genomics-sv-detection
Analyze and classify structural variants from VCF data for bioinformatics workflows.
Install
mkdir -p .claude/skills/genomics-sv-detection && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/11238" && unzip -o skill.zip -d .claude/skills/genomics-sv-detection && rm skill.zipInstalls to .claude/skills/genomics-sv-detection
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Load when summarising structural variants from an SV VCF (DEL / DUP / INV / TRA) — BND-notation parsing, size classification, per-type counts. Skip when working with small SNVs / indels (use `genomics-variant-calling`) or calling SVs from BAM (run Manta / Delly / Sniffles first).Key capabilities
- →Parses SV-flavored VCF files
- →Classifies structural variants by size
- →Generates per-type counts for DEL/DUP/INV/TRA
- →Resolves BND notation
- →Produces summary CSV and Markdown reports
How it works
The tool reads INFO/SVTYPE fields from a VCF, calculates absolute SVLEN for size binning, and aggregates counts into a structured report.
Inputs & outputs
When to use genomics-sv-detection
- →Generate summary table of structural variants
- →Classify SVs by size and type
- →Parse BND notation from VCF outputs
About this skill
genomics-sv-detection
When to use
The user has an SV VCF (from Manta, Delly, Lumpy, Sniffles, etc.) and wants per-type counts (DEL / DUP / INV / TRA / INS), size classification (small 50 bp–1 kb / medium 1 kb–100 kb / large 100 kb–10 Mb / very-large > 10 Mb), and BND breakend resolution.
The script does NOT call SVs from a BAM. Run an external SV caller first; this skill summarises its VCF output.
Inputs & Outputs
<!-- AUTO-GENERATED from skill.yaml (interface) — do not edit by hand. Regenerate: python scripts/generate_skill_md.py <skill_dir> -->Inputs
- File types:
.vcf
Outputs
tables/structural_variants.csvreport.mdresult.json
Flow
- Load VCF (
--input <sv.vcf>) or generate a demo SV VCF atoutput_dir/demo_structural_variants.vcfwith--n-svsrecords (sv_detection.py:170). - Parse records; read
INFO/SVTYPE(sv_detection.py:103). Records withoutINFO/SVTYPE(e.g. pure BNDALTnotation from Manta) classify asUNKNOWN— there is NO BND-to-TRA resolution. - Compute
abs(SVLEN)for size classification (sv_detection.py:105); bin into size classes; aggregate per-type counts. - Write
tables/structural_variants.csv(sv_detection.py:343) +report.md+result.json(:346).
Gotchas
- No SV caller is invoked. This skill ingests an SV VCF — it does NOT run Manta / Delly / Lumpy / Sniffles. To CALL SVs, run an external pipeline first.
--inputREQUIRED unless--demo.sv_detection.py:330raisesValueError("--input required when not using --demo"); non-existent paths raiseFileNotFoundErrorat:333.--n-svsonly affects--demo(sv_detection.py:319, default 100). Silently ignored when--inputis set.- Pure BND records without
INFO/SVTYPEclassify asUNKNOWN.sv_detection.py:103reads onlyINFO/SVTYPE; there is no BNDALT-notation parser and noMATEIDpairing logic. Manta callsets that emit translocations as paired BND records (without anSVTYPE=TRAINFO field) will appear as UNKNOWN, not TRA. Pre-process withbcftools view -i 'INFO/SVTYPE!=""'or with a Manta-specific BND→TRA resolver upstream. SVLENis stored as absolute value in the CSV.sv_detection.py:105writesabs(int(info.get("SVLEN", end - pos)))— a 1234-bp deletion becomes1234in the CSV regardless of the input sign. The original signedSVLENis NOT preserved.- Demo VCF mixes DEL / DUP / INV / TRA at fixed proportions. Useful for orchestrator smoke tests; not biologically meaningful.
Key CLI
# Demo (100 synthetic SVs)
python omicsclaw.py run genomics-sv-detection --demo --output /tmp/sv_demo
# Custom demo size
python omicsclaw.py run genomics-sv-detection --demo --n-svs 500 \
--output /tmp/sv_demo_large
# Real SV VCF
python omicsclaw.py run genomics-sv-detection \
--input manta_diploid.vcf --output results/
See also
references/parameters.md— every CLI flagreferences/methodology.md— SVTYPE / BND semantics, size-class boundariesreferences/output_contract.md—tables/structural_variants.csvschema- Adjacent skills:
genomics-alignment(upstream — provides BAMs for SV callers),genomics-variant-calling(parallel — small SNVs / indels),genomics-cnv-calling(parallel — copy-number from depth, complementary to SV callers),genomics-variant-annotation(downstream — functional impact of breakpoints)
When not to use it
- →Calling SVs from BAM files
- →Processing small SNVs or indels
- →Resolving complex BND-to-TRA pairings without upstream processing
Prerequisites
Limitations
- →Does not call SVs from BAMs
- →Pure BND records without SVTYPE classify as UNKNOWN
- →SVLEN is stored as absolute value
How it compares
It focuses specifically on summarizing existing SV callsets rather than performing the computationally intensive task of calling variants from raw alignments.
Compared to similar skills
genomics-sv-detection side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| genomics-sv-detection (this skill) | 0 | 3mo | Review | Intermediate |
| llm-evaluation | 6 | 2mo | No flags | Advanced |
| evaluating-llms-harness | 3 | 7mo | Review | Advanced |
| qutip | 4 | 7mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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