Agent skill

bio-phasing-imputation-haplotype-phasing

Phase genotypes into haplotypes using Beagle or SHAPEIT. Resolves which alleles are inherited together on each chromosome. Use when preparing VCF files for imputation, HLA typing, or population genetic analyses requiring phased haplotypes.

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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/haplotype-phasing

SKILL.md

Haplotype Phasing

Beagle 5.4 Phasing (Recommended)

bash
# Download Beagle 5.4
wget https://faculty.washington.edu/browning/beagle/beagle.22Jul22.46e.jar

# Basic phasing
java -jar beagle.22Jul22.46e.jar \
    gt=input.vcf.gz \
    out=phased

# Output: phased.vcf.gz (phased genotypes)

# With genetic map (improves accuracy)
java -jar beagle.22Jul22.46e.jar \
    gt=input.vcf.gz \
    map=plink.chr22.GRCh38.map \
    out=phased

Beagle Options

bash
java -jar beagle.22Jul22.46e.jar \
    gt=input.vcf.gz \
    out=phased \
    map=genetic_map.txt \
    nthreads=8 \
    window=40 \
    overlap=4 \
    ne=20000 \              # Effective population size
    seed=12345              # For reproducibility

Phase Per Chromosome

bash
# Process each chromosome separately
for chr in {1..22}; do
    java -Xmx16g -jar beagle.jar \
        gt=input.chr${chr}.vcf.gz \
        map=genetic_maps/plink.chr${chr}.GRCh38.map \
        out=phased.chr${chr} \
        nthreads=8
done

# Concatenate chromosomes
bcftools concat phased.chr*.vcf.gz -Oz -o phased.all.vcf.gz
bcftools index phased.all.vcf.gz

SHAPEIT5 Phasing (for Large Datasets)

bash
# Phase common variants first
shapeit5_phase_common \
    --input input.vcf.gz \
    --map genetic_map.txt \
    --output phased_common.bcf \
    --thread 8 \
    --log phased.log

# Then phase rare variants
shapeit5_phase_rare \
    --input input.vcf.gz \
    --scaffold phased_common.bcf \
    --map genetic_map.txt \
    --output phased.bcf \
    --thread 8

SHAPEIT5 with Reference Panel

bash
# Improves phasing using reference haplotypes
shapeit5_phase_common \
    --input input.vcf.gz \
    --reference reference_panel.bcf \
    --map genetic_map.txt \
    --output phased.bcf \
    --thread 8

Beagle with Reference Panel

bash
# Use reference panel for better phasing
java -jar beagle.22Jul22.46e.jar \
    gt=input.vcf.gz \
    ref=reference.vcf.gz \
    map=genetic_map.txt \
    out=phased \
    nthreads=8

Input Preparation

bash
# Filter variants before phasing
bcftools view -m2 -M2 -v snps input.vcf.gz -Oz -o biallelic_snps.vcf.gz

# Remove missing genotypes (optional)
bcftools view -g ^miss biallelic_snps.vcf.gz -Oz -o no_missing.vcf.gz

# Normalize (important!)
bcftools norm -f reference.fa -Oz -o normalized.vcf.gz input.vcf.gz

Check Phasing Results

bash
# View phased genotypes (| instead of /)
bcftools query -f '%CHROM\t%POS\t[%GT\t]\n' phased.vcf.gz | head

# Unphased: 0/1
# Phased: 0|1 or 1|0

# Count phased vs unphased
bcftools query -f '[%GT\n]' phased.vcf.gz | grep -c '|'

Genetic Maps

bash
# Download genetic maps (GRCh38)
wget https://faculty.washington.edu/browning/beagle/genetic_maps/plink.GRCh38.map.zip
unzip plink.GRCh38.map.zip

# Format: chromosome position rate(cM/Mb) genetic_position(cM)
# chr1 55550 2.981822 0.000000

Key Parameters

Parameter Beagle SHAPEIT5 Description
Threads nthreads --thread CPU threads
Window window --window Analysis window size
Eff. pop size ne --effective-size For LD modeling
Seed seed --seed Random seed

Memory Requirements

Dataset Size Beagle Memory SHAPEIT5 Memory
1,000 samples 8 GB 4 GB
10,000 samples 32 GB 16 GB
100,000 samples 64+ GB 32 GB

Phasing Accuracy Metrics

  • Switch error rate: Rate of phase switches vs truth
  • Mismatch error rate: Overall haplotype differences
  • Measure using trio data or known haplotypes

Related Skills

  • phasing-imputation/genotype-imputation - Impute after phasing
  • phasing-imputation/reference-panels - Get reference data
  • variant-calling/filtering-best-practices - Prepare input VCF
  • population-genetics/linkage-disequilibrium - LD analysis

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