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Single cell RNA-seq data analysis using R
Date: 18.09.2019 9:00 - 19.09.2019 17:00
Location details: The event is organised at the CSC Training Facilities located in the premises of CSC at Keilaranta 14, Espoo, Finland. The best way to reach us is by public transportation; more detailed travel tips are available.
Language: english-language
lecturers: Bishwa Ghimire (FIMM)
Heli Pessa (University of Helsinki)
Iivari Kleino (University of Helsinki)
Anna Kuosmanen (University of Helsinki)
  • 120 for-finnish-academics
  • 560 for-others

The fee covers all materials and morning and afternoon coffees.

Some of the seats are reserved for Doctoral Program in Biomedicine (DPBM) participants, whose participation fee is covered by the program.

Payment can be made with electronic invoicing, credit card, or direct bank transfer. Note that for electronic invoicing you need the operator and e-invoicing address (OVT code) of your organization. Please also note that invoice reference is needed for electronic invoicing in your organization.

If a cancellation is received five (5) business days prior to the course, the course fee will be refunded with the exception of a handling fee of 10 €. For no-shows and cancellations after the cut of date no refunds will be made. Registration can be transferred to someone else from the same organization without additional charge.

The seats are filled based on a short motivation description in the registration form. Applicants who already have scRNA-seq data are prioritized, and we will do our best to ensure that every research group gets one representative in the course.
Additional Information


New: Slides and exercises (including code) are now available at the course GitLab site. Note that lecture videos from a previous course are also available.

This hands-on course introduces the participants to single cell RNA-seq data analysis concepts and popular tools and R packages.It covers the processing of transcript counts from quality control and filtering to dimensional reduction, clustering, cell type identification, and differential expression analysis.

Please note that you are most welcome to attend also the Single cell transcriptomics symposium in Biomedicum Helsinki 23.9.2019. This event is part of the Single cell course week.

The course is kindly sponsored by the University of Helsinki Doctoral Programme in Biomedicine (DPBM).


Participants need to have


Topics covered:

  • quality control
  • normalization
  • removal of undesired sources of variation
  • choosing variable genes
  • dimensionality reduction
  • clustering
  • differential gene expression analysis
  • integrating different datasets
  • cell type identification


On this course, you will learn:

  • assess the quality of scRNAseq data
  • to control batch effects and other unwanted variation
  • cell clustering and identification
  • differential gene expression analysis
  • choosing the tools for further analyses