"It is so nice to be able to do the whole workflow in Chipster, compared to the old model, where I had to transfer the tsv file to R-studio and run Seurat there. -- I learned how to use the Seurat tools in Chipster and what all the steps really mean. I learned to check the results after every step to adjust the next steps parameters and to test different PCA plotting tools. I also learned how to find different genes in the clusters and how to visualize them. I never got this far using the R-pipeline. "
Pinja, course participant & PhD student from University of Helsinki
This e-learning course introduces single cell RNA-seq data analysis methods and tools to researchers who are planning to use single cell RNA-seq for their own projects. The course covers the processing of transcript counts from quality control and filtering to dimensional reduction, clustering, and differential expression analysis. In addition, it shows how to do integrated analysis of two samples.
You can login to our e-learning platform, self-register to the course (enrolment key: scRNAseqChipster) and complete it any time in May-August 2021!
- Basics of single cell RNA sequencing
- The free* and user-friendly Chipster software is used in the exercises, so no previous knowledge of Unix or R is required, and the course is thus suitable for everybody who is planning to use single cell RNA-seq.
*You need credentials for Chipster, read more here: https://chipster.csc.fi/access.shtml You can log in with your institutes credentials (Haka, Virtu). We also offer 3-week test credentials, which you can use to complete the course.
After this course you should be able to:
- use the Seurat tools available in Chipster to analyze single cell RNA-seq data
- name and discuss the different steps of single cell RNA-seq data analysis
- understand the advantages and limitations of single cell RNA-seq data analysis in general and in Chipster
Keywords: Chipster, Seurat, single cell sequencing, scRNA-seq, clustering, cluster marker genes
Each section of this course contains learning videos, some hands-on exercises and some questionnaires/tasks. The tasks can be used to confirm that you have reached the learning goals. Once you have finished all the tasks, you can download a course certificate with a unique course identifier. The estimated time to complete the course is 1-3 working days. In the certificate we recommend granting 1 credit (ECTS) for the course.
To self-enrol (key: scRNAseqChipster) in this MOOC course, please visit our e-Lena platform.
To self-enroll you need to first login using your HAKA or ELIXIR AAI credentials. If you do not have one, please contact email@example.com.
Check out the recording from our kick-start webinar for this course: