single cell rnaseq analysis

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This material is linked to a face-to-face training. It is not intended to be used as e-learning only since it does not contain all the info.

Tools

You need a recent installation of R, RStudio and RTools, together with the following packages:

    • Seurat

    • scater (install via BiocManager::install(‘scater’))

    • ggvenn

    • ggpubr

    • devtools

Data

On the first day we use the data set from Antunes et al., 2021. The data can be downloaded from the brain immune atlas. We use the fourth mouse sample (KO and WT) labeled as Mouse GBM citeSeq. Download the Gene-cell count matrix.

On the second day you bring your own data in the form of a count matrix or a Seurat object (or both).
We cannot process bcl files. Contact us if you have issues obtaining a count matrix.

Slides

    • Slides on Plate-based single cell sequencing by Thomas Eekhout
    • Slides on Long-read single cell sequencing by Robin Boiy
    • Slides on Combining single cell and spatial data by Evelien Van Hamme
    • Slides for the basic R script by Janick Mathys

Scripts and R objects

Links

Course Content

Bar codes and library prep 2 Topics
Sequencing platforms 1 Topic
Lesson Content
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Cell ranger: from reads to counts 1 Topic
Lesson Content
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The data set used in the training
Seurat: Import the counts into R 2 Topics
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Seurat: cluster and visualize cells 5 Topics
Single Cell Transform normalization
Removing noise from the data 4 Topics
Subsets
Annotation
Combination of scRNAseq data with other sc data 4 Topics
Comparing groups of cells 3 Topics

Contributors: Janick Mathys, Niels Vandamme, Irina Matetovici, Thomas Eekhout, Jana Roels, Kevin Verstaen, Ria Roelandt, Jeroen Sajdak, Clint Denolf, Liesbet Martens, Seppe De Winter, Sara Aibar, Ruth Seurinck, Robin Browaeys, Daniele Pittari, Chananchida Sang-aram, Leander Jonckheere, Samantha Zaunz, Darina Abaffyová, Sam Dupont

Created by Janick Mathys