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Find Markers and Cluster Identification in Single-Cell RNA-Seq Using Seurat - Workflow Tutorial

Offered By: Bioinformagician via YouTube

Tags

Bioinformatics Courses Data Visualization Courses Genomics Courses

Course Description

Overview

Learn how to identify canonical markers and differentially expressed genes in single-cell RNA-Seq data using Seurat's marker identification functions in R. Follow a detailed workflow that covers loading and visualizing data, using findAllMarkers() and findConservedMarkers() functions, annotating clusters with marker databases, and performing differential expression analysis between conditions. Gain practical skills in interpreting and visualizing results through FeaturePlots and other techniques. Access provided data, code, and resources to enhance your understanding of single-cell RNA-Seq analysis for biological research and genomics applications.

Syllabus

Intro
findMarkers, findAllMarkers, findConservedMarkers
Study design
Load data
Visualize by clusters and condition
findAllMarkers
DefaultAssay 'RNA'
findConservedMarkers for cluster 3
Visualize canonical markers in a FeaturePlot
RenameIdents
Annotating clusters and marker databases
Annotating rest of the clusters
Perform differential expression in CD16 Monocytes between conditions findMarkers
Visualize markers identified by findConservedMarkers vs findMarkers


Taught by

bioinformagician

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