SingleR EASY TUTORIAL: step-by-step cell type annotation in R

In this tutorial I will explain how to do cell type annotation with the R package SingleR. After a brief introduction to reference-based automatic cell type annotation and SingleR, we will go step by step through the workflow, including preparing our input data, running SingleR, interpreting the results and some tips and tricks to get the most out of SingleR. For this tutorial, I’ll be using RStudio, and you’ll need the packages SingleR, tidyverse. I’ll also use a reference dataset from the package celldex().
You will learn how to:
- get normalised counts from your Seurat object
- prepare a reference dataset for SingleR
- interpret SingleR's cell type predictions (deltas and pruned labels)
- plot the cell types
- add your cell types to your original Seurat object
And as always, you can find the code I am using in this tutorial at biostatsquid.com, where you can also find a step by step explanation of the code. For this tutorial you will need R, or Rstudio, and you will need to install the package listed above.
Hope you like it!
biostatsquid.c...
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Other interesting resources for cell type annotation:
SingleR (Bioconductor): bioconductor.o...
SingleR (publication): github.com/dvi...
Automatic methods in scRNAseq cell type annotation: www.sciencedir...

[@70shahin]

liked and saved for watching later tomorrow after my pharma exam :)

[@HH-ew5pd]

Thanks for the wonderful video! I'm interested in marker-based method. Hope to see the video soon!!:)

[@mihacerne7313]

Squid squad unite