Here will be a general guide to single cell transcriptomic analysis. This is a collection of resources we've found useful when analyzing scRNA data. We also have an scRNA workshop (coming soon) and analysis pipelines (coming soon) on the website.
Guides and Vignettes
Single Cell Best Practices: an online book intended to guide beginners and experienced professionals in the best practices for analyzing scRNA data. This is a fantastic resource that covers most (if not all) aspects of scRNA analysis. The provided code in this guide uses Python, unlike the majority of the shared resources.
Seurat Guides: Seurat is the go-to package when analyzing single-cell data in R and there is great documentations and guides to run a variety of different analyses.
A Guide to Analyzing Single-cell Datasets: a useful guide walking through a scRNA analyses using R.
Videos:
Intro to scRNA-seq with Seurat: a guided walkthrough of Seurat's introduction vignette from the UofM Data Analysis Networking Group! (DANG!)
Introduction to single-cell RNA-seq and Seurat: the first in a series of videos using Seurat to analyze scRNA.