A short tutorial to help beginners in biostatistics and genomics understand an usual single-cell RNA-sequencing workflow
Hector Roux de Bézieux May 2018
Single-cell RNA-sequencing (scRNA-seq) is a very potent biological tool used for many applications. A far from exhaustive list would include identifying new cell types, finding differentially expressed (DE) genes, and discovering lineages among cells. To get an overview of the principle, see here.
However, the usual framework might seem a little daunting for beginners and, while many well-crafted tutorials exists, they all share the same idea: use a biological dataset as an example. Here, we want to use a dataset that would be more understandable to a broader public to explain the usual steps in scRNA-seq analysis
The data consists of the record of votes of all delegates of the legislature (2012-2017) of the French parliament. Only some basics on data analysis are needed to understand this tutorial. Knowledge of R helps to understand the code but is not necessary to follow along.
To access the tutorial, see here.
Special thanks to Vincent Viers for the initial inspiration of this project. The code used for scraping the data is based on the blog post https://freakonometrics.hypotheses.org/50973.