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scikit-bio

Read, manipulate, and analyze biological sequences in FASTA, FASTQ, and GenBank formats.

Updated Mar 30, 2026
Search Tags:#bioinformatics#ordination#phylogenetics#sequence-analysis#microbiome#diversity-analysis#BIOM
One-click install
npx skills add https://github.com/ya-way/cytoclaw-skills --skill scikit-bio-ya-way
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scikit-bio
Source: https://github.com/ya-way/cytoclaw-skills/tree/main/workspace/skills/labclaw-scikit-bio
Command: npx skills add https://github.com/ya-way/cytoclaw-skills --skill scikit-bio-ya-way

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Biological data analysis often requires stitching together multiple specialized tools and formats. scikit-bio provides a unified Python toolkit for manipulating sequences, performing alignments and phylogenetic analyses, and calculating diversity metrics across common formats (FASTA, FASTQ, GenBank, BIOM, Newick). This enables researchers to build end-to-end workflows for microbiome and ecological studies.

Core Features & Use Cases

  • Sequence manipulation for DNA, RNA, and proteins, including reading, translating, reversing, and motif finding.
  • Alignment, phylogenetics, and diversity analysis for microbiome and ecological datasets.
  • Ordination and statistical testing (PCoA, PERMANOVA, ANOSIM) integrated with standard data structures.
  • Flexible file I/O and BIOM table support enabling seamless integration with QIIME 2 pipelines.
  • Interoperability with other bioinformatics tools and formats for end-to-end analyses.

Quick Start

Install scikit-bio and load a FASTA file to start sequence manipulation and basic analyses.

Frequently Asked Questions about scikit-bio

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

FAQPage Schema
How do I perform microbiome diversity analysis and ordination on BIOM tables?▼

Microbiome diversity analysis and ordination apply statistical tests like PERMANOVA, ANOSIM, and PCoA to BIOM tables to calculate ecological distance matrices. This toolkit integrates these tests with standard data structures for seamless ordination workflows.

Can I read and manipulate FASTA, FASTQ, and GenBank sequence files in Python?▼

Reading and manipulating FASTA, FASTQ, and GenBank files in Python requires type-specific alphabets for DNA, RNA, and proteins. This toolkit supports file I/O for sequence manipulation including reading, translating, reversing, and motif finding.

Does scikit-bio integrate with QIIME 2 pipelines for phylogenetics?▼

scikit-bio integrates with QIIME 2 pipelines through flexible file I/O and BIOM table support. It processes Newick phylogenetic trees and performs alignments to enable end-to-end microbiome and ecological analyses.

What is the best way to calculate distance matrices for ecological datasets?▼

Calculating distance matrices for ecological datasets is best handled through integrated ordination methods and diversity metrics. This approach supports BIOM tables and standard data structures for robust statistical testing of microbiome data.

How do I parse Newick trees for phylogenetic analysis alongside sequence data?▼

Parsing Newick trees for phylogenetic analysis runs alongside sequence manipulation by supporting common formats like FASTA and GenBank. This unified toolkit aligns sequences and applies phylogenetics within an end-to-end workflow.

Are there limitations when stitching together multiple biological formats for microbiome analytics?▼

Stitching together multiple biological formats for microbiome analytics requires careful handling of type-specific alphabets across FASTA, GenBank, and BIOM formats. Limitations depend on proper file I/O integration and interoperability with external statistical visualization libraries.

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