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.
Additional information
Weight
0.567 kg
Product Properties
Year of Publication
2013
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
Estimation
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
Bibliography
Index
Author
Zehua Chen
ISBN/ISSN
9781439868300
Binding
Hardback
Edition
1
Publisher
CRC Press
Reviews
There are no reviews yet.
Be the first to review “Statistical Methods for QTL Mapping” Cancel reply
Reviews
There are no reviews yet.