schedule

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	Will
10:45 - 11:15	RNA-seq pre-reading discussion	All
11:15 - 12:00	Intro to DGE / setting up DGE analysis	Radhika

Before the next class:

1. Please study the contents and work through all the code within the following lessons:

• RNA-seq counts distribution
• Count normalization
• Sample-level QC (PCA and hierarchical clustering)

2. Complete the exercises:
   • Each lesson above contain exercises; please go through each of them.
   • Copy over your code from the exercises into a text file.
   • Upload the saved text file to Dropbox the day before the next class.

Questions?

• If you get stuck due to an error while runnning code in the lesson, email us
• Post any conceptual questions that you would like to have reviewed in class here.

Answer Key

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Day 2

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

Before the next class:

1. Please study the contents and work through all the code within the following lessons:

   • Description of steps for DESeq2
   • Wald test results
   • Summarizing results and extracting significant gene lists
   • Visualization

2. Complete the exercises:

   • Each lesson above contain exercises; please go through each of them.
   • Copy over your code from the exercises into a text file.
   • Upload the saved text file to Dropbox the day before the next class.

Questions?

• If you get stuck due to an error while runnning code in the lesson, email us
• Post any conceptual questions that you would like to have reviewed in class here.

Answer Key

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Day 3

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

Before the next class:

1. Please study the contents and work through all the code within the following lessons:

   • Time course analysis
   • Gene annotation
   • Functional analysis - over-representation analysis
   • Functional analysis - functional class scoring / GSEA

2. There is no assignment submission

Questions?

• Post any conceptual questions that you would like to have reviewed in class here.

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Day 4

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

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:

• DESeq2 vignette
• GitHub book on RNA-seq gene level analysis
• Bioconductor support site (posts tagged with deseq2)
• Functional analysis visualization

Building on this workshop

• Single-cell RNA-seq workshop
• RMarkdown
• Ggplot2 for functional analysis

Other helpful links

• Online learning resources
• All hbctraining materials