This is somewhat an opinionated guide on using R for computational genomics. It is aimed at wet-lab researchers who wants to use R in their data analysis ,and bioinformaticians who are new to R and wants to learn more about its capabilities for genomics data analysis.
As new high-throughout experimental techniques on the rise, data analysis capabilities are sought-after features for researchers. R, with its statistical heritage, plotting features and rich user-contributed packages is one of the best languages for the task of analyzing data. The book gives a brief introduction on basics of R and later divided to chapters that represent subsets of genomics data analysis.
This resource describes the skills and provides how-tos that will help readers analyze their own genomics data.
You can contribute to the development of this guide using github features such as pull-requests and issue creation.