structural-variant-detector
Structural variant detection skill for identifying CNVs, inversions, translocations, and complex rearrangements
Profile →npx skills add a5c-ai/babysitter --skill structural-variant-detector --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Structural Variant Detector Skill ## Purpose Enable structural variant detection for identifying CNVs, inversions, translocations, and complex rearrangements. ## Capabilities - Split-read and paired-end SV calling - Copy number variation detection - Mobile element insertion detection - Complex SV resolution - SV annotation and visualization - Multi-caller integration ## Usage Guidelines - Use multiple callers for comprehensive detection - Integrate results from different algorithms - Validate SVs with independent methods - Annotate SVs with functional impact - Visualize SVs for manual review - Document caller combinations and filters ## Dependencies - Manta - DELLY - CNVkit - LUMPY - GRIDSS ## Process Integration - Whole Genome Sequencing Pipeline (wgs-analysis-pipeline) - Tumor Molecular Profiling (tumor-molecular-profiling) - Long-Read Sequencing Analysis (long-read-analysis)
- Purpose
- Capabilities
- Usage Guidelines
- Dependencies
- Process Integration
What does the structural-variant-detector skill do?
Structural variant detection skill for identifying CNVs, inversions, translocations, and complex rearrangements
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill structural-variant-detector --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.