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---

name: bio-workflows-longread-sv-pipeline description: 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. tool_type: cli primary_tool: Sniffles workflow: true depends_on:

• long-read-sequencing/long-read-alignment
• long-read-sequencing/long-read-qc
• long-read-sequencing/structural-variants qc_checkpoints:
• after_qc: "Read N50 >10kb, quality score >Q10"
• after_alignment: "Mapping rate >90%, coverage sufficient"
• after_calling: "SV count reasonable, genotypes concordant" measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:
• read_file
• run_shell_command

---

Long-Read SV Pipeline

Complete workflow for detecting structural variants from ONT or PacBio long-read data.

Workflow Overview

Long reads (ONT/PacBio)
    |
    v
[1. QC] ----------------> NanoPlot
    |
    v
[2. Alignment] ---------> minimap2
    |
    v
[3. SV Calling] --------> Sniffles / cuteSV
    |
    v
[4. Filtering] ---------> bcftools
    |
    v
[5. Annotation] --------> AnnotSV (optional)
    |
    v
Filtered SV VCF

Primary Path: minimap2 + Sniffles

Step 1: Quality Control

# 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

# 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

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

# 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

# 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

# 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)

# AnnotSV for gene/clinical annotations
AnnotSV -SVinputFile svs.filtered.vcf.gz \
    -outputFile annotated_svs \
    -genomeBuild GRCh38

Multi-Sample SV Calling

# 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

#!/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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