A Guide to QTL Mapping with R/qtl / by Karl W. Broman, Saunak Sen.

Por:

Broman, Karl W [autor]

Colaborador(es):

Tipo de material: Texto

TextoSeries Statistics for Biology and HealthEditor: New York, NY : Springer New York, 2009Descripción: xii, 400 páginas 151 ilustraciones, 87 ilustraciones en color. recurso en líneaTipo de contenido:

texto

Tipo de medio:

computadora

Tipo de portador:

recurso en línea

ISBN:

9780387921259

Formatos físicos adicionales: Edición impresa:: Sin títuloRecursos en línea:

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Contenidos:

Importing and simulating data -- Data checking -- Single-QTL analysis -- Non-normal phenotypes -- Experimental design and power -- Working with covariates -- Two-dimensional, two-QTL scans -- Fit and exploration of multiple-QTL models -- Case study I -- Case study II.

Resumen: Quantitative trait locus (QTL) mapping is used to discover the genetic and molecular architecture underlying complex quantitative traits. It has important applications in agricultural, evolutionary, and biomedical research. R/qtl is an extensible, interactive environment for QTL mapping in experimental crosses. It is implemented as a package for the widely used open source statistical software R and contains a diverse array of QTL mapping methods, diagnostic tools for ensuring high-quality data, and facilities for the fit and exploration of multiple-QTL models, including QTL x QTL and QTL x environment interactions. This book is a comprehensive guide to the practice of QTL mapping and the use of R/qtl, including study design, data import and simulation, data diagnostics, interval mapping and generalizations, two-dimensional genome scans, and the consideration of complex multiple-QTL models. Two moderately challenging case studies illustrate QTL analysis in its entirety. The book alternates between QTL mapping theory and examples illustrating the use of R/qtl. Novice readers will find detailed explanations of the important statistical concepts and, through the extensive software illustrations, will be able to apply these concepts in their own research. Experienced readers will find details on the underlying algorithms and the implementation of extensions to R/qtl. There are 150 figures, including 90 in full color. Karl W. Broman is Professor in the Department of Biostatistics and Medical Informatics at the University of Wisconsin-Madison, and is the chief developer of R/qtl. Saunak Sen is Associate Professor in Residence in the Department of Epidemiology and Biostatistics and the Center for Bioinformatics and Molecular Biostatistics at the University of California, San Francisco.

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Springer eBooks

Quantitative trait locus (QTL) mapping is used to discover the genetic and molecular architecture underlying complex quantitative traits. It has important applications in agricultural, evolutionary, and biomedical research. R/qtl is an extensible, interactive environment for QTL mapping in experimental crosses. It is implemented as a package for the widely used open source statistical software R and contains a diverse array of QTL mapping methods, diagnostic tools for ensuring high-quality data, and facilities for the fit and exploration of multiple-QTL models, including QTL x QTL and QTL x environment interactions. This book is a comprehensive guide to the practice of QTL mapping and the use of R/qtl, including study design, data import and simulation, data diagnostics, interval mapping and generalizations, two-dimensional genome scans, and the consideration of complex multiple-QTL models. Two moderately challenging case studies illustrate QTL analysis in its entirety. The book alternates between QTL mapping theory and examples illustrating the use of R/qtl. Novice readers will find detailed explanations of the important statistical concepts and, through the extensive software illustrations, will be able to apply these concepts in their own research. Experienced readers will find details on the underlying algorithms and the implementation of extensions to R/qtl. There are 150 figures, including 90 in full color. Karl W. Broman is Professor in the Department of Biostatistics and Medical Informatics at the University of Wisconsin-Madison, and is the chief developer of R/qtl. Saunak Sen is Associate Professor in Residence in the Department of Epidemiology and Biostatistics and the Center for Bioinformatics and Molecular Biostatistics at the University of California, San Francisco.

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