`R` is a programming language and free software environment for statistical computing and graphics. It's not only a powerful statistical programming language but also the go-to data analysis tool for many computational genomics experts. We will explore how high-dimensional genomics datasets can be analyzed with core R packages and functions.

In this activity, I practiced: - working in RStudio, - editing an R Markdown notebook, - running R code chunks, - inspecting a dataset, - converting a data frame to a matrix, - using the assignment operator `<-`, - indexing rows and columns, - making heatmaps, - scaling data, - changing color palettes, - interpreting clusters and correlations, - and connecting a simple dataset to future cancer biology analyses.