Differential gene expression analysis is a method, used to examine variations in gene expression across different sample sets. This technique is pivotal for identifying genes, transcripts, or regions that have significant differences in expression, considering the variance within conditions.

The R Bioconductor package (DEBrowser) aids in performing differential expression analysis using count data from sequencing assays, notably RNA-Seq, Chip-Seq and ATAC-Seq.

Navigating intricate parameters like p-adjust values, log fold changes, and specific plot configurations can be intricate. Here’s where DEBrowser steps in. In conjunction with DESeq2, EdgeR, and Limma, and supported by the shiny interface, DEBrowser provides a streamlined approach. This tool not only simplifies data visualization but also facilitates real-time adjustments and offers an interactive overview of analysis results.

Designed explicitly for beginners, this course provides thorough guidance from initiation to culmination, ensuring a holistic understanding of the subject.

Name of the course leader at the section: Dr. Alper Kucukural

In order to register send an email to: Susanne Keipert: susanne.keipert@su.se or Sara Rydberg: sara.rydberg@su.se