We are in the middle of a revolution. A single cell analysis revolution. Driven by the desire to unlock the heterogeneity of tissues, methods to profile the transcriptomes of single cells have exploded onto the scene in recent years. Such approaches leverage RNA-sequencing of thousands of single cells (scRNA-seq) to provide a picture of cell types and states that is unprecedented in history. In parallel to developments in scRNA-seq, -omic data types and volume has expanded at record pace. In order to manage the wave of scRNA-seq data (and other -omic data) that abounds, it is critical that investigators of the future have the skills required to analyze these types of data.

There are two major goals of this module: to introduce you to the R programming language/environment and for you apply your new skills in R to analyze scRNA-seq data. In so doing, using scRNA-seq data as a platform, you will learn in-demand skills that are broadly applicable across industries and -omic data types. Importantly, as described above, you do not need any prior experience in the R programming language. The intent of this course is to enable your entry into the analysis of scRNA-seq data without any prior knowledge. You will be expected to follow along and write/execute R code/analyses in lecture in real time.