Quantitative Trait Loci

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. 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