Synopses & Reviews
Statistical methods for the analysis of quantitative trait locus (QTL), in conjunction with genome-wide screening technologies, are today yielding exciting results in the study of human disease, experimental organisms, and agriculture. In Quantitative Trait Loci: Methods and Protocols, Drs. Nicola Camp and Angela Cox have assembled a highly experienced panel of statistical geneticists who demonstrate in a step-by-step fashion how to use this powerful methodology and associated software for the detection and fine mapping of quantitative trait loci. Writing for the nonmathematician, these experts guide the investigator from the design stage of a project onwards, providing detailed explanations of how best to proceed with each specific analysis, to find and use appropriate software, and to interpret results. Worked examples, citations to key papers, and useful variations and/or extensions to standard methods are included that ease the reader toward understanding and successful studies. Among the cutting-edge techniques presented are QTDT methods, variance components methods, and the Markov chain Monte Carlo method for joint linkage and segregation analysis. Up-to-date and highly practical, Quantitative Trait Loci: Methods and Protocols makes available to nonmathematical investigators a step-by-step guide to the productive use today of all the latest techniques for localizing genes involved in complex quantitative traits.
Synopsis
"...for nonstatistical students, this well-designed book provides 'detailed explanations of how best to proceed with each specific analysis, to find and use appropriate software, and to interpret results," as advertised on its back cover." - American Journal of Human Biology
Synopsis
In Quantitative Trait Loci: Methods and Protocols, a panel of highly experienced statistical geneticists demonstrate in a step-by-step fashion how to successfully analyze quantitative trait data using a variety of methods and software for the detection and fine mapping of quantitative trait loci (QTL). Writing for the nonmathematician, these experts guide the investigator from the design stage of a project onwards, providing detailed explanations of how best to proceed with each specific analysis, to find and use appropriate software, and to interpret results. Worked examples, citations to key papers, and variations in method ease the way to understanding and successful studies. Among the cutting-edge techniques presented are QTDT methods, variance components methods, and the Markov Chain Monte Carlo method for joint linkage and segregation analysis.
Table of Contents
Part I. Mapping Quantitative Trait Loci in Humans Association Studies Jennifer H. Barrett Parametric Linkage Analysis Lyle J. Palmer, Audrey H. Schnell, John S. Witte, and Robert C. Elston Nonparametric Linkage Analysis: I. Haseman-Elston Chad P. Garner Nonparametric Linkage Analysis: II. Variance Components Angela J. Marlow Linkage and Association: The Transmission/Disequilibrium Test for QTLs Mark M. Iles Joint Linkage and Segregation Analysis Using Markov Chain Monte Carlo Methods Ellen M. Wijsman Part II. Mapping Quantitative Trait Loci in Rodents Approaches to the Analysis of QTL Data in Mice, Using the Nonobese Diabetic Mouse as an Example Heather J. Cordell Experimental Designs for QTL Fine Mapping in Rodents Anne Shalom and Ariel Darvasi Approaches to the Analysis of Complex Quantitative Phenotypes and Marker Map Construction Based on the Analysis of Rat Models of Hypertension Dominique Gauguier and Nilesh Samani A Case Study of QTL Analysis in a Mouse Model of Asthma Youming Zhang and William Cookson Part III. Mapping Quantitative Trait Loci in Agricultural Settings QTL Analysis in Plants Shizhong Xu QTL Analysis in Livestock Joao L. Rocha, Daniel Pomp, and L. Dale Van Vleck Index