alterlab-scikit-bio

Automate bioinformatics workflows for DNA, RNA, and protein sequence data.

58|9|Updated Mar 16, 2026

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

Ready to run

npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-scikit-bio

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: alterlab-scikit-bio
Source: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/tree/main/skills/bioinformatics/alterlab-scikit-bio
Command: npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-scikit-bio

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Biological data workflows are often ad hoc, requiring extensive scripting to handle sequence data, alignments, and phylogenetic analyses. This skill provides a unified toolkit to streamline bioinformatics research by enabling convenient handling, analysis, and interpretation of biological sequence data within Python, reducing manual scripting and integration effort.

Core Features & Use Cases

Sequence I/O and format support (FASTA, FASTQ, GenBank, Newick, BIOM)
Sequence manipulation, alignment (pairwise and multiple), and motif analysis
Phylogenetic tree construction, manipulation, and evolutionary distance calculations
Diversity metrics, ordination (PCoA/CCA/RDA), and associated statistical tests
Integrates with downstream analytics tools and data visualization workflows

Quick Start

Install scikit-bio and load sequences from a FASTA file to begin basic analyses.

Frequently Asked Questions about alterlab-scikit-bio

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

FAQPage Schema

How do I handle biological sequence data from FASTA and GenBank files for phylogenetic analysis?▼

This toolkit reads biological sequence data from FASTA and GenBank files, performs alignments, and constructs phylogenetic trees to streamline complex bioinformatics workflows within Python.

What is the best way to calculate diversity metrics and perform ordination on microbiome data?▼

Diversity metrics and ordination methods like PCoA, CCA, and RDA can be applied directly to microbiome data, executing associated statistical tests and integrating with downstream visualization workflows.

Can I use this scikit-bio toolkit for both DNA and protein sequence alignment?▼

Yes, the scikit-bio toolkit supports DNA, RNA, and protein analyses, providing capabilities for both pairwise and multiple sequence alignment alongside motif analysis.

Does this sequence analysis toolkit support reading and writing BIOM format files?▼

Yes, the sequence analysis toolkit supports reading and writing common biological file formats including BIOM, FASTQ, and Newick for seamless integration into genomics workflows.

How do I automate multiple sequence alignment and phylogenetic tree construction without extensive scripting?▼

You can automate multiple sequence alignment and phylogenetic tree construction by using a unified toolkit that handles sequence manipulation and evolutionary distance calculations, reducing manual integration effort.

What downstream statistical tools integrate with sequence analysis and ordination results?▼

Sequence analysis and ordination results integrate with downstream analytics tools and data visualization workflows, enabling comprehensive statistical interpretation of biological data.