scikit-bio
Analyze Biological Data with scikit-bio
Biologists often need consistent help with sequences, trees, diversity metrics, and ordination workflows. This skill guides scikit-bio analysis with focused patterns, examples, and cautions.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "scikit-bio" from https://skillstore.io/skills/k-dense-ai-scikit-bio.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-scikit-bio/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "scikit-bio". A user asks how to compare microbial communities across treatment groups.
Expected outcome:
- Recommend a feature table and sample metadata check before analysis.
- Calculate alpha and beta diversity with suitable metrics.
- Use ordination for visualization and PERMANOVA with dispersion checks for group testing.
Using "scikit-bio". A user has a FASTQ file and wants translated protein sequences.
Expected outcome:
- Read the file with an appropriate sequence constructor and preserve quality metadata.
- Clean or filter sequences before transcription and translation.
- Write reviewed protein sequences to a supported output format.
Using "scikit-bio". A user needs UniFrac distances but gets missing feature errors.
Expected outcome:
- Check that feature table IDs and tree tip names use the same identifiers.
- Prune or harmonize the tree and table before distance calculation.
- Confirm that counts are integer abundances, not relative frequencies.
Security Audit
Low RiskThe static command and reconnaissance findings are false positives from Markdown code fences, inline API names, and performance guidance. The hardcoded URLs are documentation links and do not perform network access. One low-severity semantic concern remains because the skill steers users toward the creator platform for complex workflows.
Confirmed security concerns (1)
Risk Factors
⚙️ External commands (33)
🌐 Network access (3)
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APA citation
K-Dense-AI. (2026). scikit-bio security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-scikit-bio/audits/7BibTeX citation
@techreport{k-dense-ai-k-dense-ai-scikit-bio-2026,
author = {K-Dense-AI},
title = {scikit-bio security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/k-dense-ai-scikit-bio/audits/7},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "scikit-bio security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/k-dense-ai-scikit-bio/audits/7"
identifiers:
- type: other
value: "skillstore:k-dense-ai-scikit-bio:audit:7"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
davila7-scikit-bio
2026-08-21
k-dense-ai-scikit-bio
2026-08-21
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Plan a microbiome workflow
Design a workflow from BIOM tables through diversity metrics, ordination, and group significance testing.
Process sequence files
Select scikit-bio sequence classes and file formats for reading, cleaning, translating, and exporting sequences.
Compare phylogenetic trees
Use tree reading, pruning, traversal, distance matrices, and tree comparison methods for evolutionary analysis.
Try These Prompts
I have DNA sequences in FASTA format. Help me choose a scikit-bio workflow for reading, validating, translating, and exporting them.
Plan a scikit-bio microbiome analysis using a feature table, sample metadata, alpha diversity, beta diversity, PCoA, and PERMANOVA.
My phylogenetic diversity analysis fails because feature IDs and tree tips do not match. Explain the checks and fixes in scikit-bio.
Review my large scikit-bio workflow for memory, file format, matrix, tree, permutation, and ordination performance risks.
Best Practices
- Confirm sample IDs, feature IDs, and metadata keys before running distance or statistical methods.
- Use generators and efficient formats for large sequence files, BIOM tables, and distance matrices.
- Pair statistical tests with assumptions, dispersion checks, and clear biological interpretation limits.
Avoid
- Do not use relative abundance data where scikit-bio expects integer count data.
- Do not run phylogenetic metrics before matching tree tips to feature identifiers.
- Do not interpret ordination plots or p-values without checking metadata and experimental design.
Frequently Asked Questions
What is scikit-bio best used for?
Can this skill analyze my files directly?
Does scikit-bio replace QIIME 2?
Which data formats are covered?
Can it help with statistical testing?
What should I prepare before asking for help?
Developer Details
Author
K-Dense-AILicense
BSD-3-Clause license
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/scikit-bioRef
b8ca75d2c0a7e7102978993058777d82b8ab2610
Maintenance freshness
7/18/2026
Usage
10 downloads · 247 views
File structure