bio-metagenomics-kraken
Taxonomic classification of metagenomic reads using Kraken2. Fast k-mer based classification against RefSeq database. Use when performing initial taxonomic classification of shotgun metagenomic reads before abundance estimation with Bracken.
npx skills add majiayu000/claude-skill-registry --skill kraken-classification-gptomics-bioskills --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.
# Kraken2 Classification ## Basic Classification ```bash # Classify reads against standard database kraken2 --db /path/to/kraken2_db \ --output output.kraken \ --report report.txt \ reads.fastq.gz ``` ## Paired-End Reads ```bash kraken2 --db /path/to/kraken2_db \ --paired \ --output output.kraken \ --report report.txt \ reads_R1.fastq.gz reads_R2.fastq.gz ``` ## Common Options ```bash kraken2 --db /path/to/kraken2_db \ --threads 8 \ # CPU threads --confidence 0.1 \ # Confidence threshold --minimum-base-quality 20 \ # Quality filter --output output.kraken \ --report report.txt \ --use-names \ # Add taxon names to output --gzip-compressed \ # Input is gzipped reads.fastq.gz ``` ## Memory-Efficient Mode ```bash # For systems with limited RAM kraken2 --db /path/to/kraken2_db \ --memory-mapping \ # Use disk-based database --output output.kraken \ --report report.txt \ reads.fastq.gz ``` ## Report Only (No Per-Read Output) ```bash # Save space by not writing per-read classifications kraken2 --db /path/to/kraken2_db \ --report report.txt \ --report-zero-counts \ # Include taxa with 0 counts reads.fastq.gz ``` ## Classified/Unclassified Output ```bash # Separate classified and unclassified
- Basic Classification
- Paired-End Reads
- Common Options
- Memory-Efficient Mode
- Report Only (No Per-Read Output)
- Classified/Unclassified Output
- Build Custom Database
- Add Custom Sequences
- Inspect Database
- Report Format
- Parse Kraken Output in Python
- Filter Report by Rank
- Key Parameters
- Database Libraries
Classify reads against standard database kraken2 --db /path/to/kraken2_db \ reads.fastq.gz reads_R1.fastq.gz reads_R2.fastq.gz For systems with limited RAM Save space by not writing per-read classifications Separate classified and unclassified reads Download taxonomy kraken2-build --download-taxonomy --db custom_db Download specific libraries
What does the bio-metagenomics-kraken skill do?
Taxonomic classification of metagenomic reads using Kraken2. Fast k-mer based classification against RefSeq database. Use when performing initial taxonomic classification of shotgun metagenomic reads before abundance estimation with Bracken.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill kraken-classification-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.