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Analysis of single cell RNA-seq data

22nd June 2016 @ 9:30 am - 5:00 pm


Description: 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.

Materials for this course can be found here.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book by linking here.

Target audience:

  • Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
  • Further details regarding eligibility criteria are available here
  • Further details regarding the charging policy are available here

Duration: 1


Number of sessions: 1

Date Time Venue Trainer
Wed 22 Jun 09:30 – 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site Vladimir Kiselev ,  Martin Hemberg ,  Tallulah Andrews

Format: Presentation and demonstrations

Frequency: A number of times per year


Aims: During this course you will learn about:

  • Normalization and correction for batch effects
  • Identification of differentially expressed genes and regulatory networks
  • Unsupervised hard and soft clustering of cells

Objectives: After this course you should be able to:

  • Normalize scRNA-seq data
  • Visualize the data and apply dimensionality reduction
  • Use available tools for analyzing differential expression
  • Use available methods for clustering

Related courses:

Theme: Specialized Training


22nd June 2016
9:30 am - 5:00 pm
Event Category:


Bioinformatics Training


Bioinformatics Training Room
Craik-Marshall Building, Downing Site
Cambridge, CB2 3AR United Kingdom
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