Chemometrics with R: Multivariate Data Analysis in the Natural Sciences and Life Sciences

Springer Science & Business Media
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"Chemometrics with R" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation. Several more specific topics from the area of chemometrics are included in a special section. The corresponding R code is provided for all the examples in the book; scripts, functions and data are available in a separate, publicly available R package. For researchers working in the life sciences, the book can also serve as an easy-to-use primer on R.
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About the author

Ron Wehrens (1966) obtained a PhD in Chemometrics at the Radboud University Nijmegen, The Netherlands. He was a lecturer in Analytical Chemistry at the University of Twente, and later an associated professor at the Radboud University Nijmegen. Since January 2010, he is group leader in Biostatistics and Data Analysis at the Fondazione Edmund Mach in San Michele all'Adige, Italy.
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Additional Information

Publisher
Springer Science & Business Media
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Published on
Jan 20, 2011
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Pages
286
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ISBN
9783642178412
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Best For
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Language
English
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Genres
Mathematics / Probability & Statistics / General
Medical / Biostatistics
Science / Chemistry / General
Science / Life Sciences / Anatomy & Physiology
Science / Life Sciences / Biology
Science / Life Sciences / General
Science / Life Sciences / Molecular Biology
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Content Protection
This content is DRM protected.
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The increasing availability of molecular and genetic databases coupled with the growing power of computers gives biologists opportunities to address new issues, such as the patterns of molecular evolution, and re-assess old ones, such as the role of adaptation in species diversification.

In the second edition, the book continues to integrate a wide variety of data analysis methods into a single and flexible interface: the R language. This open source language is available for a wide range of computer systems and has been adopted as a computational environment by many authors of statistical software. Adopting R as a main tool for phylogenetic analyses will ease the workflow in biologists' data analyses, ensure greater scientific repeatability, and enhance the exchange of ideas and methodological developments. The second edition is completed updated, covering the full gamut of R packages for this area that have been introduced to the market since its previous publication five years ago. There is also a new chapter on the simulation of evolutionary data.

Graduate students and researchers in evolutionary biology can use this book as a reference for data analyses, whereas researchers in bioinformatics interested in evolutionary analyses will learn how to implement these methods in R. The book starts with a presentation of different R packages and gives a short introduction to R for phylogeneticists unfamiliar with this language. The basic phylogenetic topics are covered: manipulation of phylogenetic data, phylogeny estimation, tree drawing, phylogenetic comparative methods, and estimation of ancestral characters. The chapter on tree drawing uses R's powerful graphical environment. A section deals with the analysis of diversification with phylogenies, one of the author's favorite research topics. The last chapter is devoted to the development of phylogenetic methods with R and interfaces with other languages (C and C++). Some exercises conclude these chapters.

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