Donato Teutonico - ggplot2 Essentials

Donato Teutonico has received his PharmD degree from the University of Turin, Italy, where he specialized in chemical and pharmaceutical technology, and his PhD in pharmaceutical sciences from Paris-South University, France. He has several years of experience in the modeling and simulation of drug effects and clinical trials in industrial and academic settings. Donato has contributed to numerous scientific projects and publications in international journals. In his work, he has been extensively using R for modeling, data analysis, and data visualization.

He is the author of two R packages for pharmacometricscts-template and panels-for-pharmacometricsboth of which are available on Google Code. He has also been a reviewer for Packt Publishing and is the author of Instant R Starter , Packt Publishing .

I would like to thank my beautiful wife, Raquel, and my son, Leonardo, for all their help and their joyful support in my private and professional life.

Juanjo Abellan is a mathematician and statistician by training. He has more than 20 years of experience as an applied statistician. He has held positions in public offices, academia, and industry in Spain, the UK, and Germany. He has authored and coauthored more than 30 articles that have been published in scientific journals. His current main interests include the application of Bayesian statistics in drug development, statistical methods for handling missing data in longitudinal clinical trials, and adaptive designs. He has been using R intensively since the late 1990s.

Niels W. Hanson has a BSc in computer science and a PhD in bioinformatics from the University of British Columbia, where he currently studies metagenomics and microbial ecology in the Steven J. Hallam Laboratory. He has had much experience in the analysis of large genomic datasets from human, aquatic, and terrestrial environments and has extensively utilized the R environment and ggplot2 in his research. His other research interests include software development, machine learning, data visualization, data mining, parallel algorithms, and distributed computing. Dr. Hanson is a reviewer of Institute of Electrical and Electronics Engineers (IEEE) journals and was an editorial reviewer of Tamara Munzner's Visualization Analysis and Design , a recent textbook on information visualization. He currently resides in Vancouver, British Columbia, where his hobbies include badminton, tennis, and downhill skiing.

Sefa Kilic is a PhD candidate in computational biology at the Department of Biological Sciences, University of Maryland, Baltimore County. He received his bachelor's and master's degrees in computer science from Middle East Technical University, Turkey.

For his graduate studies, he used machine learning, statistics, and information theory methods on large genomic data to understand how bacteria regulate the expression of their genes. He has years of experience in scientific computing and data visualization libraries in the Python and R ecosystems. He is also interested in functional programming.

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Preface

As a very powerful open source language, R is rapidly becoming a standard in the scientific community, particularly for data analysis and data visualization. This is related mainly to the vast availability of library packages, which empower the user to apply this software in virtually any field of scientific research. In relation to data visualization, R provides a rich palette of tools, and among the packages available, ggplot2 is fast becoming one of the more sophisticated and advanced packages. Its use is constantly growing in the community of R users. This increasing interest is particularly related to the ggplot2 capability of creating high-quality plots with a very appealing layout and coding that is sufficiently easy to use.

As a scripting language, R may be difficult to master, but in this book, you will find a large number of examples and tips as well as detailed explanations, which will provide you with all the necessary tools to understand the concepts behind ggplot2 in depth and concretely apply them to solve everyday problems related to data visualization. You will see step-by-step descriptions, ranging from the basic applications of ggplot2 in realizing simple plots up to the realization of more advanced and sophisticated plots. We will also dig into controlling plot details, which will enable you to perform a full customization of the plot you intend to realize. Finally, we will also see more special applications of ggplot2, for instance, regarding how to include map data in plots, realize heatmaps, and realize matrix scatterplots using additional packages based on ggplot2.