scikit-bio

Perform bioinformatics sequence manipulation, alignment, and diversity analysis with scikit-bio.

Updated May 17, 2026

Search Tags:#bioinformatics #alignment #sequence analysis #ordination #phylogenetics #diversity analysis

One-click install

npx skills add https://github.com/galeep/plugin-place --skill scikit-bio-galeep

Or copy as Structured Prompt for Agent▼

Please help me install this Agent Skill.
Skill: scikit-bio
Source: https://github.com/galeep/plugin-place/tree/main/plugins/sci-bioinformatics-genomics/skills/scikit-bio
Command: npx skills add https://github.com/galeep/plugin-place --skill scikit-bio-galeep

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires scikit-bio, numpy, matplotlib, seaborn, plotly, biom-format, polars, annData, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a comprehensive Python library for bioinformatics analysis, addressing challenges in sequence manipulation, alignment, phylogenetics, and diversity metrics.

Core Features & Use Cases

Sequence Manipulation: Read/write sequences in various formats and perform operations like slicing, concatenation, and pattern matching.
Sequence Alignment: Perform pairwise and multiple sequence alignments with various scoring systems and gap penalties.
Phylogenetic Trees: Construct, manipulate, and analyze phylogenetic trees for evolutionary relationships.
Diversity Analysis: Calculate alpha and beta diversity metrics for microbial ecology and community analysis.
Ordination Methods: Reduce high-dimensional data to lower-dimensional spaces for visualization.
Statistical Testing: Perform hypothesis tests specific to ecological and biological data.
File I/O and Format Conversion: Read and write 19+ biological file formats with automatic format detection.
Distance Matrices: Create and manipulate distance/dissimilarity matrices with statistical methods.
Biological Tables: Work with feature tables (OTU/ASV tables) common in microbiome research.
Protein Embeddings: Work with protein language model embeddings for downstream analysis.
Use Case: A researcher analyzing microbiome data can use this Skill to calculate alpha diversity metrics, perform ordination analysis, and conduct statistical tests on their samples.

Quick Start

Use the scikit-bio skill to calculate alpha diversity metrics for a given sample set.

Frequently Asked Questions about scikit-bio

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

FAQPage Schema

How do I calculate alpha and beta diversity metrics for microbiome data?▼

This toolkit performs sequence alignment by executing pairwise and multiple sequence alignments with customizable scoring systems and gap penalties, handling various biological sequence formats.

What is the best way to construct and analyze phylogenetic trees in Python?▼

Yes, this bioinformatics toolkit reduces high-dimensional biological data into lower-dimensional spaces for ordination analysis, integrating with matplotlib, seaborn, and plotly for visualization.

Do I need specific Python libraries to perform biological file format conversion?▼

To perform biological file I/O and format conversion, you need scikit-bio and NumPy installed, while libraries like biom-format and polars provide extended support for biological table processing.

What statistical testing methods work for ecological and biological data analysis?▼

Statistical testing for ecological and biological data analysis is supported through hypothesis testing methods specific to microbial ecology, allowing you to validate diversity and ordination results.