Clustering and Markers Identification for ScRNA-Seq - Seurat Package Tutorial
LiquidBrain Bioinformatics via YouTube
All Coursera Certificates 40% Off
AI Engineer - Learn how to integrate AI into software applications
Overview
Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Explore single-cell RNA sequencing analysis using the Seurat package in this 23-minute tutorial. Learn how to import and preprocess data, perform quality control, normalize datasets, and cluster cells using PCA and UMAP techniques. Discover methods for identifying marker genes and visualizing analysis results. Follow along with a script adapted from Satija Lab, covering essential steps from package import to data integration. Gain insights into overcoming dilution effects in RNA-seq experiments and understanding cellular interactions within closely grouped cells.
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