Differential expression analysis is a critical step in transcriptomics studies, as it helps to identify genes or transcripts that are differentially expressed between two or more conditions. In this webinar, we will be discussing the latest techniques and methods for differential expression analysis and how to effectively interpret the results. If you have questions like how much of each transcript is in sample? How do transcript counts compare to other samples, or change under different conditions? Anne will try to answer these questions in this webinar.
Speaker: Anne Mathiesen
Bioinformatics Field Applications Scientist
Your email address is never shared with third parties.
GL-01836