Over 90 practical recipes for computational biologists to model and handle real-life data using R
- Use the existing R-packages to handle biological data
- Represent biological data with attractive visualizations
- An easy-to-follow guide to handle real-life problems in Bioinformatics like Next Generation Sequencing and Microarray Analysis
Bioinformatics is an interdisciplinary field that develops and improves upon the methods for storing, retrieving, organizing, and analyzing biological data. R is the primary language used for handling most of the data analysis work done in the domain of bioinformatics.
Bioinformatics with R Cookbook is a hands-on guide that provides you with a number of recipes offering you solutions to all the computational tasks related to bioinformatics in terms of packages and tested codes.
With the help of this book, you will learn how to analyze biological data using R, allowing you to infer new knowledge from your data coming from different types of experiments stretching from microarray to NGS and mass spectrometry.
What you will learn from this book
- Retrieve biological data from within an R environment without hassling web pages
- Annotate and enrich your data and convert the identifiers
- Find relevant text from PubMed on which to perform text mining
- Find phylogenetic relations between species
- Infer relations between genomic content and diseases via GWAS
- Classify patients based on biological or clinical features
- Represent biological data with attractive visualizations, useful for publications and presentations
This book is an easy-to-follow, stepwise guide to handle real life Bioinformatics problems. Each recipe comes with a detailed explanation to the solution steps. A systematic approach, coupled with lots of illustrations, tips, and tricks will help you as a reader grasp even the trickiest of concepts without difficulty.
Who this book is written for
This book is ideal for computational biologists and bioinformaticians with basic knowledge of R programming, bioinformatics and statistics. If you want to understand various critical concepts needed to develop your computational models in Bioinformatics, then this book is for you. Basic knowledge of R is expected.