Computational Genomics with R

Computational Genomics with R is a book that provides a comprehensive introduction to genomic data analysis using the R programming language. It covers topics from R programming, machine learning, and statistics to the latest techniques in genomic data analysis, with practical and well-documented examples in R. The book is designed for beginners and advanced practitioners in the field of computational genomics, with different starting points depending on the reader's background.

Format: Paperback / softback
Length: 440 pages
Publication date: 09 January 2023
Publisher: Taylor & Francis Ltd

Computational Genomics with R is a comprehensive guide for beginners and advanced practitioners in genomic data analysis. It covers a wide range of topics, including R programming, machine learning, statistics, and the latest techniques in genomic data analysis. The book provides accessible information and explanations, with a strong focus on the genomics context. It offers practical and well-documented examples in R, allowing readers to analyze their data with ease.

As computational genomics is an interdisciplinary field, the book caters to individuals with different backgrounds. Biologists, for instance, can skip sections on basic genome biology and start with R programming, while computer scientists can begin with genome biology.

After completing this book, readers will have a solid foundation in R and be able to apply it to specialized uses in computational genomics. They will be familiar with statistics, supervised and unsupervised learning techniques, data modeling, exploratory analysis of high-dimensional data, genomic intervals, operations, processing, quality checking, sequence analysis, visualization techniques, and analysis of high-throughput sequencing data.

The book also covers various high-throughput sequencing platforms, such as Illumina, PacBio, and Nanopore, and provides insights into their data analysis. Readers will learn about alignment, read counting, genomic feature annotation, and other tasks commonly performed in computational genomics.

Furthermore, the book discusses the importance of reproducibility in genomic data analysis and provides tips and best practices for achieving it. It emphasizes the use of version control systems, such as Git, to track changes and collaborate with others.

In conclusion, Computational Genomics with R is an essential resource for anyone interested in genomic data analysis. It provides a comprehensive and up-to-date introduction to the field, covering both basic and advanced topics. Whether you are a beginner or an experienced practitioner, this book will help you unlock the power of R and apply it to your genomic research.

Weight: 852g
Dimension: 254 x 178 (mm)
ISBN-13: 9780367634605