Differential expression analysis using edgeR

[mitsumi]

Differential expression analysis using edgeR
Published 10/2023
Created by George Sentis
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 15 Lectures ( 1h 52m ) | Size: 1.1 GB

Learn how to compare two biological conditions using transcriptomic data.

What you'll learn
Understand the structure of RNA-Seq data objects in R
Explore your RNA-Seq data
Clean your RNA-Seq data
Perform differential expression analysis using edgeR
Requirements
Basic R programming skills
Description
Hello everyone! My name is George and I am a bioinformatician. I am here to guide you through an analysis of RNA sequencing data using edgeR. This is a differential expression analysis where we compare samples from Psoriatic Arthritis patients to Healthy controls in order to identify deregulated genes. It is a very simple and common experimental design that is an industry-standard nowadays and a great tool to have at your disposal. For this course, you need to have some basic R programming experience and you need to have a computer with R language installed. This course is intended for people aiming to dive into the world of RNA sequencing data analysis and have not had the chance to analyse data using edgeR before.We will use the publicly available Psoriatic Arthritis dataset and perform some data cleaning, preparation, exploratory analysis, data normalization and subsequently reach our desired goal which is the differential expression analysis. Finally, we will visualize the results by creating a volcano plot and a heatmap of the top differentially expressed genes and we will save any information needed for this analysis to be documented in a reproducible way.If you fulfil the above-mentioned criteria, tag along and let's explore the basics of differential expression using edgeR!
Who this course is for
Beginner or Advanced R users aiming to delve into bioinformatics

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