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.