DESeq2 Design Explained: Understanding Interaction Terms in RNA-Seq Analysis
In this video, I'll break down the concept of interaction terms in #DESeq2 design, making complex statistical models accessible and easy to understand. In this tutorial I will guide you through -
what are main effects vs interaction terms and why they are crucial in your experimental design, step-by-step examples of setting up and interpreting interaction terms in DESeq2, common pitfalls and best practices to ensure accurate and meaningful results.
I hope you liked the video. I look forward to your comments under the comments section!
▸ Link to previous DESeq2 videos:
1. • DESeq2 Basics Explained | Differentia...
2. • DESeq2 workflow tutorial | Differenti...
▸ Link to Vignette:
https://www.bioconductor.org/packages...
▸ Link to code:
https://github.com/kpatel427/YouTubeT...
Chapters:
0:00 Intro
1:14 Main effect vs Interaction terms
3:09 Case 1: One factor with 2 groups
5:14 Case 2: One factor with multiple groups
6:34 Case 3: Two factors with 2 groups each
8:28 Does the order matter? [~ genotype + treatment] vs [~ treatment + genotype]
9:59 Understanding Interaction terms
11:58 When to use interaction terms?
18:01 Case 4: Two factors with multiple groups (without interaction terms)
19:47 Case 4: Two factors with multiple groups (with interaction terms)
20:42 Difference between [~ genotype:treatment] and [~ genotype + treatment + genotype:treatment]
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To get in touch:
Website: https://bioinformagician.org/
Github: https://github.com/kpatel427
Email: [email protected]
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