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VCF/BCF Basics · FreedomIntelligence | DecimalAI

Bio Vcf Basics

SkillScore16Maintained

bio-vcf-basics

View, query, and understand VCF/BCF variant files using bcftools and cyvcf2. Use when inspecting variants, extracting specific fields, or understanding VCF format structure.

scienceby FreedomIntelligence

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

Data Engineer pack

1 · One-time — install the CLI (docs ↗)

pip install decimalai

2 · Get the skill — writes .claude/skills/bio-vcf-basics/SKILL.md

decimalai skills pull bio-vcf-basics --out .claude/skills/

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/bio-vcf-basics/SKILL.md https://app.decimal.ai/s/bio-vcf-basics/SKILL.md

Raw file: /s/bio-vcf-basics/SKILL.md ↗ · machine-readable summary at /s/bio-vcf-basics.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

25 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 57d ago

Yes — +8% lift · at higher cost+203% tokens0% turns16% of whole cases pass with skill (4/25)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-15	✗→✓	▲ Improved	—	—
case-22	✗→✓	▲ Improved	—	—
case-07	✓→✓	＝ Same ✓	—	—
case-04	✓→✓	＝ Same ✓	—	—
case-12	✗→✗	＝ Same ✗	—	—

Showing 5 of 25 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 7/30/2026

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IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

FreedomIntelligence / OpenClaw-Medical-Skills

skills/bio-vcf-basics/SKILL.md

View on GitHub ↗

Imported 8/1/2026Version v1

Skill contents

SKILL.md

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

| Format | Description | Use Case | |--------|-------------|----------| | VCF | Text format, human-readable | Debugging, small files | | VCF.gz | Compressed VCF (bgzip) | Standard distribution | | BCF | Binary VCF | Fast processing, large files |

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

| Column | Description | |--------|-------------| | CHROM | Chromosome | | POS | 1-based position | | ID | Variant identifier (e.g., rs number) | | REF | Reference allele | | ALT | Alternate allele(s), comma-separated | | QUAL | Phred-scaled quality score | | FILTER | PASS or filter name | | INFO | Semicolon-separated key=value pairs | | FORMAT | Colon-separated format keys | | SAMPLE | Colon-separated values matching FORMAT |

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

bash
bcftools view input.vcf.gz | head

View Header Only

bash
bcftools view -h input.vcf.gz

View Without Header

bash
bcftools view -H input.vcf.gz | head

View Specific Region

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

View Specific Samples

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

Exclude Samples

bash
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

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

Query with INFO Fields

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

Query with Sample Fields

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

Query Specific Samples

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

Include Header

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

Common Format Specifiers

| Specifier | Description | |-----------|-------------| | %CHROM | Chromosome | | %POS | Position | | %ID | Variant ID | | %REF | Reference allele | | %ALT | Alternate allele | | %QUAL | Quality score | | %FILTER | Filter status | | %INFO/TAG | INFO field value | | %TYPE | Variant type (snp, indel, etc.) | | [%GT] | Genotype (per sample) | | [%DP] | Depth (per sample) | | [%SAMPLE] | Sample name | | \n | Newline | | \t | Tab |

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

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

BCF to VCF

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

Compress VCF (bgzip)

bash
bgzip input.vcf
# Creates input.vcf.gz

Index VCF/BCF

bash
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

| Flag | Format | |------|--------| | -Ov | Uncompressed VCF | | -Oz | Compressed VCF (bgzip) | | -Ou | Uncompressed BCF | | -Ob | Compressed BCF |

Genotype Encoding

| Genotype | Meaning | |----------|---------| | 0/0 | Homozygous reference | | 0/1 | Heterozygous | | 1/1 | Homozygous alternate | | 1/2 | Heterozygous (two different alts) | | ./. | Missing | | 0\|1 | Phased heterozygous |

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

python
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

python
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

python
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

python
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

python
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

python
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

python
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

python
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

| Task | bcftools | cyvcf2 | |------|----------|--------| | View VCF | bcftools view file.vcf.gz | VCF('file.vcf.gz') | | View header | bcftools view -h file.vcf.gz | vcf.header_iter() | | Get region | bcftools view file.vcf.gz chr1:1-1000 | vcf('chr1:1-1000') | | Query fields | bcftools query -f '%CHROM\t%POS\n' | Loop with properties | | Count variants | bcftools view -H file.vcf.gz \| wc -l | sum(1 for _ in vcf) | | VCF to BCF | bcftools view -Ob -o out.bcf in.vcf.gz | Use Writer |

Common Errors

| Error | Cause | Solution | |-------|-------|----------| | no BGZF EOF marker | Not bgzipped | Use bgzip not gzip | | index required | Missing index for region query | Run bcftools index | | sample not found | Wrong sample name | Check with bcftools query -l |

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

Illustrative Want to see what bio-vcf-basics would put in front of your model? Preview the rendered body and check its trigger phrases — no LLM call, no signup.

Latest benchmark · publisher runVerified

7/26/2026, 09:56 UTC · 25 cases

Lift

+8%

16% vs 8%

Agent turns

1.0 vs 1.0

Tokens

+203%

3,539.28 vs 1,169.16

fail → pass · 2pass → pass · 2fail → fail · 21

Per-case results (25)

Case	Status	Duration (ms)			Turns			Tokens			Tool calls
Case	Status	Without	With	Δ	Without	With	Δ	Without	With	Δ	Without	With	Δ
case-12 Write a Python snippet to iterate through `variants.vcf.gz`, obtain the numeric genotype array for each variant record, and map codes where 0 is hom-ref, 1 is het, and 3 is hom-alt.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-13 Write a Python code snippet to read `variants.vcf.gz` and retrieve the per-sample read depths (`DP`) recorded in the FORMAT column as a NumPy array for each variant.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-14 Write a Python snippet to iterate over variant records restricted to coordinate region `chr1:1000000-2000000` from indexed file `indexed_calls.vcf.gz`.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-21 Write a command-line command using bcftools query to extract CHROM, POS, REF, and ALT columns from `data.vcf.gz` with a leading header row showing column names.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-25 Write a command to generate an uncompressed BCF pileup file from an alignment file `aligned.bam` against reference genome `ref.fasta`.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-03 Write a command-line command to view the data lines of `data.vcf.gz` while suppressing all `##` header and `#CHROM` header lines.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-18 Which bcftools view flag specifies uncompressed BCF output format suitable for piping directly into downstream analysis commands without compression overhead?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-05 Write a command-line command to slice `cohort.vcf.gz` so that the output VCF contains data only for sample `HG001` and sample `HG002`.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-17 You have an uncompressed VCF file named `variants.vcf`. Write the exact command-line command to compress it so that it supports spatial region indexing with tabix.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-07 Write a command-line command to convert `input.vcf.gz` into a compressed binary BCF file named `output.bcf`.	pass→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-09 Write a command-line command to generate a tabix-compatible `.tbi` index file for `alignment_variants.vcf.gz`.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-04 Write a command-line command to extract variants from `gnomad.vcf.gz` located between position 1000000 and 2000000 on chromosome 1.	pass→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-20 When running `bcftools index sample.vcf.gz`, you receive the error: `[E::hts_idx_load3] get_disk_err: no BGZF EOF marker`. What caused this error and how do you fix it?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-06 Write a command-line command to output `cohort.vcf.gz` excluding sample `NA12878` while retaining all other samples in the VCF.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-01 Write a command-line invocation to output only tab-separated CHROM, POS, REF, and ALT columns from `variants.vcf.gz` without any metadata header lines.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-23 Write a command-line command to merge three separate single-sample VCF files (`sample1.vcf.gz`, `sample2.vcf.gz`, `sample3.vcf.gz`) into a single multi-sample VCF file `merged.vcf.gz`.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-16 Write a Python snippet to read `input.vcf.gz`, filter for variants with QUAL score strictly greater than 30, and write those matching records to `filtered.vcf` preserving header metadata.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-15 Write a Python snippet to iterate through header definitions in `input.vcf.gz` and print descriptions for all INFO fields defined in the metadata.	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-22 Write a Python snippet to inspect variants in `sample.vcf.gz` and print whether each record is classified as a SNP or INDEL using built-in record properties.	fail→pass	—	—	—	—	—	—	—	—	—	—	—	—
case-02 Write a command-line command to inspect only the header section (metadata lines and column names) of `sample.vcf.gz`.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-10 Write a command-line command to extract the DP (depth) and AF (allele frequency) INFO tags for every record in `study.vcf.gz` alongside chromosome and position.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-11 Write a command-line command to dump variants from `panel.vcf.gz` showing chromosome, position, and per-sample genotypes formatted as `SAMPLE=GT` for each sample.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-19 In a VCF file, sample A has genotype `0/1` and sample B has genotype `0\|1`. Explain the distinction in phasing represented by the slash versus vertical bar delimiters.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-08 Write a command-line command to convert binary BCF file `input.bcf` into an uncompressed text VCF file named `output.vcf`.	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—
case-24 What standard GATK filter parameters and cutoffs should be specified when applying hard filters to raw SNP variant calls based on Quality by Depth (QD) and Strand Odds Ratio (SOR)?	fail→fail	—	—	—	—	—	—	—	—	—	—	—	—

These cases were also screened by the skill’s intent / safety pass.See the Trust review ↗Reproduce this benchmark in Colab ↗

How this skill was measured

DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 25 cases were attempted. The headline lift of +8 percentage points is the difference between those two pass rates over the 25 comparable cases.

Model measured: gemini-3.6-flash
Graded by: gemini-3.6-flash
Grading method: judged
Verification: verified
Pass rate without the skill: 8%
Pass rate with the skill: 16%
Cases attempted: 25
Cases counted toward lift: 25
Cases that regressed: 0
Skill version measured: v1
Run completed: 7/26/2026, 09:56 UTC

The per-case answers from this run were removed by the retention sweep, so the case table below shows the verdicts without the text either arm produced. The counts above were recorded at the time and are unaffected. Answers are now kept for 180 days.

SkillScore blends 4 signals1 of 4 complete

BenchmarkPass rate WITH skill on a verified run16

Live evalNeeds ≥10 evaluated traces in 30 days

AI ratingNeeds ≥10 rated traces

AdoptionNeeds ≥10 serves across ≥2 orgs in 30 days

Efficiency · separate axis (at equal correctness)+0% turns+255% tokens

Shown for transparency; not credited unless a verified run shows no correctness regression.

Backed by 1 of 4 signals — each added signal makes the score more robust.

Verified on gemini-3.6-flash · re-tested 57 days ago

Other measured skills in the registry, with their headline benchmark lift.