seuratclusterstats

Generate cluster statistics and visualizations for Seurat objects.

22|4|Updated May 18, 2021

Search Tags:#visualization #statistics #single-cell #cluster #seurat #scrna-seq #clustree

Ready to run

npx skills add https://github.com/pwwang/immunopipe --skill seuratclusterstats

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: seuratclusterstats
Source: https://github.com/pwwang/immunopipe/tree/main/skills/seuratclusterstats
Command: npx skills add https://github.com/pwwang/immunopipe --skill seuratclusterstats

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generates comprehensive cluster statistics and visualizations for Seurat objects to facilitate evaluation of clustering results and interpretation of cluster relationships.

Core Features & Use Cases

Produces dimension reduction plots, cluster quality metrics, and gene expression visualizations.
Creates clustree diagrams to illustrate cluster relationships and stability.
Supports SeuratClustering and SeuratSubClustering workflows and outputs plots for QC and reporting.

Quick Start

Run SeuratClusterStats on your Seurat object to generate the standard set of cluster statistics and visualizations.

Frequently Asked Questions about seuratclusterstats

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

FAQPage Schema

How do I visualize Seurat clustering results and evaluate cluster quality?▼

To evaluate Seurat cluster quality, generate dimension reduction plots, cluster statistics, and gene expression visualizations directly from your Seurat object to assess clustering results and interpret relationships.

What is a clustree diagram and when do I need it for scRNA-seq analysis?▼

A clustree diagram illustrates cluster relationships and stability across resolutions in scRNA-seq analysis. You need it to visually evaluate how clusters relate and maintain consistency during Seurat clustering workflows.

Can I generate cluster statistics for Seurat subclustering workflows?▼

Yes, you can generate cluster statistics for Seurat subclustering workflows. The process supports both SeuratClustering and SeuratSubClustering objects to evaluate sub-population quality and relationships.

How do I plot gene expression features across Seurat clusters?▼

To plot gene expression features across Seurat clusters, apply feature plots and dimension reduction visualizations to your clustered Seurat object. This maps gene expression distributions onto the calculated cluster structures.

Does Seurat cluster visualization work with metadata variables?▼

Seurat cluster visualization works with metadata by evaluating cluster relationships against variables stored in the Seurat object. This allows you to compare clustering structures directly with sample conditions or QC metrics.

What visualizations are needed to report scRNA-seq cluster statistics?▼

To report scRNA-seq cluster statistics, you need dimension reduction plots, clustree diagrams, gene counts, and feature plots. These visualizations summarize clustering structure and quality for reproducible QC reporting.