Introduction to RNA-seq data analysis
1st - 3rd July 2020
Taught remotely
Bioinformatics Training, Craik-Marshall Building, Downing Site, University of Cambridge
Instructors
- Abbi 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
- Dominique-Laurent Couturier - Bioinformatics Core, Cancer Research UK Cambridge Institute
- Jon Price - Miska Group, Gurdon Institute, Cambridge
- Manik Garg - Brazma Group, EBI
- Sankari Nagarajan - School of Biological Sciences, University of Manchester
- Stephane Ballereau - Bioinformatics Core, Cancer Research UK Cambridge Institute
- Zeynep Kalender Atak - Miller Group, Cancer Research UK Cambridge Institute
Outline
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, this is the second time that we will be teaching 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.
Prerequisites
**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
Google Document
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.
Course etiquette
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:
-
Please mute your microphone
-
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.
-
Please ask any general question by typing it into the Google Doc mentioned above
-
During practicals, when you are done, please press the green “Yes” button:
This way we will know when we can move on.
Timetable
As we have taught this course remotely only once before, all times here should be regarded as aspirations
Day 1
9:30 - 9:45 - Welcome!
9:45 - 10:15 - Introduction to RNAseq Methods - Sankari Nagarajan
10:15 - 11:15 Raw read file format and QC - Abbi Edwards
- Introductory slides
- Practical
- Practical solutions
11:15 - 12:45 Short read alignment with HISAT2 - Zeynep Kalender Atak
- Introductory slides
- Practical
- Practical solutions
12:45 - 13:45 Lunch
13:45 - 15:30 QC of alignment - Zeynep Kalender Atak
- Introductory slides
- Practical
- Practical solutions
15:30 - 17:00 Quantification with SubRead - Chandra Chilamakuri
- Introductory slides
- Practical
- Practical solutions
Day 2
9:30 - 10:15 Introduction to RNAseq Analysis in R - Sankari Nagarajan
10:15 - 12:30 - RNA-seq Pre-processing -
Chandra Chilamakuri
- Practical solutions
12:30 - 13:30 Lunch
13:30 - 15:30 Statistical Analysis of Bulk RNAseq Data - Dominique-Laurent
Couturier
- Slides
- Practical (html) (rmd)
15:30 - 17:00 Experimental Design of Bulk RNAseq studies - Sankari Nagarajan
- Slides
- Practical
Day 3
9:30 - 12:15 - Differential Expression for
RNA-seq - Ashley Sawle
- practical solutions
12:15 - 13:15 Lunch
13:15 - 15:30 Annotation and Visualisation of RNA-seq
results - Abbi Edwards
- practical solutions
15:30 - 17:00 Gene-set testing - Stephane Ballereau
- practical solutions
Source Materials for Practicals
The lecture slides and other source materials, including R code and practical solutions, can be found in the course’s Github repository
Extended materials
The materials linked to from this page are somewhat cut down from the complete course that we normally teach. The Extended Materials contain the full course materials and links to additional RNAseq 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.
Additional Resources
Acknowledgements
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.
