In stemangiola/rpharma2020_tidytranscriptomics: Introduction to Tidy Transcriptomics

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Schedule

• Part 1 Bulk RNA-seq Core
• Part 2 Bulk RNA-seq Extended
• Part 3 Single-cell RNA-seq

A more detailed schedule can be found here.

Format: a few introductory slides, then demos, exercises plus Q&A.
Interact: Zoom chat and polls

What is transcriptomics?

“The transcriptome is the set of all RNA transcripts, including coding and non-coding, in an individual or a population of cells”

Wikipedia

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Why use transcriptomics?

• Genome (DNA) pretty stable
• Proteome (proteins) harder to measure
• Transcriptome (RNA) can measure changes in expression of thousands of coding and non-coding transcripts
  
  

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Possible experimental design

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How does transcriptomics work?

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Types of transcriptomic analyses

• Differential expression
• Cell type composition
• Alternative splicing
• Novel transcript discovery
• Fusions identification
• Variant analysis
  
  Topics in bold we will see in this workshop
  
  

Bulk RNA sequencing differential expression workflow

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Differences between bulk and single-cell RNA sequencing

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Shalek and Benson, 2017

Single-cell RNA sequencing analysis workflow

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Getting started

Cloud

Easiest way to run this material. Only available during workshop.
* You should have received an invite to join the classroom in the R in Pharma Organization space in RStudio Cloud.
* Login and click the "Start" button as shown in the screenshot below
* Open tidytranscriptomics.Rmd in vignettes folder

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Local

If you want to install on your own computer, see instructions here. We recommend using the Cloud during the RPharma workshop and this method if you want to run the material after the workshop.

stemangiola/rpharma2020_tidytranscriptomics documentation built on Oct. 9, 2020, 9:41 p.m.