Visualizing Biological Data with ggplot2 : Chapman & Hall/CRC Computational Biology Series - William G. Vilchez
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Visualizing Biological Data with ggplot2

By: William G. Vilchez

Paperback | 31 August 2026 | Edition Number 1

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We are currently living in an era where technology is constantly advancing, which leads to the generation of large volumes and many types of data. Consequently, the ability to transform complex data into clear and attractive visualizations has become essential. Visualizing Biological Data with ggplot2 encourages readers to explore the power of visualization in biology, combining science and art to communicate findings clearly.

The first part of the book begins with a general overview of data visualization and then guides readers through the use of the R language, especially its visualization package called ggplot2. In the second part, the author introduces the creation of different visualizations, from basic graphs and tables to more complex representations such as phylogenetic trees, heat maps, and geographic maps, among others. Subsequently, in the third section, tips and strategies for optimizing the design of your graphs are presented. Finally, the author addresses the creation of interactive visualizations and explains the various options available for exporting and sharing your visualizations.

Features:

⦠Introduction to data visualization

⦠Explains the basics of R and its suite of packages called tidyverse

⦠Tutorial on ggplot2 to create a wide range of graph types

⦠Advice on when to avoid certain types of visualization which can lead to errors or confusion in the interpretation of results

⦠Strategies for customizing charts, ready for publication

⦠Numerous examples based on real biological data, which facilitate the practical application of the concepts learned

With a wide variety of biological examples and practical exercises, allowing readers to consolidate knowledge throughout this book, Visualizing Biological Data with ggplot2 is perfect for experienced students and researchers, while also serving as a graphic guide for anyone wishing to transform their data into visualizations.

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