Analysis of single cell RNA-seq data (IN-PERSON)

Prerequisites

Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). Even though scRNA-seq makes it possible to address problems that are intractable with bulk RNA-seq data, analysing scRNA-seq is also more challenging.

In this course we will be surveying the existing problems as well as the available computational and statistical frameworks available for the analysis of scRNA-seq.

If you do not have a University of Cambridge Raven account please book or register your interest here.

• ♿ The training room is located on the first floor and there is currently no wheelchair or level access.
• Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
• Attendance will be taken on all courses and a charge is applied for non-attendance, including for University of Cambridge students. After you have booked a place, if you are unable to attend any of the live sessions, please email the Bioinfo Team.
• Further details regarding eligibility criteria are available here.
• Guidance on visiting Cambridge and finding accommodation is available here.

• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals

Essential

• Basic understanding of high-throughput sequencing technologies.
  • Watch this iBiology video for an excellent overview.
• A working knowledge of the UNIX command line (course registration page).
  • If you are not able to attend this prerequisite course, please work through our Unix command line materials ahead of the course (up to section 7).
• A working knowledge of R (course registration page).
  • If you are not able to attend this prerequisite course, please work through our R materials ahead of the course.

Desirable

• Experience with analysis of bulk RNA-seq data is strongly recommended (course registration page).
• A working knowledge of running analysis on High Performance Computing (HPC) clusters (course registration page).

Bioinformatics, Data handling, Data mining, Data visualisation, Functional genomics, Transcriptomics

After this course you should be able to:

• Know about different single-cell sequencing technologies available nowadays, their pros and cons and which you may want to use for your experiments
• Process raw single-cell sequencing data and assess the quality of your data
• Normalise scRNA-seq data
• Visualise the data and apply dimensionality reduction
• Apply methods for batch correction and data integration
• Identify groups of similar cells by clustering and identify marker genes to differentiate them
• Apply differential expression between conditions

During this course you will learn about:

• Different scRNA-seq technologies and what kind of data you obtain from each
• Processing raw sequencing data from the commonly-used 10x Chromium platform using cellranger and the Loupe browser for exploratory analysis of the data. Preparing reference genomes for mapping with cellranger.
• Use several R/Bioconductor packages for downstream analysis of scRNA-seq data, including: data normalization, correction for batch effects, dimensionality reduction methods (PCA, t-SNE and UMAP), cell clustering and differential expression analysis.

Presentation and demonstrations

• Free for registered University of Cambridge students
• £ 60/day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 60/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 120/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

3

A number of times per year

• Introduction to working with UNIX and bash (IN-PERSON)
• Introduction to R for Biologists (IN-PERSON)
• Analysis of bulk RNA-seq data (IN-PERSON)
• High Performance Computing: An Introduction (IN-PERSON)
• Extracting biological information from gene lists (IN-PERSON)