While numerous advanced statistical approaches have recently
been developed for quantitative trait loci (QTL) mapping, the
methods are scattered throughout the literature. Statistical
Methods for QTL Mapping brings together many recent statistical
techniques that address the data complexity of QTL mapping.
After introducing basic genetics topics and statistical
principles, the author discusses the principles of quantitative
genetics, general statistical issues of QTL mapping, commonly used
one-dimensional QTL mapping approaches, and multiple interval
mapping methods. He then explains how to use a feature selection
approach to tackle a QTL mapping problem with dense markers. The
book also provides comprehensive coverage of Bayesian models and
MCMC algorithms and describes methods for multi-trait QTL mapping
and eQTL mapping, including meta-trait methods and multivariate
sequential procedures.
This book emphasizes the modern statistical methodology for QTL
mapping as well as the statistical issues that arise during this
process. It gives the necessary biological background for
statisticians without training in genetics and, likewise, covers
statistical thinking and principles for geneticists. Written
primarily for geneticists and statisticians specializing in QTL
mapping, the book can also be used as a supplement in graduate
courses or for self-study by PhD students working on QTL mapping
projects.
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