Single cell transcriptome workshop

Date 27 - 28 June 2018
Speaker(s) Tim Tickle, Broad Institute, Cambrigde, USA
Fees *academic: 120 CHF   -   for-profit: 600 CHF
Cancellation deadline 20 Jun 2018
City Bern
*academic fee includes non for-profit organisations as well as unemployed participants at the time of application.

This course is co-organised by the CUSO/StarOmics doctoral program. Priority is given to its members, but is open to everyone.


Through a combination of lecture materials and hands-on computational exercises, we explore the use of Trinity for de novo rna-seq assembly and downstream analysis of transcript expression, annotation, differential expression, and interactive data analysis. Although participants will be provided with sample RNA-Seq data sets, they are encouraged to bring their own data for use during the guided studies. We can also include information on applications for cancer transcriptome studies and/or studies of non-model organisms lacking reference genomes.

Single cell transcriptome studies are transforming our knowledge about cell types and cell states, and revealing important variation in gene expression that is otherwise hidden in the context of bulk measurements. Single cell RNA-Seq technology and analysis tools are rapidly evolving, and the complexity of such studies necessitates careful statistical considerations. In this workshop, we provide an overview of the sequencing technologies and experimental methods that make possible single cell transcriptome sequencing. Through hands-on activities with single cell RNA-Seq data, we explore analysis methods available for exploring the variation in transcript expression among cells, define clusters of related cells, and identify characteristics of cell types that are relevant to their biological function.

Learning objectives

The overall theme of this course will center on how single-cell RNA-Seq is different than population based RNASeq and, due to those differences, how analysis methodology differs. Participants will:

  • have an understanding of how sequence data is generated using the most common single-cell RNA-Seq assays.

  • form an intuition on how single-cell RNA-Seq expression data is different and how that affects the selection of methodology for analysis.

  • use popular R libraries to perform quality control, plotting, and analysis targeting both cell heterogeneity and genes that may discriminate those groups.


Knowledge / competencies

Attendees should already be familiar with the basic terms and concepts of genetics and genomics.


Attendees should bring their own laptop computers.

For the practical tutorial, basic familiarity with the command line environment is required. Basic knowledge in R-statistics is recommended but not mandatory.

Prior to the course, please download the Integrative Genome Viewer (IGV).


Application is closed.

There are no registration fees for members of Staromics. For other academics, the fees are 120 CHF. This includes course content material and coffee breaks.

Deadline for registration and free-of-charge cancellation is set is set to 20/06/2018. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to our general conditions.

You will be informed by email of your registration confirmation.

Venue and Time

Universität Bern, Hochschulstrasse 4, room Nr. 028 / EG West.

Additional information

Coordination: Staromics and SIB Training

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