scikit-bio

Analyze biological sequence, tree, and microbiome data workflows in Python.

Updated Jul 1, 2026
One-click install
npx skills add https://github.com/jasrajtulsi/GRAD-SCOPE --skill scikit-bio-jasrajtulsi
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: scikit-bio
Source: https://github.com/jasrajtulsi/GRAD-SCOPE/tree/main/.claude/skills/scikit-bio
Command: npx skills add https://github.com/jasrajtulsi/GRAD-SCOPE --skill scikit-bio-jasrajtulsi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you analyze biological data in a structured way, reducing the manual effort involved in sequence handling, phylogenetic analysis, microbiome workflows, and statistical interpretation.

Core Features & Use Cases

  • Sequence and alignment analysis: Work with DNA, RNA, and protein data, including pairwise alignment and motif searching.
  • Phylogenetics and diversity: Build and compare trees, calculate alpha and beta diversity, and run ecological statistics.
  • Data I/O and ordination: Read and write FASTA, Newick, BIOM, and related formats, then visualize patterns with ordination methods.
  • Use Case: A researcher can load sequencing data, compute community diversity, compare samples with PERMANOVA, and generate publication-ready ordination results from the same workflow.

Quick Start

Ask me to analyze your biological sequences, trees, or microbiome tables with scikit-bio and I will prepare the appropriate Python workflow for your files.

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 microbiome tables in Python?

You can calculate alpha and beta diversity from microbiome tables in Python by processing BIOM tabular inputs through this Skill, which computes community diversity metrics and runs permutation-based ecological statistics like PERMANOVA for sample comparison.

What is the best way to run PERMANOVA and ordination on biological sequencing data?

The best way to run PERMANOVA and ordination on biological sequencing data is using this Skill to load sequencing files, compute distance matrices, and generate publication-ready ordination results from a single Python workflow.

Can I read and write FASTA and Newick files for phylogenetic tree analysis?

Yes, you can read and write FASTA and Newick files for phylogenetic tree analysis. This Skill handles biological data I/O, allowing you to load tree formats, build phylogenetic structures, and compare them within your Python environment.

Does this approach support pairwise alignment for DNA, RNA, and protein sequences?

Yes, this approach supports pairwise alignment for DNA, RNA, and protein sequences. The Skill applies sequence and alignment analysis workflows, including motif searching, directly on biological sequence data in Python.

Do I need scikit-bio objects to perform distance matrix and ecological statistics tasks?

Yes, you need scikit-bio objects to perform distance matrix and ecological statistics tasks. The Skill requires these specific Python objects to execute file I/O, alignment, and permutation-based diversity workflows accurately.