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.
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