scientific-microbiome-metagenomics

Analyze microbiome sequencing data for taxonomic profiles, diversity metrics, and functional pathways.

3|1|Updated Feb 11, 2026
One-click install
npx skills add https://github.com/nahisaho/satori --skill scientific-microbiome-metagenomics
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: scientific-microbiome-metagenomics
Source: https://github.com/nahisaho/satori/tree/main/src/.github/skills/scientific-microbiome-metagenomics
Command: npx skills add https://github.com/nahisaho/satori --skill scientific-microbiome-metagenomics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a standardized pipeline for microbiome analysis, enabling systematic handling of both 16S rRNA amplicon data and shotgun metagenomics to generate taxonomic profiles, diversity metrics, and functional pathways.

Core Features & Use Cases

  • 16S amplicon analysis: DADA2-based ASV inference and taxonomic assignment.
  • Shotgun metagenomics profiling: Taxonomic and functional profiling using MetaPhlAn and HUMAnN.
  • Diversity and differential abundance: Alpha/beta diversity metrics and differential abundance testing (DESeq2/ANCOM-BC).
  • Functional profiling & CoDA: Functional profiling and compositional data analysis for robust interpretation.
  • Use Case: A microbiome project comparing healthy vs diseased samples with integrated 16S and shotgun data to identify biomarkers and pathways.

Quick Start

Run the microbiome analysis workflow on 16S and shotgun data to generate ASV tables, taxonomic profiles, diversity metrics, differential abundance results, and functional pathways.

Frequently Asked Questions about scientific-microbiome-metagenomics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze 16S amplicon and shotgun metagenomics data in one pipeline?

Microbiome metagenomics analysis integrates DADA2 for 16S ASV inference and MetaPhlAn/HUMAnN for shotgun profiling, generating taxonomic profiles, diversity metrics, and functional pathways within a reproducible workflow.

What is the best way to perform differential abundance testing on microbiome sequencing data?

Differential abundance testing for microbiome data applies ANCOM-BC and DESeq2, utilizing compositional data analysis (CoDA) to identify significant biomarkers between sample groups robustly.

Can I use DADA2 and MetaPhlAn together for integrated microbiome profiling?

Yes, DADA2 handles 16S amplicon ASV inference and taxonomic assignment, while MetaPhlAn profiles shotgun metagenomics, allowing integrated analysis across both sequencing workflows.

How does functional profiling work with HUMAnN in shotgun metagenomics?

Functional profiling in shotgun metagenomics uses HUMAnN to identify metabolic pathways and functional abundance from sequencing data, enabling robust interpretation of microbiome functional potential.

Do I need compositional data analysis for robust metagenomics interpretation?

Compositional data analysis (CoDA) is required for robust metagenomics interpretation because it addresses the constrained nature of microbiome data, preventing false discoveries in differential abundance testing.