Statistical Methods for QTL Mapping: 1st Edition (Hardback) book cover

Statistical Methods for QTL Mapping

1st Edition

By Zehua Chen

Chapman and Hall/CRC

308 pages | 28 B/W Illus.

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Hardback: 9781439868300
pub: 2013-11-01
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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.


"This book can be very useful for young researchers working on QTL mapping analysis. No a priori training in genetics or statistics is required."

Mathematical Reviews, June 2015

"… a good reference for advanced graduate students and researchers working on statistical genetics research. … The book can be used as an advanced reference tool or to supplement a textbook … I found the book’s discussion of various techniques and analytical tools in QTL mapping particularly appealing. The book is unique in terms of the breadth and depth of its statistical treatment in QTL mapping. … The author also provides R code. … Researchers working in statistical genetics with a particular focus on QTL mapping will find this book valuable. It can also help researchers working in other fields to identify potential research topics and begin working in this exciting field."

Journal of the American Statistical Association, June 2015

"… the clear writing style and careful development of ideas by the author make it possible to understand the gist of the theoretical aspects of statistical methods for QTL mapping. … important background knowledge and theoretical elements are clearly explicated. Also, the book spends a substantial part on explaining the estimation algorithms for presented methods; readers who are interested in developing computer codes related to the methods can benefit from the book. … good study material for a graduate course on advanced quantitative genetics. … the book is a useful addition to the field of quantitative genetics and can help students and researchers to understand the advanced statistical methods used for QTL mapping."

Biometrics, December 2014

Table of Contents

Biological Background

A Brief Sketch of the History of Genetics and Mendel’s Pea Plant Experiments

Basic Elements of Genetics

Cell Division, Crossover and Recombination

Gene Expression

Genetic Maps and Mapping Functions

Experimental Crosses

Selected Topics in Statistics

Population and Distribution

Random Variable, Samples, Statistics and Related Distribution


Hypothesis Testing

Linear and Generalized Linear Models

Mixture Models and EM Algorithm

Bayesian Analysis

Samplers for Markov Chain Monte Carlo Simulation

An Overview on Feature Selection with Small-n-large-p Models

Model Selection Criteria for Small-n-large-p Models

Quantitative Genetics and General Issues on QTL Mapping

Distributional Features of Genetic Quantitative Traits

Genetic Values and Variances

Statistical Models with Known QTL Genotypes

Conditional Probabilities of Putative QTL Genotypes Given Markers

QTL Mapping Data

One-Dimensional Mapping Approaches

QTL Mapping by Single-Marker Analysis

Single Interval Mapping

Composite Interval Mapping

Determination of Threshold Values

Determination of Sample Sizes

Selective Genotyping

Multiple Interval Mapping

Gaussian Mixture Models for QTL Mapping

An EM Algorithm for Gaussian Mixture Models

Mixture Generalized Linear Models

General EM Algorithms for Mixture Generalized Linear Models

Multiple Interval Mapping Procedures

Example: The Analysis of Radiata Pine Data

Multiple Interval Mapping with Polytomous Traits

Multiple Interval Mapping of Traits with Spike Distributions

QTL Mapping with Dense Markers

Feature Selection Methods for QTL Mapping

QTL Mapping with Consideration of QTL Epistatic Effects

Bayesian Approach to QTL Mapping

The Framework of the Bayesian Approach to QTL Mapping

Bayesian QTL Mapping with Inbred Line Cross Data

Bayesian QTL Mapping for Outbred Offsprings

Bayesian QTL Mapping for Ordinal Polytomous Traits

Multi-Trait QTL Mapping and eQTL Mapping

Multi-Trait QTL Mapping I: Single-QTL Model Approaches

Multi-Trait QTL Mapping II: Multi-QTL Model Approaches

eQTL Mapping Approaches



About the Series

Chapman & Hall/CRC Mathematical and Computational Biology

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Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General
SCIENCE / Life Sciences / Biology / General
SCIENCE / Life Sciences / Genetics & Genomics