OpenSkillIndex← back to search
claude-codescience

Babysitter seurat-single-cell-analyzer

Seurat single-cell analysis skill for clustering, annotation, and trajectory analysis

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/science/bioinformatics/skills/seurat-single-cell-analyzer" ~/.claude/skills/a5c-ai-babysitter-seurat-single-cell-analyzer && rm -rf "$T"
manifest: library/specializations/domains/science/bioinformatics/skills/seurat-single-cell-analyzer/SKILL.md
tags
#single-cell#scrnaseq#clustering#annotation#trajectory#transcriptomics
source content

Seurat Single-Cell Analyzer Skill

Purpose

Enable Seurat single-cell analysis for clustering, annotation, and trajectory analysis of scRNA-seq data.

Capabilities

  • Quality filtering and normalization
  • Dimensionality reduction (PCA, UMAP)
  • Graph-based clustering
  • Marker gene identification
  • Cell type annotation
  • Integration across datasets
  • Trajectory inference

Usage Guidelines

  • Apply quality filters appropriate for experiment
  • Normalize data before dimensionality reduction
  • Select clustering resolution based on biology
  • Identify markers for cluster annotation
  • Integrate datasets to remove batch effects
  • Document analysis parameters

Dependencies

  • Seurat
  • Scanpy
  • CellRanger

Process Integration

  • Single-Cell RNA-seq Analysis (scrnaseq-analysis)
  • Spatial Transcriptomics Analysis (spatial-transcriptomics)