Workshop Schedule

Pre-reading

  1. Workflow (raw data to counts)
  2. Experimental design considerations

Day 1

Time Topic Instructor
10:00 - 10:30 Workshop Introduction Radhika
10:30 - 10:45 R refresher Q & A Vishal
10:45 - 11:15 RNA-seq pre-reading discussion Radhika/Vishal
11:15 - 12:00 Intro to DGE / setting up DGE analysis Meeta

Self-Learning Part 1

  1. RNA-seq counts distribution
  2. Count normalization
  3. Sample-level QC (PCA and hierarchical clustering)

Assignment #1


Day 2

Time Topic Instructor
10:00 - 11:00 Self-learning lessons discussion Radhika
11:00 - 11:30 Design formulas Vishal
11:30 - 12:00 Hypothesis testing and multiple test correction Meeta

Self-Learning Part 2

  1. Description of steps for DESeq2
  2. Wald test results
  3. Summarizing results and extracting significant gene lists
  4. Visualization

Assignment #2


Day 3

Time Topic Instructor
10:00 - 11:15 Self-learning lessons discussion Meeta/Vishal/Radhika
11:15 - 12:00 Likelihood Ratio Test results Meeta

Self-Learning Part 3

  1. Time course analysis
  2. Gene annotation
  3. Functional analysis - over-representation analysis
  4. Functional analysis - functional class scoring / GSEA

Assignment #3


Day 4

Time Topic Instructor
10:00 - 11:00 Questions about self-learning lessons All
11:00 - 11:15 Summarizing workflow Vishal
11:15 - 11:45 Discussion, Q & A All
11:45 - 12:00 Wrap Up Meeta

Resources

We have covered the inner workings of DESeq2 in a fair amount of detail such that when using this package you have a good understanding of what is going on under the hood. For more information on topics covered, we encourage you to take a look at the following resources:

Building on this workshop