Agent skill

bio-microbiome-taxonomy-assignment

Taxonomic classification of ASVs using reference databases like SILVA, GTDB, or UNITE. Covers naive Bayes classifiers (DADA2, IDTAXA) and exact matching approaches. Use when assigning taxonomy to ASVs after DADA2 amplicon processing.

majiayu000534★ · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill taxonomy-assignment-gptomics-bioskills-2407c71a --agent claude-code

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

Facts
Files in the skill folder: 2
SKILL.md size: 4 KB
Bundled scripts: none
Path: skills/analysis/taxonomy-assignment-gptomics-bioskills-2407c71a/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

# Taxonomy Assignment ## DADA2 Naive Bayes Classifier ```r library(dada2) seqtab_nochim <- readRDS('seqtab_nochim.rds') # SILVA for 16S (download from https://zenodo.org/record/4587955) taxa <- assignTaxonomy(seqtab_nochim, 'silva_nr99_v138.1_train_set.fa.gz', multithread = TRUE) # Add species-level (exact matching) taxa <- addSpecies(taxa, 'silva_species_assignment_v138.1.fa.gz') # Check results head(taxa) ``` ## GTDB for 16S ```r # GTDB-formatted database (better for environmental samples) taxa_gtdb <- assignTaxonomy(seqtab_nochim, 'GTDB_bac120_arc53_ssu_r220_fullTaxo.fa.gz', multithread = TRUE) ``` ## UNITE for ITS (Fungi) ```r # UNITE database for fungal ITS taxa_its <- assignTaxonomy(seqtab_nochim, 'sh_general_release_dynamic_25.07.2023.fasta', multithread = TRUE) ``` ## QIIME2 Feature Classifier ```bash # Train classifier (one-time) qiime feature-classifier fit-classifier-naive-bayes \ --i-reference-reads silva-138-99-seqs.qza \ --i-reference-taxonomy silva-138-99-tax.qza \ --o-classifier silva-138-99-nb-classifier.qza # Classify ASVs qiime feature-classifier classify-sklearn \ --i-classifier silva-138-99-nb-classifier.qza \ --i-reads rep-seqs.qza \ --o-classification taxonom

What's inside
Steps it walks through
  1. DADA2 Naive Bayes Classifier
  2. GTDB for 16S
  3. UNITE for ITS (Fungi)
  4. QIIME2 Feature Classifier
  5. VSEARCH Exact Matching
  6. RDP Classifier
  7. IDTAXA (DECIPHER) - Often More Accurate
  8. Confidence Filtering
  9. Combine into phyloseq
  10. Database Comparison
  11. Related Skills
Ships with 1 file
  • metadata.json
Commands it runs
Train classifier (one-time)
qiime feature-classifier fit-classifier-naive-bayes \
Classify ASVs
qiime feature-classifier classify-sklearn \
Faster but requires exact or near-exact matches
vsearch --usearch_global asv_seqs.fasta \
More from claude-skill-registry
All skills →
About this skill
What does the bio-microbiome-taxonomy-assignment skill do?

Taxonomic classification of ASVs using reference databases like SILVA, GTDB, or UNITE. Covers naive Bayes classifiers (DADA2, IDTAXA) and exact matching approaches. Use when assigning taxonomy to ASVs after DADA2 amplicon processing.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill taxonomy-assignment-gptomics-bioskills-2407c71a --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.

Keep going