This course covers the learning outcomes and goals of analyzing RNASeq data, including identifying Differential Expressed Genes (DEGs) and performing Gene Set Enrichment Analysis. Participants will learn data manipulation in R, Weighted Correlation Network Analysis (WGCNA), and creating R packages. The teaching method includes tutorials and practical demonstrations in R, making it suitable for beginners in bioinformatics. The intended audience for this course is individuals interested in RNASeq analysis and bioinformatics.
Overview
Syllabus
RNASeq Analysis | Differential Expressed Genes (DEGs) from FastQ.
Log2 fold-change & DESeq2 model in a nutshell.
Gene Set Enrichment Analysis (+ R tutorial).
Data manipulation in R (For Bioinformatics)| R tutorial | For beginner.
Weighted correlation network analysis (WGCNA) tutorial in R| PART I.
How to create your own package in R?.
Taught by
Liquid Brain
