Agent skill
bio-workflows-longread-sv-pipeline
End-to-end workflow for detecting structural variants from long-read sequencing data. Covers ONT/PacBio alignment with minimap2 and SV calling with Sniffles or cuteSV. Use when detecting structural variants from long reads.
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Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/longread-sv-pipeline
SKILL.md
Long-Read SV Pipeline
Complete workflow for detecting structural variants from ONT or PacBio long-read data.
Workflow Overview
Long reads (ONT/PacBio)
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[1. QC] ----------------> NanoPlot
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[2. Alignment] ---------> minimap2
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[3. SV Calling] --------> Sniffles / cuteSV
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[4. Filtering] ---------> bcftools
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[5. Annotation] --------> AnnotSV (optional)
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Filtered SV VCF
Primary Path: minimap2 + Sniffles
Step 1: Quality Control
bash
# ONT reads QC
NanoPlot --fastq reads.fastq.gz \
--outdir nanoplot_output \
--threads 8
# Check key metrics
# - Read N50 should be >10kb
# - Mean quality >Q10
# - Total bases sufficient for coverage
Step 2: Alignment with minimap2
bash
# ONT reads
minimap2 -ax map-ont \
-t 16 \
--MD \
-Y \
reference.fa \
reads.fastq.gz | \
samtools sort -@ 4 -o aligned.bam
samtools index aligned.bam
# PacBio HiFi
minimap2 -ax map-hifi \
-t 16 \
--MD \
-Y \
reference.fa \
reads.fastq.gz | \
samtools sort -@ 4 -o aligned.bam
# PacBio CLR
minimap2 -ax map-pb \
-t 16 \
--MD \
-Y \
reference.fa \
reads.fastq.gz | \
samtools sort -@ 4 -o aligned.bam
QC Checkpoint: Check alignment stats
bash
samtools flagstat aligned.bam
samtools depth -a aligned.bam | awk '{sum+=$3} END {print "Average coverage:",sum/NR}'
- Mapping rate >90%
- Average coverage >10x for SV calling (>20x preferred)
Step 3: SV Calling with Sniffles
bash
# Sniffles2 (recommended)
sniffles \
--input aligned.bam \
--vcf svs.vcf.gz \
--reference reference.fa \
--threads 8 \
--minsvlen 50
# With tandem repeat annotations (recommended)
sniffles \
--input aligned.bam \
--vcf svs.vcf.gz \
--reference reference.fa \
--tandem-repeats tandem_repeats.bed \
--threads 8
Alternative: cuteSV
bash
# cuteSV (faster, good for ONT)
cuteSV \
aligned.bam \
reference.fa \
svs.vcf \
work_dir/ \
--threads 8 \
--min_size 50 \
--genotype
bgzip svs.vcf
tabix svs.vcf.gz
Step 4: Filtering
bash
# Filter by quality and size
bcftools view -i 'QUAL>=20 && ABS(SVLEN)>=50' svs.vcf.gz -Oz -o svs.filtered.vcf.gz
# Filter by SV type
bcftools view -i 'SVTYPE="DEL" || SVTYPE="INS"' svs.filtered.vcf.gz -Oz -o del_ins.vcf.gz
# Filter by genotype
bcftools view -i 'GT="1/1" || GT="0/1"' svs.filtered.vcf.gz -Oz -o genotyped.vcf.gz
# Stats
bcftools stats svs.filtered.vcf.gz > sv_stats.txt
Step 5: Annotation (Optional)
bash
# AnnotSV for gene/clinical annotations
AnnotSV -SVinputFile svs.filtered.vcf.gz \
-outputFile annotated_svs \
-genomeBuild GRCh38
Multi-Sample SV Calling
bash
# Call SVs per sample
for sample in sample1 sample2 sample3; do
sniffles --input ${sample}.bam \
--snf ${sample}.snf \
--reference reference.fa
done
# Merge and joint genotype
sniffles --input sample1.snf sample2.snf sample3.snf \
--vcf merged_svs.vcf.gz \
--reference reference.fa
Parameter Recommendations
| Tool | Parameter | ONT | PacBio HiFi |
|---|---|---|---|
| minimap2 | -ax | map-ont | map-hifi |
| Sniffles | --minsvlen | 50 | 50 |
| Sniffles | --minsupport | auto | auto |
| cuteSV | --min_size | 50 | 50 |
| cuteSV | --min_support | 3 | 3 |
SV Types Detected
| Type | Abbreviation | Description |
|---|---|---|
| Deletion | DEL | Sequence removed |
| Insertion | INS | Sequence added |
| Duplication | DUP | Sequence copied |
| Inversion | INV | Sequence reversed |
| Translocation | BND | Breakend (interchromosomal) |
Troubleshooting
| Issue | Likely Cause | Solution |
|---|---|---|
| Few SVs | Low coverage | Increase sequencing depth |
| Many false positives | Low quality reads | Filter by QUAL, increase min support |
| Missing known SV | Repeat region | Use tandem repeat annotations |
| High breakend count | Mapping artifacts | Check alignment quality |
Complete Pipeline Script
bash
#!/bin/bash
set -e
THREADS=16
READS="reads.fastq.gz"
REF="reference.fa"
SAMPLE="sample1"
OUTDIR="sv_results"
mkdir -p ${OUTDIR}/{qc,aligned,sv}
# Step 1: QC
echo "=== QC ==="
NanoPlot --fastq ${READS} --outdir ${OUTDIR}/qc -t ${THREADS}
# Step 2: Alignment
echo "=== Alignment ==="
minimap2 -ax map-ont -t ${THREADS} --MD -Y ${REF} ${READS} | \
samtools sort -@ 4 -o ${OUTDIR}/aligned/${SAMPLE}.bam
samtools index ${OUTDIR}/aligned/${SAMPLE}.bam
echo "Alignment stats:"
samtools flagstat ${OUTDIR}/aligned/${SAMPLE}.bam
# Step 3: SV calling
echo "=== SV Calling ==="
sniffles --input ${OUTDIR}/aligned/${SAMPLE}.bam \
--vcf ${OUTDIR}/sv/${SAMPLE}.vcf.gz \
--reference ${REF} \
--threads ${THREADS}
# Step 4: Filter
echo "=== Filtering ==="
bcftools view -i 'QUAL>=20' ${OUTDIR}/sv/${SAMPLE}.vcf.gz \
-Oz -o ${OUTDIR}/sv/${SAMPLE}.filtered.vcf.gz
bcftools index ${OUTDIR}/sv/${SAMPLE}.filtered.vcf.gz
# Stats
bcftools stats ${OUTDIR}/sv/${SAMPLE}.filtered.vcf.gz > ${OUTDIR}/sv/stats.txt
echo "=== Complete ==="
echo "SVs: $(bcftools view -H ${OUTDIR}/sv/${SAMPLE}.filtered.vcf.gz | wc -l)"
Related Skills
- long-read-sequencing/long-read-alignment - minimap2 details
- long-read-sequencing/structural-variants - Sniffles, cuteSV options
- long-read-sequencing/long-read-qc - NanoPlot metrics
- variant-calling/structural-variant-calling - Short-read SV methods
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