scikit-bio

Analyze biological sequences, phylogenies, and diversity metrics in Python.

1|Updated Mar 4, 2026

Search Tags:#bioinformatics #data-analysis #ordination #phylogenetics #sequence-analysis #microbiome #diversity-metrics

Ready to run

npx skills add https://github.com/Hung-3008/agusta --skill scikit-bio-hung-3008

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scikit-bio
Source: https://github.com/Hung-3008/agusta/tree/main/.agents/skills/scikit-bio
Command: npx skills add https://github.com/Hung-3008/agusta --skill scikit-bio-hung-3008

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

scikit-bio provides a comprehensive Python library for working with biological data. It enables researchers to manipulate sequences, construct and analyze phylogenetic trees, perform diversity and ordination analyses, and integrate with data ecosystems such as pandas.

Core Features & Use Cases

Sequence manipulation, reading/writing common formats (FASTA, FASTQ, GenBank, Newick, BIOM) and calculating diversity metrics (alpha/beta, UniFrac).
Phylogenetic tree construction, distance metrics, ASCII visualization, and ordination analyses (PCoA, CCA, RDA), plus statistical testing (PERMANOVA, ANOSIM, Mantel).
Ecosystem for microbiome data, protein embeddings, and integration with pandas for downstream ML.

Quick Start

Analyze a BIOM table to compute alpha and beta diversity and generate an ordination plot.

Frequently Asked Questions about scikit-bio

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

FAQPage Schema

How do I compute alpha and beta diversity from a BIOM table for microbiome analysis?▼

To perform microbiome diversity analysis from a BIOM table, calculate alpha and beta diversity metrics, including UniFrac, and use ordination analyses like PCoA to visualize sample relationships.

Can I parse and write common bioinformatics sequence formats like FASTA and GenBank in Python?▼

Yes, you can read and write common sequence formats like FASTA, FASTQ, GenBank, Newick, and BIOM directly in Python, enabling seamless biological sequence manipulation and processing within your data pipelines.

What statistical tests are available for phylogenetic and ordination analysis?▼

For phylogenetic and ordination analysis, you can perform statistical tests including PERMANOVA, ANOSIM, and Mantel tests to evaluate ecological patterns and significance across biological data samples.

Does scikit-bio integrate with pandas for downstream machine learning tasks?▼

Yes, scikit-bio integrates with pandas, allowing you to structure biological data and diversity metrics into DataFrames for downstream machine learning workflows and advanced ecological data analysis.

How do I construct and visualize phylogenetic trees from sequence data?▼

To construct and visualize phylogenetic trees from sequence data, build trees using distance metrics, generate ASCII visualizations, and save the outputs using the Newick format for downstream analysis.