RNA-Seq Data Analysis in R: From Raw Counts to Differential Expression Analysis

RNA-Seq is a widely used method for analyzing gene expression. This workshop focuses on differential expression analysis using R, guiding participants through essential steps from raw count data to identifying differentially expressed genes.

This workshop provides graduate students in public universities with the necessary skills and tools to analyze biological data using high-performance computing resources.

Participants will acquire hands-on experience with industry-standard command-line tools (CLI) for DNA and RNA sequencing analysis, sequence manipulation and alignment, and pipeline management for automating complex workflows. They will also learn about differential expression analysis for identifying genes with altered expression levels, data visualization techniques for effectively presenting results, and the basics of artificial intelligence (AI) and machine learning (ML) in bioinformatics.

Upon completion of this workshop, graduates will be capable of using these powerful tools and methods to address real-world biological challenges and make significant contributions to bioinformatics research.

SERIES: Exploring Tools for Data Analysis and AI Applications in Biosciences and Genomics
Where: REGISTER for Zoom link  Weaver Science-Engineering Library, Rm 212 and on Zoom
Instructor: Michele Cosi and Simona Merlini
YouTube: UArizona DataLab and session links

Workshop sessions:

• 1/30 Sequence manipulation, alignment, and assessment
• 2/6 A Beginner's Guide to RNA-seq with DESeq2    
• 2/13 RNA-Seq Data Analysis in R: From Raw Counts to Differential Expression Analysis    
• 2/20 Downstream Analysis of RNA-Seq Results in R: GSEA, PPI Networks, and Biological Interpretation    
• 2/27 QTL mapping with qtl2    
• 3/6  Introduction to GWAS
• 3/20 De-novo Detection and Annotation of Transposable Elements    
• 3/27 Explore Current AI/ML Trends and Tools in Bioinformatics

REGISTER