• About the course

    Course contents

    In this course, you will learn how to analyse single-cell RNA-seq data using the Seurat single cell tools integrated in the easy-to-use Chipster software. The exercises and course data are based on the Seurat guided analyses "Guided tutorial - 2700 PBMCs" and "Stimulated vs Control PBMCs".

    You will learn the following topics, and how to perform these steps in the Chipster software:

    • tSNE plot showing how cells (dots) are clusteredperform quality control and filter out low quality cells
    • normalize gene expression values
    • scale data and remove unwanted sources of variation
    • select hihgly variable genes
    • perform dimensionality reduction (PCA, tSNE, UMAP, CCA)
    • cluster cells
    • find marker genes for a cluster
    • integrate two samples
    • find conserved cluster marker genes for two samples
    • find genes which are differentially expressed between two samples in a cell type specific manner
    • visualize genes with cell type specific responses in two samples

    Learning objectives

    After this course you should be able to:

    • use the Seurat tools available in Chipster to undertake basic analysis of 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, RNA-seq, clustering, aligning cells, cluster markers


    Links to material
    The relevant material is linked in each course section. Here are some quick links:


    Practicalities
    Each section of this course contains lecture videos, hands-on exercises and questions/tasks. The tasks can be used to confirm that you have reached the learning goals. You can use the Q&A Forum below to ask questions regarding the course topics or the exercises. Once you have finished all the tasks, you can download a course certificate with a unique course identifier. You can follow your progress with the progress bar on the right. The estimated time to complete the course is 2-3 days. In the certificate we recommend granting 1 credit (ECTS) for the course. In practical matters, please contact event-support (at) csc.fi, and in content related questions, chipster (at) csc.fi.
  • In this section, you will learn how to use the Chipster software, and where to find support and more information.

    Chipster is an easy-to-use graphical analysis software for high-throughput data such as RNA-seq and single cell RNA-seq. Chipster contains over 450 analysis tools and a collection of reference genomes. Chipster runs on your web browser, and the actual analysis jobs use CSC's powerful cloud environment. 

    You don't need to know about command line usage, R or Python to get started, and any laptop with a browser and decent internet connection will do. So to get started, all you need are credentials! If you are working, studying or otherwise affiliated to a Finnish university or research institute, you can log in to Chipster with your Haka or Virtu account, or request a CSC user account. If this is not the case, you can ask for a 3-week evaluation account or purchase a one-year user account to CSC's Chipster server. The Chipster server is also available for download as a virtual machine image free of charge. More information about getting Chipster user account.

    First, watch the Chipster 101 video and check the Chipster quick tour below 

    (please give some time for the video to load in order to have a sharp image).


    Make sure that you have Chipster credentials to do the exercises. 

    You can log in to Chipster with your Haka or Virtu account, or with your CSC account. You can also request a 3-week evaluation account.

    Next, please go through these exercises:
    1. Open Chipster: Go to https://chipster.csc.fi/, click on Launch Chipster (use the web Chipster v4) and log in. 
    2. Open training sessionClick Sessions and select the session course_single_cell_RNAseq_Seurat under Training sessions.


    Finally, answer the quiz and question below.
2. Introduction to scRNA-seq