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bio-longread-structural-variants

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Detect structural variants from long-read alignments using Sniffles, cuteSV, and SVIM. Use when detecting deletions, insertions, inversions, translocations, or complex rearrangements from ONT or PacBio data, especially those missed by short-read methods.

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Version Compatibility

Reference examples tested with: bcftools 1.19+

Before using code patterns, verify installed versions match. If versions differ:

  • CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Structural Variant Detection

"Call structural variants from my long reads" → Detect large deletions, insertions, inversions, duplications, and translocations with precise breakpoint resolution from ONT or PacBio alignments.

  • CLI: sniffles --input aligned.bam --vcf svs.vcf, cuteSV aligned.bam ref.fa svs.vcf output/

Sniffles2 - Basic SV Calling

# Call SVs from aligned BAM
sniffles --input aligned.bam \
    --vcf structural_variants.vcf \
    --reference reference.fa \
    --threads 4

Sniffles2 - Common Options

sniffles --input aligned.bam \
    --vcf structural_variants.vcf \
    --reference reference.fa \
    --threads 8 \
    --minsupport 3 \               # Min supporting reads
    --minsvlen 50 \                # Min SV length
    --mapq 20 \                    # Min mapping quality
    --output-rnames \              # Include read names
    --mosaic                       # Detect mosaic SVs

Sniffles2 - Population Calling

Goal: Jointly call and genotype structural variants across a cohort of long-read samples for population-level SV analysis.

Approach: Generate per-sample SNF signature files from individual BAMs, then merge and jointly genotype all samples in a single Sniffles2 call.

# Step 1: Call SVs per sample with SNF output
sniffles --input sample1.bam --snf sample1.snf --reference reference.fa
sniffles --input sample2.bam --snf sample2.snf --reference reference.fa

# Step 2: Merge and genotype
sniffles --input sample1.snf sample2.snf \
    --vcf population_svs.vcf \
    --reference reference.fa

cuteSV - Alternative Caller

# cuteSV SV calling
cuteSV aligned.bam reference.fa output.vcf work_dir/ \
    --threads 8 \
    --min_support 3 \
    --min_size 50 \
    --genotype

cuteSV - ONT Optimized

# Settings optimized for ONT
cuteSV aligned.bam reference.fa output.vcf work_dir/ \
    --threads 8 \
    --max_cluster_bias_INS 100 \
    --diff_ratio_merging_INS 0.3 \
    --max_cluster_bias_DEL 100 \
    --diff_ratio_merging_DEL 0.3 \
    --genotype

cuteSV - PacBio HiFi Optimized

# Settings optimized for HiFi
cuteSV aligned.bam reference.fa output.vcf work_dir/ \
    --threads 8 \
    --max_cluster_bias_INS 1000 \
    --diff_ratio_merging_INS 0.9 \
    --max_cluster_bias_DEL 1000 \
    --diff_ratio_merging_DEL 0.5 \
    --genotype

SVIM - Another Alternative

# SVIM for ONT data
svim alignment output_dir/ aligned.bam reference.fa \
    --insertion_sequences \
    --read_names \
    --sample sample_name

pbsv - PacBio Specific

# Discover signatures
pbsv discover aligned.bam signatures.svsig.gz

# Call SVs
pbsv call reference.fa signatures.svsig.gz structural_variants.vcf

Filter SV Calls

# Filter by quality and size
bcftools filter -i 'QUAL>=20 && ABS(SVLEN)>=50' svs.vcf > svs.filtered.vcf

# Keep only PASS
bcftools view -f PASS svs.vcf > svs.pass.vcf

# Filter specific SV types
bcftools view -i 'SVTYPE="DEL"' svs.vcf > deletions.vcf
bcftools view -i 'SVTYPE="INS"' svs.vcf > insertions.vcf

Merge Multiple Callers

# Use SURVIVOR to merge SV callsets
SURVIVOR merge sample_files.txt 1000 2 1 1 0 50 merged_svs.vcf

# sample_files.txt contains VCF paths, one per line
# Parameters: max_distance, min_callers, type_agree, strand_agree, est_distance, min_size

Annotate SVs

# Annotate with AnnotSV
AnnotSV -SVinputFile svs.vcf \
    -genomeBuild GRCh38 \
    -outputFile annotated_svs

# Or with bcftools
bcftools annotate -a gnomad_sv.vcf.gz -c INFO svs.vcf > svs.annotated.vcf

SV Types

TypeCodeDescription
DeletionDELSequence removed
InsertionINSSequence added
InversionINVSequence inverted
DuplicationDUPSequence duplicated
TranslocationBNDBreakend (complex)

Key Parameters - Sniffles2

ParameterDefaultDescription
--minsupportautoMin supporting reads
--minsvlen50Min SV length
--mapq20Min mapping quality
--referencenoneReference (for INS sequences)
--tandem-repeatsnoneBED of tandem repeats
--mosaicoffDetect mosaic SVs

Key Parameters - cuteSV

ParameterDefaultDescription
--min_support10Min supporting reads
--min_size30Min SV length
--max_size100000Max SV length
--genotypeoffOutput genotypes
--report_readidoffReport read IDs

Coverage Guidelines

CoverageSV Detection
5-10xLarge SVs (>1kb)
10-20xMost SVs
20-30xHigh confidence
>30xMosaic/rare SVs

Related Skills

  • long-read-alignment - Generate input BAM
  • medaka-polishing - Polish assembly with SVs
  • variant-calling/structural-variant-calling - Short-read SV comparison