Introduction to Bulk RNA-seq data analysis
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
- Session 1 - Introduction to RNAseq Methods
- Session 2 - Raw read file format and QC
- Session 3 - Alignment and Quantification of Gene Expression with Salmon
- Session 4 - QC of alignment
- Session 5 - Data Exploration in R (Note: This session does not include a video lecture)
- Session 6 - Introduction to RNAseq Analysis in R .
- Session 7 - Statistical analysis of RNAseq data
- Session 8 - Differential Expression Analysis with DESeq2
- Session 9 - Annotation of RNA-seq results
- Session 10 - Visualisation differential expression results
- Session 11 - Gene set testing
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. Do not attempt to download the entire directory, it is very large. Just download the files as you need them.
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!