Detects structural variants (deletions, insertions, inversions, duplications, translocations) from Oxford Nanopore and PacBio long-read alignments with Sniffles2, cuteSV, SVIM, and assembly-based callers, joint-genotypes cohorts via the Sniffles2 .snf workflow, and benchmarks with Truvari against GIAB. Covers why an SV call is a representation artifact (the tandem-repeat BED, aligner, and Truvari params set precision/recall as much as the caller), the cuteSV per-platform parameter trap, soft-clipped supplementary alignments as the SV substrate, and the somatic/mosaic boundary to Severus/nanomonsv. Use when calling germline or somatic SVs from ONT/HiFi reads, joint-genotyping a cohort, choosing or tuning an SV caller, or benchmarking SV calls.
Detects structural variants (deletions, insertions, inversions, duplications, translocations) from Oxford Nanopore and PacBio long-read alignments with Sniffles2, cuteSV, SVIM, and assembly-based callers, joint-genotypes cohorts via the Sniffles2 .snf workflow, and benchmarks with Truvari against GIAB. Covers why an SV call is a representation artifact (the tandem-repeat BED, aligner, and Truvari params set precision/recall as much as the caller), the cuteSV per-platform parameter trap, soft-clipped supplementary alignments as the SV substrate, and the somatic/mosaic boundary to Severus/nanomonsv. Use when calling germline or somatic SVs from ONT/HiFi reads, joint-genotyping a cohort, choosing or tuning an SV caller, or benchmarking SV calls.
Before using code patterns, verify installed versions match. If versions differ:
CLI: <tool> --version then to confirm flags
<tool> --help
Results depend on inputs that outlive the binary version - record them:
The reference-matched tandem-repeat BED supplied to the caller (Sniffles --tandem-repeats) drives the FP rate in repeats more than any other setting. Record which TR BED was used.
Benchmark numbers depend on the region set + TR handling + Truvari params; record all three.
cuteSV parameters are platform-specific (ONT vs HiFi vs CLR); the defaults are not platform-appropriate.
If code throws an error, introspect the installed tool (sniffles --help, cuteSV --help) and adapt the example to the actual API rather than retrying.
Long-Read Structural Variants
"Find structural variants in my long reads" -> Map with the SV-ready preset (soft-clipped supplementaries), call with a TR-aware caller, and benchmark stating the region set and Truvari params.
Long reads are the killer app for SVs: a single read spans the breakpoint (within-read CIGAR or split alignment) and resolves repeats short reads cannot. By convention SV = >=50 bp; the 30-100 bp range is a VNTR-dominated gray zone where callers disagree most.
The Single Most Important Modern Insight -- An SV Call Is a Representation Artifact as Much as a Biological Fact
In tandem repeats and segmental duplications, the same biological event has many valid VCF encodings - a deletion can be written as the reciprocal insertion on the other allele, and a VNTR expansion's breakpoints slide freely across repeat units. Consequently:
The tandem-repeat BED, the aligner, and the Truvari parameters decide precision/recall as much as the caller does. A claim like "caller X has F1 0.95" is meaningless without also stating the region set, the TR BED supplied to the caller, and the Truvari params - change any one and the number moves more than the gap between callers.
Without a TR BED, one event fragments into several false-positive calls with inconsistent breakpoints. --tandem-repeats makes clustering repeat-aware (widening the merge window inside annotated TRs) - the single biggest FP-reduction lever, not a nicety.
truvari refine exists precisely to re-harmonize representations within TR regions; benchmarking TR-dense regions without it systematically understates recall.
Caller Taxonomy
Tool
Regime
Best for
Citation
Sniffles2
germline + population + mosaic
the default germline workhorse; cohort joint genotyping; .snf merge
Smolka 2024 Nat Biotechnol 42:1571
cuteSV
germline
high sensitivity, speed; per-platform tuning required
Jiang 2020 Genome Biol 21:189
SVIM
germline
scores (not hard-filters) SVs; good INS detection
Heller 2019 Bioinformatics 35:2907
pbsv
germline (PacBio)
two-step discover->call; official PacBio tool
PacBio (no journal paper)
NanoVar
germline, low-depth
4-8x ONT clinical
Tham 2020 Genome Biol 21:56
dipcall / SVIM-asm / PAV
assembly-based germline
most accurate single sample with phased HiFi; truth-set generation
Li 2018; Heller 2021; Ebert 2021
Severus
somatic (tumor-normal)
cancer T/N, complex/subclonal
Keskus 2026 Nat Biotechnol
nanomonsv
somatic (tumor-normal)
precise somatic breakpoints, MEI
Shiraishi 2023 NAR 51:e74
SVision-pro
de novo + somatic, complex
resolving nested CSVs
Wang 2025 Nat Biotechnol 43:181
Decision Tree by Scenario
Scenario
Recommended
Why
Single ONT/HiFi germline sample
Sniffles2 + --tandem-repeats
TR-aware, auto support, fast
Cohort germline
Sniffles2 per-sample .snf -> merge
re-genotypes from raw signal; true joint genotypes
paired callers; Sniffles --mosaic is single-sample only
Low-VAF mosaic in one sample
Sniffles2 --mosaic
lowers support, reports VAF (not a T/N caller)
Low coverage (4-8x)
NanoVar
designed for low-depth clinical
Benchmarking
Truvari (+refine) vs GIAB Tier1/CMRG
the field standard; state region + params
Alignment for SV Calling
Map with minimap2 (the modern default; NGMLR is a higher-precision/slower legacy niche for Sniffles). Use the platform preset and keep soft-clipped supplementary alignments - split-read callers reconstruct breakpoints from the clipped sequence on those records.
minimap2 -ax map-ont --MD -Y ref.fa ont.fq.gz | samtools sort -o aln.bam && samtools index aln.bam
# -Y keeps SEQ on supplementaries (the SV substrate); --MD for cuteSV; map-hifi/map-pb for PacBio
Sniffles2 - germline and the .snf population workflow
# Single sample (always supply --reference for INS sequence and --tandem-repeats for repeats)
sniffles --input aln.bam --vcf svs.vcf --reference ref.fa --tandem-repeats human_GRCh38_TR.bed
# Cohort: per-sample .snf signature index, then merge + joint-genotype
sniffles --input s1.bam --snf s1.snf --reference ref.fa --tandem-repeats TR.bed
sniffles --input s2.bam --snf s2.snf --reference ref.fa --tandem-repeats TR.bed
sniffles --input s1.snf s2.snf --vcf cohort.vcf --reference ref.fa
# Force-call / regenotype a known SV set in a new sample
sniffles --input new.bam --genotype-vcf known_svs.vcf --vcf genotyped.vcf
# Single-sample low-VAF / mosaic (NOT a tumor-normal caller)
sniffles --input tumor.bam --vcf mosaic.vcf --mosaic
The .snf is a binary signature index (NOT a VCF - never bcftools it); it retains sub-threshold signatures so the merge re-genotypes an SV even in a sample that did not independently pass support.
cuteSV - the per-platform parameter trap
cuteSV's defaults are not platform-appropriate; the README gives distinct sets by error rate. --genotype is OFF by default. Positional args: cuteSV <bam> <ref> <out.vcf> <work_dir>. Force-calling moved to the separate cuteFC tool.
--pctseq (default 0.7) compares the actual inserted/deleted sequence, not just coordinates - set 0 for depth-based callers lacking alt sequence, keep 0.7 for long-read callers. Region set dominates the headline: Tier1 (resolvable INS/DEL >=50 bp) overstates whole-genome performance; CMRG reflects hard clinical loci. Tier1 v0.6 is INS/DEL only - do not report INV recall against it.
Per-Method Failure Modes
One VNTR fragments into many false positives
Trigger: calling in tandem repeats without a TR BED. Mechanism: the breakpoint slides across repeat units, scattering signatures. Symptom: several calls with inconsistent breakpoints where one event exists. Fix: supply --tandem-repeats to the caller; truvari refine when benchmarking.
cuteSV defaults inflate or fragment calls
Trigger: running cuteSV with one parameter set across platforms. Mechanism: HiFi settings over-merge ONT noise; ONT settings fragment clean HiFi signatures. Symptom: FP inflation or split calls. Fix: use the platform-matched set; remember --genotype is off by default.
Missing insertion sequence / breakpoints
Trigger: Sniffles without --reference, or alignment without -Y. Mechanism: no reference -> no ALT sequence; hard-clipped supplementaries -> lost breakpoint sequence. Symptom: INS lack sequence; imprecise breakpoints. Fix: add --reference and align with -Y.
Treating Sniffles --mosaic as a cancer caller
Trigger: somatic SV calling with single-sample --mosaic. Mechanism: mosaic mode lowers support in one sample; it has no normal to subtract. Symptom: germline SVs reported as somatic; FP at low VAF. Fix: Severus or nanomonsv (paired tumor-normal).
Comparing F1 across studies that handled repeats differently
Trigger: quoting F1 without region + TR BED + Truvari params. Mechanism: representation handling moves the number more than the caller. Symptom: apples-to-oranges comparisons. Fix: fix the region set, TR BED, and Truvari params; run truvari refine.
Quantitative Thresholds
Threshold
Source
Rationale
SV >= 50 bp
GIAB convention
30-100 bp is a VNTR gray zone where callers disagree
Sniffles --minsvlen 35, --mapq 25, --minsupport auto
Sniffles2 manpage
the actual defaults (support is coverage-derived, not a fixed 3)
Coverage ~20-30x germline; >30-60x mosaic/somatic
SV practice
large SVs callable from 5-10x; low-VAF needs depth
Truvari --pctseq 0.7, --refdist 500
English 2022
sequence-aware INS matching; loosen refdist to 1000 only for fuzzy callers
cuteSV params per platform
cuteSV README
error rate sets cluster bias / merge ratio
Common Errors
Error / symptom
Cause
Solution
Many FP calls in repeats
no TR BED
supply --tandem-repeats
cuteSV VCF has no GT
--genotype off by default
add --genotype
Cannot bcftools the .snf
.snf is a binary signature index
use it as Sniffles input, not a VCF
INS records lack sequence
--reference not supplied
add --reference ref.fa
Imprecise/missing breakpoints
supplementaries hard-clipped
align with minimap2 -Y
Looking for cuteSV force-calling flag
moved to cuteFC
use the cuteFC tool
Somatic SVs from a single sample
germline/mosaic caller
Severus / nanomonsv (paired)
References
Smolka M, Paulin LF, Grochowski CM, et al. 2024. Detection of mosaic and population-level structural variants with Sniffles2. Nat Biotechnol 42:1571-1580.
Jiang T, Liu Y, Jiang Y, et al. 2020. Long-read-based human genomic structural variation detection with cuteSV. Genome Biol 21:189.
Heller D, Vingron M. 2019. SVIM: structural variant identification using mapped long reads. Bioinformatics 35:2907-2915.
Keskus AG, Bryant A, Ahmad T, et al. 2026. Severus detects somatic structural variation and complex rearrangements in cancer genomes using long-read sequencing. Nat Biotechnol 44:247-257.
