bio-workflows-longread-sv-pipeline

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"}]

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/.filtered.vcf.gz


bcftools stats /sv/.filtered.vcf.gz > /sv/stats.txt

 
 

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