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seuratsubclustering

Re-cluster selected cell subsets within a Seurat object using PCA, UMAP, and clustering workflows.

22|4|Updated May 18, 2021
Search Tags:#workflow#r#single-cell#clustering#seurat#subclustering#subset
One-click install
npx skills add https://github.com/pwwang/immunopipe --skill seuratsubclustering
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: seuratsubclustering
Source: https://github.com/pwwang/immunopipe/tree/main/skills/seuratsubclustering
Command: npx skills add https://github.com/pwwang/immunopipe --skill seuratsubclustering

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Performs fine-grained re-clustering on specific subsets of cells within a Seurat object to resolve heterogeneity and reveal hidden subpopulations.

Core Features & Use Cases

  • Complete clustering workflow on user-defined subsets, including PCA, UMAP, FindNeighbors, and FindClusters, to explore substructure within clusters or annotated cell types.
  • Supports metadata- or barcode-based subsetting, multiple resolutions, and case-based outputs to compare hierarchical clustering results.
  • Integrates with mutaters and subset expressions to tailor analyses for targeted biological questions, such as dissecting CD4 T cell or CD8 T cell heterogeneity.

Quick Start

Provide a Seurat object and a subset expression, and run the full re-clustering workflow on that subset.

Frequently Asked Questions about seuratsubclustering

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

FAQPage Schema
How do I perform subclustering on a specific subset of cells in a Seurat object?▼

To perform subclustering in a Seurat object, provide a subset expression or cell barcode list. The workflow runs RunPCA, RunUMAP, FindNeighbors, and FindClusters on that subset to reveal hidden subpopulations.

Can I re-cluster cells using metadata filters and multiple resolutions in Seurat?▼

Yes, you can re-cluster cells using metadata filters or barcode lists across multiple resolutions. This enables case-based outputs to compare hierarchical clustering results within defined groups.

What is the best way to resolve hidden heterogeneity within an annotated cell type?▼

Re-clustering specific cell types, such as CD4 T cells, using a configurable PCA and UMAP workflow resolves hidden heterogeneity. Mutaters and subset expressions tailor the analysis to targeted biological questions.

Does this subclustering workflow support subsetting by cell barcode lists?▼

Yes, the subclustering workflow supports subsetting by cell barcode lists as well as metadata filters. This allows precise targeting of custom cell groups for fine-grained re-clustering.

How does fine-grained re-clustering differ from initial single-cell clustering?▼

Fine-grained re-clustering focuses on selected cell subsets to resolve substructure, unlike initial broad clustering. It applies PCA, UMAP, and FindClusters within subsets to dissect cell type heterogeneity.

When should I use mutaters for subset definitions in Seurat subclustering?▼

Use mutaters for subset definitions when you need to tailor re-clustering analyses for targeted biological questions. They integrate with subset expressions to define custom groups across multiple resolutions.

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