Agent skill

consensus-sequences

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Install this agent skill to your Project

npx add-skill https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/variant-interpretation-acmg/bioSkills/consensus-sequences

SKILL.md

name: bio-consensus-sequences description: Generate consensus FASTA sequences by applying VCF variants to a reference using bcftools consensus. Use when creating sample-specific reference sequences or reconstructing haplotypes. tool_type: cli primary_tool: bcftools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

Consensus Sequences

Apply variants to reference FASTA using bcftools consensus.

Basic Usage

Generate Consensus

bash
bcftools consensus -f reference.fa input.vcf.gz > consensus.fa

Specify Sample

bash
bcftools consensus -f reference.fa -s sample1 input.vcf.gz > sample1.fa

Output to File

bash
bcftools consensus -f reference.fa -o consensus.fa input.vcf.gz

Haplotype Selection

First Haplotype Only

bash
bcftools consensus -f reference.fa -H 1 input.vcf.gz > haplotype1.fa

Second Haplotype Only

bash
bcftools consensus -f reference.fa -H 2 input.vcf.gz > haplotype2.fa

Haplotype Options

Option Description
-H 1 First haplotype
-H 2 Second haplotype
-H A Apply all ALT alleles
-H R Apply REF alleles where heterozygous
-I Apply IUPAC ambiguity codes (separate flag)

IUPAC Codes for Heterozygous Sites

bash
bcftools consensus -f reference.fa -I input.vcf.gz > consensus_iupac.fa

Heterozygous sites encoded with IUPAC ambiguity codes:

  • A/G → R
  • C/T → Y
  • A/C → M
  • G/T → K
  • A/T → W
  • C/G → S

Missing Data Handling

Mark Missing as N

bash
bcftools consensus -f reference.fa -M N input.vcf.gz > consensus.fa

Mark Low Coverage as N

Using a mask BED file:

bash
# Create mask from depth
samtools depth input.bam | awk '$3<10 {print $1"\t"$2-1"\t"$2}' > low_coverage.bed

# Apply mask
bcftools consensus -f reference.fa -m low_coverage.bed input.vcf.gz > consensus.fa

Mask Options

Option Description
-m FILE Mask regions in BED file with N
-M CHAR Character for masked regions (default N)

Region Selection

Specific Region

bash
bcftools consensus -f reference.fa -r chr1:1000-2000 input.vcf.gz > region.fa

Multiple Regions

Use with BED file to extract multiple regions.

Chain Files

Generate Chain File

bash
bcftools consensus -f reference.fa -c chain.txt input.vcf.gz > consensus.fa

Chain files map coordinates between reference and consensus:

  • Useful for liftover of annotations
  • Required when indels change sequence length

Chain File Format

chain score ref_name ref_size ref_strand ref_start ref_end query_name query_size query_strand query_start query_end id

Sample-Specific Consensus

For Each Sample

bash
for sample in $(bcftools query -l input.vcf.gz); do
    bcftools consensus -f reference.fa -s "$sample" input.vcf.gz > "${sample}.fa"
done

Both Haplotypes

bash
sample="sample1"
bcftools consensus -f reference.fa -s "$sample" -H 1 input.vcf.gz > "${sample}_hap1.fa"
bcftools consensus -f reference.fa -s "$sample" -H 2 input.vcf.gz > "${sample}_hap2.fa"

Filtering Before Consensus

PASS Variants Only

bash
bcftools view -f PASS input.vcf.gz | \
    bcftools consensus -f reference.fa > consensus.fa

High-Quality Variants Only

bash
bcftools filter -i 'QUAL>=30 && INFO/DP>=10' input.vcf.gz | \
    bcftools consensus -f reference.fa > consensus.fa

SNPs Only

bash
bcftools view -v snps input.vcf.gz | \
    bcftools consensus -f reference.fa > consensus_snps.fa

Sequence Naming

Default Naming

Output uses reference sequence names.

Custom Prefix

bash
bcftools consensus -f reference.fa -p "sample1_" input.vcf.gz > consensus.fa

Sequences named: sample1_chr1, sample1_chr2, etc.

Common Workflows

Phylogenetic Analysis Preparation

bash
# For each sample, generate consensus
mkdir -p consensus
for sample in $(bcftools query -l cohort.vcf.gz); do
    bcftools view -s "$sample" cohort.vcf.gz | \
        bcftools view -c 1 | \
        bcftools consensus -f reference.fa > "consensus/${sample}.fa"
done

# Combine for alignment
cat consensus/*.fa > all_samples.fa

Viral Genome Assembly

bash
# Apply high-quality variants only
bcftools filter -i 'QUAL>=30 && INFO/DP>=20' variants.vcf.gz | \
    bcftools view -f PASS | \
    bcftools consensus -f reference.fa -M N > consensus.fa

Gene-Specific Consensus

bash
# Extract gene region
bcftools consensus -f reference.fa -r chr1:1000000-1010000 \
    -s sample1 variants.vcf.gz > gene.fa

Masked Low-Coverage Regions

bash
# Create mask from coverage
samtools depth -a input.bam | \
    awk '$3<5 {print $1"\t"$2-1"\t"$2}' | \
    bedtools merge > low_coverage.bed

# Generate consensus with mask
bcftools consensus -f reference.fa -m low_coverage.bed \
    variants.vcf.gz > consensus.fa

Verify Consensus

Check Differences

bash
# Align consensus to reference
minimap2 -a reference.fa consensus.fa | samtools view -bS > alignment.bam

# Or simple comparison
diff <(grep -v "^>" reference.fa) <(grep -v "^>" consensus.fa) | head

Count Changes

bash
# Number of differences
bcftools view -H input.vcf.gz | wc -l

Handling Overlapping Variants

bcftools consensus handles overlapping variants automatically:

  • Applies variants in order
  • Warns about conflicts

Check for warnings:

bash
bcftools consensus -f reference.fa input.vcf.gz 2>&1 | grep -i warn

cyvcf2 Consensus (Simple Cases)

Manual Consensus Generation

python
from cyvcf2 import VCF
from Bio import SeqIO

# Load reference
ref_dict = {rec.id: str(rec.seq) for rec in SeqIO.parse('reference.fa', 'fasta')}

# Apply variants (SNPs only, simplified)
vcf = VCF('input.vcf.gz')
changes = {}

for variant in vcf:
    if variant.is_snp and len(variant.ALT) == 1:
        chrom = variant.CHROM
        pos = variant.POS - 1  # 0-based
        if chrom not in changes:
            changes[chrom] = {}
        changes[chrom][pos] = variant.ALT[0]

# Apply changes
for chrom, positions in changes.items():
    seq = list(ref_dict[chrom])
    for pos, alt in positions.items():
        seq[pos] = alt
    ref_dict[chrom] = ''.join(seq)

# Write output
with open('consensus.fa', 'w') as f:
    for chrom, seq in ref_dict.items():
        f.write(f'>{chrom}\n{seq}\n')

Note: Use bcftools consensus for production - handles indels and edge cases properly.

Quick Reference

Task Command
Basic consensus bcftools consensus -f ref.fa in.vcf.gz
Specific sample bcftools consensus -f ref.fa -s sample in.vcf.gz
Haplotype 1 bcftools consensus -f ref.fa -H 1 in.vcf.gz
IUPAC codes bcftools consensus -f ref.fa -I in.vcf.gz
With mask bcftools consensus -f ref.fa -m mask.bed in.vcf.gz
Generate chain bcftools consensus -f ref.fa -c chain.txt in.vcf.gz
Specific region bcftools consensus -f ref.fa -r chr1:1-1000 in.vcf.gz

Common Errors

Error Cause Solution
not indexed VCF not indexed Run bcftools index
sequence not found Chromosome mismatch Check chromosome names
overlapping records Variants overlap Usually OK, check warnings
REF does not match Wrong reference Use same reference as caller

Related Skills

  • variant-calling - Generate VCF for consensus
  • filtering-best-practices - Filter variants before consensus
  • variant-normalization - Normalize indels first
  • alignment-files/reference-operations - Reference manipulation

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