bio-vcf

name	bio-vcf
description	This skill should be used when the user asks to analyze, filter, or inspect VCF/BCF variant files from WGS/WES sequencing. Triggers include requests to calculate variant statistics, filter variants by quality/depth/frequency, extract variants from specific chromosomes or regions, or export variant data as JSON for downstream analysis.
user_invocable	true

VCF Toolkit

Toolkit for VCF/BCF variant file analysis: calculate statistics, filter variants, and export as JSON. Designed for WGS/WES sequencing result inspection and quality control.

Quick Start

Install

uv pip install pysam typer

Basic Usage

# 1. VCF 統計情報を取得
python scripts/vcf_stats.py --vcf variants.vcf.gz --chrom chr1

# 2. 高品質バリアントのみをフィルタして新しい VCF を作成
python scripts/filter_vcf.py \
  --vcf variants.vcf.gz \
  --output high_quality.vcf \
  --min-qual 30 \
  --min-dp 10

# 3. フィルタされたバリアントを JSON で出力（≤100 エントリ）
python scripts/inspect_vcf.py \
  --vcf high_quality.vcf \
  --chrom chr1 \
  --output chr1.json

Scripts

inspect_vcf.py - VCF Inspection & JSON Export

Extract variants from VCF files for specific chromosomes or regions and export as JSON format.

Required Arguments

• --vcf PATH - Input VCF file path
• --chrom TEXT or --region TEXT - Either one required
  • --chrom: Entire chromosome (e.g., chr1)
  • --region: Specific region (e.g., chr1:1000000-2000000)

Optional Arguments

Output:

• --output PATH - JSON output path (default: stdout)

Filter Conditions:

• --min-qual FLOAT - Minimum quality score (QUAL >= X)
• --min-dp INT - Minimum depth (INFO/DP >= X)
• --min-af FLOAT - Minimum allele frequency (INFO/AF >= X)
• --max-af FLOAT - Maximum allele frequency (INFO/AF <= X)
• --pass-only / --all-filters - PASS only (default) / Include all filters

Limits:

• --max-variants INT - Maximum variant count (default: 100)
• --force - Ignore entry limit (allows large JSON output)

Output Format (JSON)

{
  "num_variants": 45,
  "samples": ["sample1", "sample2"],
  "variants": [
    {
      "chrom": "chr1",
      "pos": 12345,
      "id": "rs123456",
      "ref": "A",
      "alts": ["G"],
      "qual": 100.0,
      "filter": ["PASS"],
      "info": {
        "DP": 50,
        "AF": [0.5
         
      
       
              
              
      
    
  

vcf_stats.py - VCF Statistics

Calculate comprehensive statistics from VCF files and output as JSON. Includes variant counts, quality distributions, depth distributions, and allele frequency statistics.

Arguments

Required:

• --vcf PATH - Input VCF file path

Optional:

• --chrom TEXT - Chromosome specification (default: all chromosomes)
• --region TEXT - Region specification (e.g., chr1:1000-2000)
• --output PATH - JSON output path (default: stdout)

Output Content (JSON)

• total_variants - Total variant count
• filter_counts - Breakdown by filter (PASS, LowQual, etc.)
• variant_types - Breakdown by variant type (SNP, insertion, deletion)
• chrom_counts - Variant count per chromosome
• quality_stats - Quality score statistics (min, max, mean, median)
• depth_stats - Depth statistics (INFO/DP)
• allele_frequency_stats - Allele frequency statistics (INFO/AF)

Usage Examples

# Calculate statistics for chr1
python scripts/vcf_stats.py --vcf variants.vcf.gz --chrom chr1

# Calculate statistics for all chromosomes (output to JSON file)
python scripts/vcf_stats.py --vcf variants.vcf.gz --output stats.json

# Calculate statistics for specific region
python scripts/vcf_stats.py --vcf variants.vcf.gz --region chr1:10000-20000

filter_vcf.py - VCF Filtering

Filter VCF files by quality, depth, and allele frequency criteria. Output filtered variants as a new VCF file.

Arguments

Required:

• --vcf PATH - Input VCF file path
• --output PATH - Output VCF file path

Optional:

• --chrom TEXT - Chromosome specification
• --region TEXT - Region specification (e.g., chr1:1000-2000)
• --min-qual FLOAT - Minimum quality score
• --min-dp INT - Minimum depth (INFO/DP)
• --min-af FLOAT - Minimum allele frequency (INFO/AF)
• --max-af FLOAT - Maximum allele frequency (INFO/AF)
• --pass-only - PASS variants only (default: False)

Usage Examples

# Extract chr1 PASS variants only
python scripts/filter_vcf.py \
  --vcf variants.vcf.gz \
  --output chr1_pass.vcf \
  --chrom chr1 \
  --pass-only

# Extract high-quality variants (QUAL >= 30, DP >= 10)
python scripts/filter_vcf.py \
  --vcf variants.vcf.gz \
  --output high_quality.vcf \
  --min-qual 30 \
  --min-dp 10

# Extract rare variants (AF <= 0.01)
python scripts/filter_vcf.py \
  --vcf variants.vcf.gz \
  --output rare_variants.vcf \
  --max-af 0.01

Workflow Examples

Example 1: Comprehensive Variant Analysis Workflow

Combine all three scripts for complete VCF analysis:

# Step 1: Calculate overall statistics
python scripts/vcf_stats.py --vcf variants.vcf.gz --chrom chr1 --output stats.json

# Step 2: Filter high-quality variants to new VCF
python scripts/filter_vcf.py \
  --vcf variants.vcf.gz \
  --output high_quality.vcf \
  --chrom chr1 \
  --min-qual 30 \
  --min-dp 10 \
  --pass-only

# Step 3: Export filtered variants as JSON for downstream analysis
python scripts/inspect_vcf.py \
  --vcf high_quality.vcf \
  --chrom chr1 \
  --output chr1_filtered.json

Example 2: Rare Variant Discovery

Identify and export rare variants from specific region:

# Filter rare variants (AF <= 0.01)
python scripts/filter_vcf.py \
  --vcf variants.vcf.gz \
  --output rare.vcf \
  --region chr17:41196312-41277500 \
  --max-af 0.01

# Export as JSON for analysis
python scripts/inspect_vcf.py \
  --vcf rare.vcf \
  --region chr17:41196312-41277500 \
  --output brca1_rare.json

Error Handling

Variant Count Exceeds Limit

$ python scripts/inspect_vcf.py --vcf huge.vcf --chrom chr1 --output out.json

Error: VCF contains 1,234+ variants after filtering (limit: 100).

Suggestions:
  - Apply more restrictive filters: --min-qual, --min-dp, --pass-only
  - Specify a genomic region: --region chr1:1000-2000
  - Override limit with --force (warning: may produce very large JSON)
  - Use bcftools directly for large-scale processing

Current filter conditions:
  --chrom chr1 --pass-only

Solutions:

• Apply more restrictive filters: --min-qual 30, --min-dp 10
• Narrow down the region: --region chr1:1000000-1100000
• Override limit with --force (use cautiously)

Missing Chromosome/Region Specification

$ python scripts/inspect_vcf.py --vcf variants.vcf --output out.json

Error: Either --chrom or --region must be specified.

Solutions:

• Add --chrom chr1 or --region chr1:1000-2000 to the command

Best Practices

1. Always Specify Chromosome or Region

Always specify chromosome or region when using inspect_vcf.py to avoid processing entire VCF files inefficiently.

# ❌ Bad: No chromosome specified
python scripts/inspect_vcf.py --vcf variants.vcf

# ✅ Good: Chromosome specified
python scripts/inspect_vcf.py --vcf variants.vcf --chrom chr1

2. Apply Additional Filters for Efficiency

Combine quality and depth filters with default PASS-only filtering for better results.

# ✅ Good: Multiple filters applied
python scripts/inspect_vcf.py \
  --vcf variants.vcf \
  --chrom chr1 \
  --min-qual 30 \
  --min-dp 10

3. Respect 100-Entry Limit for JSON Export

Use inspect_vcf.py for small datasets only. Pre-filter large VCF files with filter_vcf.py or bcftools before JSON export.

# Pre-filter large datasets with bcftools
bcftools view -i 'QUAL>=30 && DP>=10' -r chr1:1000000-2000000 variants.vcf > filtered.vcf

# Then export to JSON
python scripts/inspect_vcf.py --vcf filtered.vcf --chrom chr1 --output filtered.json

4. Use --force Cautiously

Use --force only when necessary. JSON files with thousands of entries can become several MB to tens of MB in size.

When to Use vcf-toolkit vs bcftools

Task	vcf-toolkit	bcftools
Small dataset JSON export	✅ inspect_vcf.py	-
Large-scale filtering	filter_vcf.py	✅ bcftools view
Complex filter expressions	-	✅ bcftools
VCF-to-VCF conversion	filter_vcf.py	✅ bcftools
Variant statistics	✅ vcf_stats.py	✅ bcftools stats

Recommended Workflow:

1. Pre-filter large datasets with bcftools or filter_vcf.py
2. Export filtered results to JSON with inspect_vcf.py for detailed inspection
3. Perform downstream analysis in Python/R using JSON output

Related Skills

• pysam - BAM/CRAM alignment file operations
• sequence-io - FASTA/FASTQ sequence file operations
• blast-search - BLAST homology search
• blat-api-searching - BLAT genome mapping

Troubleshooting

VCF File Too Large

Specify a narrower region or pre-filter with bcftools before JSON export.

# Specify narrower region
python scripts/inspect_vcf.py --vcf variants.vcf --region chr1:1000000-1100000

# Pre-filter with bcftools
bcftools view -i 'QUAL>=50' variants.vcf | python scripts/inspect_vcf.py --vcf - --chrom chr1

Index Error

Create tabix index for compressed VCF files.

# Compress with bgzip
bgzip variants.vcf

# Create tabix index
tabix -p vcf variants.vcf.gz

# Use indexed VCF
python scripts/inspect_vcf.py --vcf variants.vcf.gz --chrom chr1

Include Non-PASS Variants

Use --all-filters flag to include all variants regardless of FILTER field.

python scripts/inspect_vcf.py --vcf variants.vcf --chrom chr1 --all-filters