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Analyzing Single Cell RNA sequencing Data in RIntro: The purpose of this document is not to walk through every step in the analysis of single cell data. The intended purpose of this sheet is to provide resources that make an analysis possible. The Dai Lab utilizes R and its packages for the analysis of single cell data. Specifically, we use Seurat, a package developed by the Satija Lab. The Satija Lab provides a guided tutorial that can help a new user understand the workflow and pipeline at their website. Please visit for more information about Seurat and how it works. For someone who has never utilized R for data analysis, there are many online resources that can help. For example, you can visit for an introduction to R. Here you will learn the basic syntax of R and how to use its many inherent functions. Seurat relies on ggplot2, an R package built for visualizations. ggplot2 is much more modular than base R for plotting data, but can take some getting used to. Information about ggplot2 can be found at Because ggplot2 is so widespread in the R community, there are tons of resources to help when making different styles of plots. A good source of help and inspiration can be found at Here, users can find example code that will provide different styles of plots and how to modulate aspects of plots. ................
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