In R Bioinformatics Cookbook, you will encounter common and not-so-common challenges in the bioinformatics domain using real-world examples.
This book will use a recipe-based approach to help you perform practical research and analysis in computational biology with R. You will gain an understanding of your data through the analysis of Bioconductor, ggplot, and the tidyverse library in bioinformatics. You will be introduced to a number of essential tools in Bioconductor so that you can understand and carry out protocols in RNAseq, phylogenetics, genomics, and sequence analysis. You will also learn how machine learning techniques can be used in the bioinformatics domain. You will develop key computational skills, such as developing workflows in R Markdown and designing your own packages for efficient and reproducible code reuse.
By the end of this book, you'll have a solid understanding of the most important and widely used techniques in bioinformatic analysis, as well as the tools you'll need to work with real biological data.