This course teaches learners how to integrate single-cell RNA-Seq datasets in R using the Seurat package to correct for batch effects. The course covers study design, types of integration, batch correction methods, downloading and reading data in R, merging Seurat objects, quality control, visualization of data before and after integration, and comparing UMAPs. The intended audience for this course includes beginners in genomics, bioinformatics researchers, and individuals interested in single-cell RNA sequencing and data integration techniques. The teaching method involves a detailed tutorial with a step-by-step workflow and additional external resources for further learning.
Integrate Single-Cell RNA-Seq Datasets in R Using Seurat - Detailed Seurat Workflow Tutorial
Overview
Syllabus
Intro
Study design
When to integrate?
Types of integration
Batch correction methods
Downloading data
Read data in R
Merge Seurat objects
QC and filtering
Do we see batch effects in our data?
Visualize merged data before integration
Integration steps
Visualize integrated data after integration
Comparing UMAPs: before integration vs after integration
Taught by
bioinformagician
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