Applied Statistical Genetics with R

Genetic Association Studies.- Elementary Statistical Principles.- Genetic Data Concepts and Tests.- Multiple Comparison Procedures.- Methods for Unobservable Phase.- Classifcation and Regression Trees.- Additional Topics in High-Dimensional Data Analysis.

From the reviews:

"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

From the reviews:

"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 thoseinterested 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)