Skills Guide

Haplotype Phasing Using Beagle and SHAPEIT

VerifiedCaution

Phase genotypes into haplotypes using Beagle or SHAPEIT. Determines which alleles are inherited together. Use when preparing VCF files for imputation, HLA typing, or population genetic analyses.

Sby Skills Guide Bot
Data & AIIntermediate
108/30/2026
Claude CodeCursorWindsurfCopilotCodex
#bioinformatics#haplotype-phasing#beagle#shapeit5#genomics

Recommended for

Claude CodeCursorCopilotWindsurfData scientistCodex

Our review

This skill phases genotypes into haplotypes using Beagle or SHAPEIT5, preparing VCF files for imputation, HLA typing, or population genetic analyses.

Strengths

  • Supports two major phasing tools (Beagle and SHAPEIT5) with advanced options.
  • Incorporates genetic maps and reference panels to improve accuracy.
  • Provides commands for per-chromosome processing and concatenation.
  • Includes VCF preprocessing and result verification steps.

Limitations

  • Requires downloading Beagle and installing SHAPEIT5 or Java.
  • Focuses on command-line usage without explaining underlying algorithms.
  • Options and formats are tool-specific and may need adaptation.
When to use it

Use this skill when you have an unphased VCF and need phased haplotypes for imputation, HLA typing, or population genetics analyses.

When not to use it

Do not use it if you only need simple genotype calling or if your data does not require full phasing.

Security analysis

Caution
Quality score88/100

The skill instructs legitimate bioinformatics phasing workflows using standard tools (Beagle, SHAPEIT5, bcftools). It does not contain destructive, exfiltration, or obfuscated actions. However, it involves downloading and running external executables and uses shell commands, so caution is warranted.

Findings
  • •Downloads and executes a Java jar (Beagle) from an external source without checksum verification.
  • •Uses shell commands to download genetic maps and process VCF files.
  • •Contains author signature and copyright notice but no explicit license for use.

Examples

Phase with Beagle using a genetic map
Phase the genotypes in input.vcf.gz using Beagle 5.4 with the provided genetic map plink.chr22.GRCh38.map, using 8 threads, and name the output 'phased'.
Phase with SHAPEIT5 common and rare variants
Use SHAPEIT5 to phase the common variants from input.vcf.gz with genetic_map.txt, then phase rare variants using the common phased scaffold, with 8 threads.
Verify phasing results
Check whether the variants in phased.vcf.gz are phased by counting the number of genotypes containing a pipe (|) using bcftools query.
<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

name: bio-phasing-imputation-haplotype-phasing description: 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. tool_type: cli primary_tool: beagle measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

Haplotype Phasing

Beagle 5.4 Phasing (Recommended)

# 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

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

# 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)

# 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

# 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

# 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

# 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

# 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

# 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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