Learn how to analyze single-cell RNA-Seq data in R using the Seurat package. This course covers downloading data, creating Seurat objects, quality control, filtering, normalization, identifying variable features, dimensionality reduction techniques like PCA and UMAP, and clustering. The teaching method includes a detailed workflow tutorial. This course is intended for individuals interested in bioinformatics, genomics, and RNA sequencing analysis.
How to Analyze Single-Cell RNA-Seq Data in R - Detailed Seurat Workflow Tutorial
Overview
Syllabus
Intro
Download data from 10X Genomics website
Read counts matrix
Create a Seurat Object
Quality Control
Filtering
Normalization
'@commands' slot
Find Variable Features
Scale data
Difference between @counts, @data and @scale.data slots
Linear dimensionality reduction PCA
Determine the dimensionality of the dataset
Clustering
Understanding 'Resolution' in Clustering
Non-linear dimensionality reduction UMAP
Taught by
bioinformagician
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Bioinformatics
