Agent skill · Data & Analytics

bio-workflows-longread-sv-pipeline

End-to-end workflow for detecting structural variants from long-read sequencing data. Covers ONT/PacBio alignment with minimap2 and SV calling with Sniffles or cuteSV. Use when detecting structural variants from long reads.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill longread-sv-pipeline-gptomics-bioskills --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 6 KB
Bundled scripts: none
Path: skills/analysis/longread-sv-pipeline-gptomics-bioskills/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Long-Read SV Pipeline Complete workflow for detecting structural variants from ONT or PacBio long-read data. ## Workflow Overview ``` Long reads (ONT/PacBio) | v [1. QC] ----------------> NanoPlot | v [2. Alignment] ---------> minimap2 | v [3. SV Calling] --------> Sniffles / cuteSV | v [4. Filtering] ---------> bcftools | v [5. Annotation] --------> AnnotSV (optional) | v Filtered SV VCF ``` ## Primary Path: minimap2 + Sniffles ### Step 1: Quality Control ```bash # ONT reads QC NanoPlot --fastq reads.fastq.gz \ --outdir nanoplot_output \ --threads 8 # Check key metrics # - Read N50 should be >10kb # - Mean quality >Q10 # - Total bases sufficient for coverage ``` ### Step 2: Alignment with minimap2 ```bash # ONT reads minimap2 -ax map-ont \ -t 16 \ --MD \ -Y \ reference.fa \ reads.fastq.gz | \ samtools sort -@ 4 -o aligned.bam samtools index aligned.bam # PacBio HiFi minimap2 -ax map-hifi \ -t 16 \ --MD \ -Y \ reference.fa \ reads.fastq.gz | \ samtools sort -@ 4 -o aligned.bam # PacBio CLR minimap2 -ax map-pb \ -t 16 \ --MD \ -Y \ reference.fa \ reads.fastq.gz | \ samtools sort -@ 4 -o aligned.bam ``` **QC Checkpoint:** Check alignment stats ```bash samtools flagstat aligned.bam

What's inside
Steps it walks through
  1. Workflow Overview
  2. Primary Path: minimap2 + Sniffles
  3. Step 1: Quality Control
  4. Step 2: Alignment with minimap2
  5. Step 3: SV Calling with Sniffles
  6. Alternative: cuteSV
  7. Step 4: Filtering
  8. Step 5: Annotation (Optional)
  9. Multi-Sample SV Calling
  10. Parameter Recommendations
  11. SV Types Detected
  12. Troubleshooting
  13. Complete Pipeline Script
  14. Related Skills
Ships with 1 file
  • metadata.json
Commands it runs
ONT reads QC
NanoPlot --fastq reads.fastq.gz \
Check key metrics
ONT reads
minimap2 -ax map-ont \
reference.fa \
reads.fastq.gz | \
samtools sort -@ 4 -o aligned.bam
samtools index aligned.bam
PacBio HiFi
More from claude-skill-registry
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About this skill
What does the bio-workflows-longread-sv-pipeline skill do?

End-to-end workflow for detecting structural variants from long-read sequencing data. Covers ONT/PacBio alignment with minimap2 and SV calling with Sniffles or cuteSV. Use when detecting structural variants from long reads.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill longread-sv-pipeline-gptomics-bioskills --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 majiayu000/claude-skill-registry, a repository with 534 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.

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