lgeistlinger
commented
2 months ago Thanks @spholmes. Here is also where we need to expand and sharpen on pre-requisites based on the comments from @lgatto.
A general statement is provided under https://ccb-hms.github.io/osca-workbench/:
"This tutorial strives to be of interest to the experimental biologists wanting to analyze their data and to the bioinformaticians approaching single-cell data."
In more detail, we list on the same page the following pre-requisites:
-
Familiarity with R/Bioconductor, such as the Introduction to data analysis with R and Bioconductor lesson.
-
Familiarity with the biology of gene expression and scRNA-seq, such as the review article A practical guide to single-cell RNA-sequencing by Haque et.al.
My current hunch is that we declare background on stats such as PCA, t-SNE, UMAP, etc as beneficial but not required, as the course focuses on the application of these concepts. That means while a good understanding of the underlying concepts will be beneficial for analysis and interpretation, a rough intuition of these concepts as eg provided for PCA in Section 4.2 of the OSCA book will be sufficient for getting started.
andrewGhazi
This is usually where we try and insist on the necessary pre-requisites explicitly. For this lesson it might also be the opportunity for providing links to background material which are needed.