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Introduction to Bulk RNA-seq data analysis

15, 18, 19 March 2024

In person

Bioinformatics Training Facility, Craik-Marshall Building, Downing Site, University of Cambridge

Instructors

  • Ash Sawle - Bioinformatics Core, Cancer Research UK Cambridge Institute
  • Chandra Chilamakuri - Bioinformatics Core, Cancer Research UK Cambridge Institute
  • Erin Doody - Sainsbury Laboratory, University of Cambridge
  • Ian Tsang - NIAB, Cambridge
  • Puspendu Sardar - Department of Medicine, University of Cambridge

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, we are still improving and learning how to teach it best.
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 adjustments to the course as we go.

Prerequisites

  • 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: Ash, Chandra, Erin, Ian, Puspendu

9:30 - 9:45 - Welcome - in person

9:45 - 10:15 - Introduction to RNAseq Methods - Erin

10:15 - 11:00 Raw read file format and QC - Ian

11:00 - 13:30 Alignment and Quantification of Gene Expression with Salmon - Chandra

13:30 - 14:30 Lunch

14:30 - 15:30 QC of alignment - Chandra

15.30 - 17.30 Data Exploration in R (pdf) - Ash

Day 2

Trainers: Ash, Chandra, Erin, Ian, Puspendu

9:30 - 10:15 Introduction to RNAseq Analysis in R - Ash

10:15 - 13:00 Statistical Analysis of Bulk RNAseq Data - Ash

13:00 - 14:00 Lunch

14:00 - 17:30 - Differential Expression for RNA-seq (pdf) - Chandra

Day 3

Trainers: Ash, Chandra, Erin, Ian, Puspendu

9.30 - 9.45 - Recap of Day 1 and 2 - Chandra

9.45 - 12.30 Annotation and Visualisation of RNA-seq results - Ian / Chandra

12.30 - 13.30 Lunch

13.30 - 16:30 Gene-set testing - Ash

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!