Clustering and Markers Identification for ScRNA-Seq - Seurat Package Tutorial
Offered By: LiquidBrain Bioinformatics via YouTube
Course Description
Overview
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
Related Courses
Intro to StatisticsStanford University via Udacity Introduction to Data Science
University of Washington via Coursera Passion Driven Statistics
Wesleyan University via Coursera Information Visualization
Indiana University via Independent DCO042 - Python For Informatics
University of Michigan via Independent