Introduction to Bulk RNA-seq data analysis
12, 19, 26 Nov 2024
In person
Bioinformatics Training Facility, Craik-Marshall Building, Downing Site, University of Cambridge
Instructors
- Ashley Sawle (CRUK Cambridge Institute)
- Betty Wang (Dpt Clinical Neurosciences, University of Cambridge)
- Chandra Chilamakuri (CRUK Cambridge Institute)
- Yuki Ye (Dpt Clinical Neurosciences, University of Cambridge)
- Erin Doody (Sainsbury Laboratory)
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.
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
Timetable
Day 1
Trainers:
9:30 - 9:45 - Welcome! - Bajuna
9:45 - 10:15 - Introduction to RNAseq Methods - Chandra
10:15 - 11:00 Raw read file format and QC - Erin
11:00 - 13:30 Alignment and Quantification of Gene Expression with Salmon - Erin
13:30 - 14:30 Lunch
14:30 - 15:30 QC of alignment - Ash
15.30 - 17.30 Data Exploration in R - Ash
Day 2
Trainers:
9:30 - 10:15 Introduction to RNAseq Analysis in R - Betty
10:15 - 11:30 Statistical Analysis of Bulk RNAseq Data - Betty
11:30 - 17:30 Linear Models in R and DESeq2 (Slides) - Chandra
- Practical - Differential Expression for RNA-seq (pdf) - Chandra
- Linear Models in R and DESeq2 (Worksheet) (pdf)
- DESeq2 results extraction cheatsheet
- practical solutions (pdf)
- live script
13:00 - 14:00 Lunch
Day 3
Trainers:
9:30 - 9:45 - Recap of Day 1 and 2 - Chandra
9:45 - 11:00 Annotation of RNA-seq results - Puspendu
11:00 - 12.30 Visualisation differential expression results - Yuki
12.30 - 13.30 Lunch
13.30 - 16:30 Gene-set testing - Puspendu
Data, software and materials
The lecture slides and other source materials, including R code and practical solutions, can be found in the course’s Github repository
The full data used in the course can be downloaded from dropbox.
Instructions to install software are available from the “Software installation instructions” page.
Extended materials
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.
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.
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 Tom Smith Zeynep Kalender Atak
Apologies if we have missed anyone!