omicverse-microbiome-phylogeny

Name: omicverse-microbiome-phylogeny
Availability: InStock
Author: omicverse

Build phylogenetic trees and compute tree-aware diversity metrics from 16S amplicon data.

13|2|Updated Apr 5, 2026

Search Tags:#phylogeny #omicverse #anndata #microbiome #mafft #unifrac #fasttree

Ready to run

npx skills add https://github.com/omicverse/omicverse-skills --skill omicverse-microbiome-phylogeny

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: omicverse-microbiome-phylogeny
Source: https://github.com/omicverse/omicverse-skills/tree/main/src/omicverse_skills/skills/microbiome-phylogeny
Command: npx skills add https://github.com/omicverse/omicverse-skills --skill omicverse-microbiome-phylogeny

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

This Skill removes the manual friction of making 16S phylogenetic diversity analyses work end to end, from ASV sequences to tree-aware alpha and beta diversity metrics.

Core Features & Use Cases

Phylogenetic tree construction: Builds an ASV-level tree with MAFFT alignment and FastTree under a GTR plus gamma model.
Tree attachment and validation: Attaches the resulting tree to AnnData, validates tip names, and prunes mismatches when appropriate.
Phylogenetically-aware diversity: Computes Faith PD, unweighted UniFrac, and weighted UniFrac for microbiome cohort analysis.
Use Case: A microbiome researcher can turn a saved 16S AnnData and ASV FASTA into a tree-augmented dataset, compare UniFrac against Bray-Curtis, and save the result for downstream analysis.

Quick Start

Use this skill to build a FastTree GTR plus gamma phylogeny from your ASV FASTA, attach it to the AnnData object, and compute Faith PD together with unweighted and weighted UniFrac for comparison.

Frequently Asked Questions about omicverse-microbiome-phylogeny

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

FAQPage Schema

How do I build a phylogenetic tree from ASV sequences for UniFrac analysis?▼

To build a phylogenetic tree for UniFrac analysis, you construct an ASV-level tree using MAFFT alignment and FastTree under a GTR plus gamma model. This process creates the tree structure required to compute phylogenetically-aware beta diversity metrics.

How does attaching a phylogenetic tree to AnnData work for microbiome cohort comparison?▼

Attaching a phylogenetic tree to AnnData involves validating tree tip names against ASV features and pruning mismatches. The validated tree is stored in adata.uns and adata.obsp, enabling direct computation of cohort diversity metrics.

What phylogenetic diversity metrics can I compute from 16S amplicon data with an AnnData object?▼

You can compute Faith PD for alpha diversity, alongside unweighted UniFrac and weighted UniFrac for beta diversity, from 16S amplicon data. These metrics provide phylogenetically-aware insights into microbiome cohort differences.

Do I need MAFFT and FastTree to calculate Faith PD and UniFrac metrics?▼

Yes, MAFFT and FastTree are required to construct the ASV phylogenetic tree needed to calculate Faith PD and UniFrac metrics. Without this tree-building step, you cannot compute phylogenetically-aware diversity from 16S sequences.

What is the best way to compare UniFrac against Bray-Curtis for microbiome diversity?▼

The best way to compare UniFrac against Bray-Curtis is to compute both unweighted and weighted UniFrac from a tree-augmented AnnData object. This allows you to contrast phylogenetically-aware beta diversity with standard abundance-based metrics.

Why does tree tip validation fail when attaching phylogenetic trees to AnnData?▼

Tree tip validation fails when attaching phylogenetic trees to AnnData due to mismatches between tree tip names and ASV feature names. The Skill addresses this by validating tip names and pruning mismatches when appropriate before attachment.