The single cell RNAseq with Seurat workshop will include a brief overview of scRNAseq preprocessing and technologies and analysis of a PMBC dataset in Seurat, an R program for analyzing single cell datasets. We will go through quality control, normalization, principal component analysis, and clustering, as well as visualizing datasets and marker gene expression of a single PBMC dataset and a treated vs control experiment provided by the creators of  the Seurat package, with additional commentary on real-world experimental concerns. This workshop aims to help researchers gain greater understanding and control of their data, including looking up expression of genes of interest, choosing analysis parameters,  contrasting different libraries, genotypes (WT/KO) or treatments, and producing figures for publication. Note that we will use the newest version of Seurat, v3, which will be released on April 16th, 2019 (although it has been available for several months). Pre-class setup instructions will be sent to registrants a few days before class.

NOTE: This is NOT an Intro R class and REQUIRED prerequisites include working knowledge of with R/RStudio, with additional experience recommended with ggplot2 and/or Intro to RNAseq.