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

• • Tutorial for the basic script
  • R markdown file for the basic script
  • Simple basic R script
  • Script to start day 2
  • Script to start day 3
  • Small raw data set as a matrix
  • Clean data set as a matrix
  • Single Cell Experiment after outlier analysis
  • Seurat object before Seurat analysis
  • List of Seurat objects before Seurat analysis
  • Seurat object after Seurat analysis

Links

• • How does Illumina sequencing work? (Lesson of the NGS introduction course)
  • What is a FASTQ file? (Lesson of the NGS introduction course)
  • What is a BAM/SAM file? (Topic of the NGS introduction course)