Pathway Enrichment With Gprofiler, Clusterprofiler And Fgsea

Learn how to perform OverRepresentation Analysis (ORA) and Functional Class Scoring (FCS) analysis.

What you'll learn

How overrepresentation analysis works

How functional class scoring works

How to perform pathway enrichment analysis

How to visualize the results

Requirements

Basic R programming skills

Description

Hello everyone!This course focuses on exploring the biological pathways associated with a list of genes. More specifically, it focuses on knowledge-based pathway enrichment analysis through methods such as OverRepresentation Analysis (ORA) and Functional Class Scoring (FCS). At the end of this course you should be able to perform ORA using two of the most commonly used tools, gProfiler and clusterProfiler. You should also be able to perform FCS analysis by using clusterProfiler and fgsea packages. You will also learn how to choose the top results,  how to visualize these results using two different kinds of plots and also how to plot the expression of the core genes associated with a specific pathway that might hold biological significance in your data.If you are eager to extract biological insight from a list of genes of interest you have on your hands, or if you plan on diving in the world of transcriptomics data analysis, the analyses mentioned in this course are a must.So, get in your learning mood and start the course to learn one of the most commonly used bioinformatics analyses!P.S. You also get to keep the script for use with your own gene lists and datasets! Neat!

Overview

Section 1: Introduction

Lecture 1 File Structure

Lecture 2 Introduction

Lecture 3 Basic R commands and data structures

Lecture 4 Installing the required libraries

Lecture 5 Basic Dplyr Info

Section 2: Pathway Enrichment

Lecture 6 Brief explanation of pathway enrichment methods

Lecture 7 Description of available data

Lecture 8 Setting up Overrepresentation analysis (ORA)

Lecture 9 Gathering Gene sets

Lecture 10 ORA using gProfiler

Lecture 11 ORA using clusterProfiler

Lecture 12 Comparing ORA results

Lecture 13 Preparing ranked gene list and FCS using clusterProfiler

Lecture 14 FCS using fgsea

Lecture 15 Comparing FCS results

Section 3: Visualizing results

Lecture 16 Creating an enrichment bubble plot for gProfiler

Lecture 17 Creating an enrichment bubble plot for clusterProfiler's ORA

Lecture 18 Creating an enrichment bubble plot for clusterProfiler's FCS

Lecture 19 Plotting fgsea results

Lecture 20 Plotting a leading egde gene expression heatmap

Section 4: Reproducibility

Lecture 21 Reproducibility and closing remarks

Intermediate or Advanced R users aiming to delve more into bioinformatics