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Pathway enrichment with gProfiler, clusterProfiler and fgsea

Pathway enrichment with gProfiler, clusterProfiler and fgsea
Free Download Pathway enrichment with gProfiler, clusterProfiler and fgsea
Published 2/2024
Created by George Sentis
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 21 Lectures ( 2h 22m ) | Size: 1.3 GB


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!
Who this course is for:
Intermediate or Advanced R users aiming to delve more into bioinformatics
Homepage
https://www.udemy.com/course/pathway-enrichment-analysis-dama/








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