- Abigail Edwards - Bioinformatics Core, Cancer Research UK Cambridge Institute
- Ashley D Sawle - Bioinformatics Core, Cancer Research UK Cambridge Institute
- Chandra Chilamakuri - Bioinformatics Core, Cancer Research UK Cambridge Institute
- Jon Price - Miska Group, Gurdon Institute, Cambridge
- Stephane Ballereau - Bioinformatics Core, Cancer Research UK Cambridge Institute
- Zeynep Kalender Atak - Miller Group, Cancer Research UK Cambridge Institute
- Hugo Tavares - Bioinformatics Training Facility, Dept of Genetics
In this workshop, you will be learning how to analyse RNA-seq data. This will include read alignment, quality control, quantification against a reference, reading the count data into R, performing differential expression analysis, and gene set testing, with a focus on the DESeq2 analysis workflow. You will learn how to generate common plots for analysis and visualisation of gene expression data, such as boxplots and heatmaps.
This workshop is aimed at biologists interested in learning how to perform differential expression analysis of RNA-seq data.
Whilst we have run this course for several years, we are still learning how to teach it remotely. Please bear with us if there are any technical hitches, and be aware that timings for different sections laid out in the schedule below may not be adhered to. There may be some necessity to make adjusments to the course as we go.
Some basic experience of using a UNIX/LINUX command line is assumed
Some R knowledge is assumed and essential. Without it, you will struggle on this course. If you are not familiar with the R statistical programming language we strongly encourage you to work through an introductory R course before attempting these materials. We recommend our Introduction to R course
This Google Document contains useful information and links..
Please use it to post any questions you have during the course.
The trainers will be monitoring the document and will answer questions as quickly as they can.
There is another Google Doc here. Please write a couple sentences here to introduce yourself to the class, tell us a bit about your background and what you hope to get out of this course. If you are a student or staff at the University of Cambridge, tell us which Department you are in.
As this course is being taught online and there are a large number of participants, we will all need to follow a few simple rules to ensure things run as smoothly as possible:
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Please mute your microphone
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To get help from a tutor, please click the "Raise Hand" button in Zoom:
This can be found by clicking on the 'Participants' button. A tutor will then contact you in the chat. If necessary, you and the tutor can be moved to a breakout room where you can discuss your issue in more detail.
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Please ask any general question by typing it into the Google Doc mentioned above
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During practicals, when you are done, please press the green "Yes" button:
This way we will know when we can move on.
We are still learning how to teach this course remotely, all times here should be regarded as aspirations
9:30 - 9:45 - Welcome!
9:45 - 10:15 - Introduction to RNAseq Methods - Zeynep Kalender Atak
10:15 - 11:15 Raw read file format and
QC - Zeynep Kalender Atak
- Practical (pdf)
- Practical solutions (pdf)
11:15 - 12:45 Short read alignment with
HISAT2 - Jon Price
- Practical (pdf)
- Practical solutions (pdf)
12:45 - 13:45 Lunch
13:45 - 15:30 QC of alignment - Jon Price
- Practical (pdf)
- Practical solutions (pdf)
15:30 - 17:00 Quantification of Gene Expression with Salmon - Ashley Sawle
- Practical (pdf)
- Practical solutions (pdf)
9:30 - 10:15 Introduction to RNAseq Analysis in R - Ashley Sawle
10:15 - 12:15 - RNA-seq
Data Exploration (pdf) - Ashley Sawle
- Practical solutions (pdf)
- Ashley's Live Script
12:15 - 13:15 Lunch
13:15 - 15:45 Statistical Analysis of Bulk RNAseq Data
- Part I: Statistics of RNA-seq analysis - Zeynep Kalender Atak
- Part II: Linear Models in R and DESeq2 (pdf) - Hugo Tavares
- Slides (live blackboard used during lecture)
- Find the worksheet in
Course_Materials/stats/models_in_r_worksheet.R
15:45 - 17:00 Experimental Design of Bulk RNAseq studies - Abbi Edwards
- Practical
- Answers
9:30 - 12:15 - Differential Expression for RNA-seq (pdf) - Chandra Chilamakuri
- practical solutions (pdf)
12:15 - 13:15 Lunch
13:15 - 15:30 Annotation and Visualisation of RNA-seq
results (pdf) - Abbi Edwards
- practical solutions
- Abbi's Live Script
15:30 - 17:00 Gene-set testing - Stephane Ballereau
The lecture slides and other source materials, including R code and practical solutions, can be found in the course's Github repository
The Extended Materials contain extensions to some of the sessions and additional materials, including instruction on downloading and processing the raw data for this course, a link to an excellent R course, and where to get further help after the course.
This course is based on the course RNAseq analysis in R prepared by Combine Australia and delivered on May 11/12th 2016 in Carlton. We are extremely grateful to the authors for making their materials available; Maria Doyle, Belinda Phipson, Matt Ritchie, Anna Trigos, Harriet Dashnow, Charity Law.
The materials have been rewritten/modified/corrected/updated by various contributors over the past 5 years including:
Abigail Edwards Ashley D Sawle Chandra Chilamakuri Dominique-Laurent Couturier Guillermo Parada González Hugo Tavares Jon Price Mark Dunning Mark Fernandes Oscar Rueda Sankari Nagarajan Stephane Ballereau Zeynep Kalender Atak
Apologies if we have missed anyone!