Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

How to Analyze Single-Cell RNA-Seq Data in R - Detailed Seurat Workflow Tutorial

Bioinformagician via YouTube

Start learning Write review
Coursera Ad

AI, Data Science & Cloud Certificates from Google, IBM & Meta

Learn More → Scrimba Ad

Get 20% off all career paths from fullstack to AI

Learn More →

Overview

Google, IBM & Meta Certificates – 40% Off
One Coursera Plus subscription covers most Professional Certificates on Coursera.
Unlock All Certificates
This tutorial demonstrates a standard Seurat workflow for analyzing a 10X Genomics single-cell RNA sequencing dataset in R. It covers quality control, filtering, normalization, dimensionality reduction, and clustering.

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

Reviews

Start your review of How to Analyze Single-Cell RNA-Seq Data in R - Detailed Seurat Workflow Tutorial

Start learning

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.