Statistical genetics has become a core course in many graduate programs in public health and medicine. Applied Statistical Genetics with R presents fundamental concepts and principles in this emerging field at a level that is accessible to students and researchers with a first course in biostatistics.
Extensive examples are provided using publicly available data and the open source, statistical computing environment, R.
"This book aims at filling a real gap in the literature. [...] After three introductory chapters on basic statistical and genetic concepts and association studies, the book deals with the problems of multiple comparison, unknown phase, and model building and predictions in high dimension: topic choices that I find relevant and stimulating [...] This textbook, then, serves as a starting point for further reading, and this is a great way of introducing statistical genetics problems to a general audience. From this point of view, and in many ways, the book feels like the transcription of lecture notes of an introductory class. This is certainly the way in which many great texts were developed.
- Chiara Sabatti, Journal of Statistical Software, September 2009, Volume 31
"This book provides a gentle introduction to genome-wide association studies (GWAS) within both a theoretical and methodological perspective. It will especially be a useful resource to those interested in the ever growing interdisciplinary approach to 'genetic epidemiology' [...] This new book in the Springer Use R! series certainly fills the lacking R resources on this rapidly evolving field in statistical genetics..."
- Christopher Lalanne, Journal of Statistical Software, September 2009, Volume 31
"Applied Statistical Genetics With R is written at a level accessible to non-experts in statistical genetics. The author does not assume the reader is familiar with statistical techniques and hence introduces techniques s required. Examples are accompanied by R scripts typical of the Use R! book series which encourages hands-on experimentation by the readers. Re-using existing packages is characteristic of open-source software development, such as R, and encourages transparency and reproducibility whole minimizing redundancy. The author invokes functionalities from readily available R packages and provides supplemental R scripts as required. [...] Overall, the book provides a nice [...] introduction to the area of statistical genetics concepts using R."
- American Statistician, August 2010, Vol. 64, No. 3
"This book is addressed to a wide readership. Researcher with medical background will learn about the statistical fundamentals in this field, whereas statisticians will see how established methods can be used in this modern research area. [...] a book written about this topic often has to satisfy particular needs and interests. This is well done in this book. [...] The book is a useful help for researchers and students who are interested in an applied approach to statistical genetics in population-based association studies."
- Daniel Fischer, International Statistical Review, Vol. 78 (1), 2010
- Genetic association studies
- Elementary statistical principles
- Genetic data concepts and tests
- Multiple comparison procedures
- Methods for unobservable phase
- Classification and regression trees
- Additional topics in high-dimensional data analysis
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