Fr. 134.00

Analysis of Genetic Association Studies

English · Hardback

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Description

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Analysis of Genetic Association Studies is both a graduate level textbook in statistical genetics and genetic epidemiology, and a reference book for the analysis of genetic association studies. Students, researchers, and professionals will find the topics introduced in Analysis of Genetic Association Studies particularly relevant. The book is applicable to the study of statistics, biostatistics, genetics and genetic epidemiology.

In addition to providing derivations, the book uses real examples and simulations to illustrate step-by-step applications. Introductory chapters on probability and genetic epidemiology terminology provide the reader with necessary background knowledge. The organization of this work allows for both casual reference and close study.

List of contents

Introduction to statistics. - Population genetics. - Introduction to epidemiology. - Single-marker analysis for unmatched case-control data. - Single- marker analysis for matched case-control data. - Bayesian analysis for case-control data. - Robust procedures. - Advanced topics I. - Haplotype analysis for case-control data. - Gene- gene interaction. - Advanced topics II. - Genome-wide association studes (GWAS). - Cost -effictient two-stage designs and analyses for GWAS. - Appendix. - References. - Index.

About the author

Gang Zheng is a Mathematical Statistician in the Office of Biostatistics Research, National Heart, Lung and Blood Institute, National Institutes of Health. His research interests include robust procedures, statistical genetics, inference with nuisance parameters, analysis of ordered data, and clinical trials. E-mail: zhengg@nhlbi.nih.gov
Yaning Yang is a professor in the Department of Statistics and Finance at the University of Science and Technology of China. He received his Ph.D. in Statistics from the Rutgers University. His main specialty is statistical genetics and bioinformatics. E-mail: ynyang@gmail.com
Xiaofeng Zhu is a professor in Department of Epidemiology and Biostatistics, Case Western Reserve University. His research focuses on developing statistical methods in the areas of association analysis, rare variant association analysis, population stratification, admixture mapping and searching genetic variants contributing hypertension related traits. He is currently on the editorial board of Genetic Epidemiology. E-mail: xzhu1@darwin.epbi.cwru.edu
Robert Elston, Professor of Epidemiology and Biostatistics at Case Western Reserve University, has been a leader in the field of genetic epidemiology for over forty years, having developed the software package S.A.G.E. (Statistical Analysis for Genetic Epidemiology). He has authored six books on biostatistics and genetic epidemiology prior to this one. E-mail: robert.elston@cwru.edu

Summary

Analysis of Genetic Association Studies is both a graduate level textbook in statistical genetics and genetic epidemiology, and a reference book for the analysis of genetic association studies. Students, researchers, and professionals will find the topics introduced in Analysis of Genetic Association Studies particularly relevant.  The book is applicable to the study of statistics, biostatistics, genetics and genetic epidemiology. 
 
In addition to providing derivations, the book uses real examples and simulations to illustrate step-by-step applications.  Introductory chapters on probability and genetic epidemiology terminology provide the reader with necessary background knowledge.  The organization of this work allows for both casual reference and close study. 

Product details

Authors Robert C. Elston, Yanin Yang, Yaning Yang, Gan Zheng, Gang Zheng, Xiaofeng Zhu, Xiaofeng et al Zhu
Publisher Springer, Berlin
 
Languages English
Product format Hardback
Released 01.03.2012
 
EAN 9781461422440
ISBN 978-1-4614-2244-0
No. of pages 414
Dimensions 163 mm x 244 mm x 30 mm
Weight 780 g
Illustrations XXII, 414 p.
Series Statistics for Biology and Health
Statistics for Biology and Health
Subject Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics

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