seurat-single-cell-analyzer

# 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)