Standard scRNAseq preprocessing workflow with Seurat | Beginner R

In this tutorial we will go over the basics steps of preprocessing for single cell RNA seq data in R using the Seurat package.
With this step-by-step guide you will learn the standard pipeline using the Seurat package, which is very common in transcriptomics analysis. We will go through the basic steps of quality control and filtering, normalisation, identification of highly variable features (genes), clustering and different dimensionality reduction methods (PCA, UMAP…).
Hope you like it!

Link to dataset: https://www.10xgenomics.com/resources...
Step by step explanation: https://biostatsquid.com/scrnaseq-pre...

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Other interesting resources for scRNAseq preprocessing:
A hitchhiker's guide to single-cell transcriptomics and data analysis pipelines: https://www.sciencedirect.com/science...
Amazing step-by-step tutorials and scRNAseq analysis workflows with Bioconductor:
https://www.singlecellcourse.org/scrn...
http://bioconductor.org/books/3.16/OS...