT
    for sample, gt in zip(samples, gts):
        gt_str = ['HOM_REF', 'HET', 'UNKNOWN', 'HOM_ALT'][gt]
        print(f'{sample}: {gt_str}')
    break

Access Sample Fields

from cyvcf2 import VCF

for variant in VCF('input.vcf.gz'):
    depths = variant.format('DP')  # numpy array
    gqs = variant.format('GQ')     # Genotype quality
    print(f'Depths: {depths}')

Fetch Region

from cyvcf2 import VCF

vcf = VCF('input.vcf.gz')
for variant in vcf('chr1:1000000-2000000'):
    print(f'{variant.CHROM}:{variant.POS}')

Get Header Info

from cyvcf2 import VCF

vcf = VCF('input.vcf.gz')
print(f'Samples: {vcf.samples}')
print(f'Contigs: {vcf.seqnames}')

# INFO field definitions
for info in vcf.header_iter():
    if info['HeaderType'] == 'INFO':
        print(f'{info["ID"]}: {info["Description"]}')

Write VCF

from cyvcf2 import VCF, Writer

vcf = VCF('input.vcf.gz')
writer = Writer('output.vcf', vcf)

for variant in vcf:
    if variant.QUAL > 30:
        writer.write_record(variant)

writer.close()
vcf.close()

Quick Reference

Common Errors

Related Skills

• variant-calling - Generate VCF from alignments
• filtering-best-practices - Filter variants by quality/criteria
• vcf-manipulation - Merge, concat, intersect VCFs
• alignment-files/pileup-generation - Generate pileup for calling