CRUK_CI_Summer_School_ScRnaSeq_2021

Introduction to single-cell RNA-seq data analysis

23rd - 26th July 2021

Taught remotely

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

Instructors

Outline

In this workshop, you will be learning how to analyse single-cell RNA-seq data.

This will include reading the count data into R, quality control, normalisation, data set integration, clustering and identification of cluster marker genes, differential expression and abundance analyses, and trajectory analysis. You will also learn how to generate common plots for analysis and visualisation of gene expression data, such as TSNE, UMAP and violin plots.

The workshop follows that on bulk RNA-seq analysis that covers read alignment, quality control, quantification against a reference, and gene set testing. These are therefore not included here.

This workshop is aimed at biologists interested in learning how to perform standard single-cell RNA-seq analyses.

We have run this course once and 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.

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

Data sets

Two data sets:

Tentative schedule

Tentative schedule for a 1.5 day course.

(Each 1h session should include a 5 min break before the next session)

Day A 13:30 - 17:30

Day B 09:30 - 17:30