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Clustering and Markers Identification for ScRNA-Seq - Seurat Package Tutorial

LiquidBrain Bioinformatics via YouTube

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Overview

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This tutorial demonstrates a Seurat workflow for single-cell RNA-seq, from importing 10x data through quality control, normalization, PCA/UMAP clustering, and marker-gene identification. It uses a PBMC dataset to visualize and assign cell types.

Syllabus

1. Package Import
2. Data Import
3. Data QC and Inspection
4. Data Normalization
5. Data Clustering PCA/UMAP
6. Markers Identification
7. Putting all together

Taught by

LiquidBrain Bioinformatics

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