Version Compatibility
Reference examples tested with: Sniffles 2.2+, cuteSV 2.1+, minimap2 2.28+, samtools 1.19+, truvari 4.0+.
Before using code patterns, verify installed versions match. If versions differ:
- CLI:
<tool> --version then <tool> --help to confirm flags
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.
- CLI:
sniffles --input aln.bam --vcf svs.vcf --reference ref.fa --tandem-repeats TR.bed
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 |
| Maximum sensitivity / speed |
cuteSV with the platform-matched param set |
per-platform tuning is mandatory |
| Phased HiFi, want best per-sample accuracy |
assembly-based (dipcall/SVIM-asm) -> hifi-assembly |
resolves the alt haplotype directly |
| Tumor-normal somatic SVs |
Severus or nanomonsv |
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.
| Platform |
--maxclusterbias_INS |
--diffratiomerging_INS |
--maxclusterbias_DEL |
--diffratiomerging_DEL |
| ONT |
100 |
0.3 |
100 |
0.3 |
| PacBio HiFi/CCS |
1000 |
0.9 |
1000 |
0.5 |
| PacBio CLR |
100 |
0.3 |
200 |
0.5 |
mkdir cutesv_work
cuteSV aln.bam ref.fa cutesv.vcf cutesv_work --genotype \
--max_cluster_bias_INS 100 --diff_ratio_merging_INS 0.3 \
--max_cluster_bias_DEL 100 --diff_ratio_merging_DEL 0.3 # ONT set
Benchmarking with Truvari
truvari bench --base giab_tier1.vcf.gz --comp calls.vcf.gz \
--includebed tier1_regions.bed --pctseq 0.7 --refdist 500 --passonly -o bench/
truvari refine bench/ # re-harmonize TR-region representations for a fair comparison
--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.
- English AC, Menon VK, Gibbs RA, Metcalf GA, Sedlazeck FJ. 2022. Truvari: refined structural variant comparison preserves allelic diversity. Genome Biol 23:271.
- Zook JM, Hansen NF, Olson ND, et al. 2020. A robust benchmark for detection of germline large deletions and insertions. Nat Biotechnol 38:1347-1355.
- Wagner J, Olson ND, Harris L, et al. 2022. Curated variation benchmarks for challenging medically relevant autosomal genes (CMRG). Nat Biotechnol 40:672-680.
- 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.
Related Skills
- long-read-alignment - SV-ready mapping (
-Y soft-clip, platform preset)
- basecalling - Read accuracy/length that gates breakpoint precision
- clair3-variants - Small variants (<50 bp) are Clair3's job, not an SV caller's
- haplotype-phasing - Haplotag the BAM for haplotype-specific / phased SVs
- genome-assembly/hifi-assembly - Phased assembly for assembly-based SV calling
- variant-calling/structural-variant-calling - The variant-calling-side SV view
- variant-calling/vcf-manipulation - Filter/merge the SV VCFs
- genome-intervals/gtf-gff-handling - Annotate SVs against gene models