Agent skill · Testing & QA

bio-longread-alignment

Align long reads using minimap2 for Oxford Nanopore and PacBio data. Supports various presets for different read types and applications. Use when aligning ONT or PacBio reads to a reference genome for variant calling, SV detection, or coverage analysis.

FreedomIntelligencegithub.com/FreedomIntelligenceGitHub ↗
claude-codeships scripts
Install
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-longread-alignment --agent claude-code

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

Facts
Files in the skill folder: 3
SKILL.md size: 5 KB
Bundled scripts: yes
Path: skills/bio-longread-alignment/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,909
Language: Python
Read our review of the source →

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

From the SKILL.md

## Version Compatibility Reference examples tested with: minimap2 2.26+, samtools 1.19+ Before using code patterns, verify installed versions match. If versions differ: - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Long-Read Alignment with minimap2 **"Align my long reads to the reference"** → Map ONT or PacBio reads using minimap2 with technology-specific presets for optimal sensitivity and accuracy. - CLI: `minimap2 -ax map-ont ref.fa reads.fq | samtools sort -o aligned.bam` (ONT), `minimap2 -ax map-hifi` (PacBio HiFi) ## Oxford Nanopore Alignment ```bash # Basic ONT alignment minimap2 -ax map-ont reference.fa reads.fastq.gz | \ samtools sort -o aligned.bam samtools index aligned.bam ``` ## PacBio HiFi Alignment ```bash # PacBio HiFi reads (high accuracy) minimap2 -ax map-hifi reference.fa reads.fastq.gz | \ samtools sort -o aligned.bam samtools index aligned.bam ``` ## PacBio CLR Alignment ```bash # PacBio CLR (continuous long reads, lower accuracy) minimap2 -ax map-pb reference.fa reads.fastq.gz | \ sam

What's inside
Steps it walks through
  1. Version Compatibility
  2. Oxford Nanopore Alignment
  3. PacBio HiFi Alignment
  4. PacBio CLR Alignment
  5. Pre-Build Index for Multiple Runs
  6. Common Options
  7. Splice-Aware Alignment (RNA)
  8. With Junction BED (Known Splice Sites)
  9. Assembly to Reference Alignment
  10. Output PAF (Faster, No BAM)
  11. Keep Secondary and Supplementary
  12. Filter Alignments
  13. Multiple FASTQ Files
  14. Output Statistics
Ships with 2 files
  • examples/minimap2_align.sh
  • usage-guide.md
Commands it runs
Basic ONT alignment
minimap2 -ax map-ont reference.fa reads.fastq.gz | \
samtools sort -o aligned.bam
samtools index aligned.bam
PacBio HiFi reads (high accuracy)
minimap2 -ax map-hifi reference.fa reads.fastq.gz | \
PacBio CLR (continuous long reads, lower accuracy)
minimap2 -ax map-pb reference.fa reads.fastq.gz | \
Build index once
minimap2 -d reference.mmi reference.fa
More from OpenClaw-Medical-Skills
All skills →
About this skill
What does the bio-longread-alignment skill do?

Align long reads using minimap2 for Oxford Nanopore and PacBio data. Supports various presets for different read types and applications. Use when aligning ONT or PacBio reads to a reference genome for variant calling, SV detection, or coverage analysis.

How do I install it?

Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-longread-alignment --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 FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 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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