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Principles of Statistical Genomics

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Cover of 'Principles of Statistical Genomics'

Table of Contents

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    Book Overview
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    Chapter 1 Map Functions
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    Chapter 2 Recombination Fraction
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    Chapter 3 Genetic Map Construction
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    Chapter 4 Multipoint Analysis of Mendelian Loci
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    Chapter 5 Basic Concepts of Quantitative Genetics
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    Chapter 6 Major Gene Detection
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    Chapter 7 Segregation Analysis
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    Chapter 8 Genome Scanning for Quantitative Trait Loci
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    Chapter 9 Interval Mapping
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    Chapter 10 Interval Mapping for Ordinal Traits
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    Chapter 11 Mapping Segregation Distortion Loci
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    Chapter 12 QTL Mapping in Other Populations
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    Chapter 13 Random Model Approach to QTL Mapping
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    Chapter 14 Mapping QTL for Multiple Traits
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    Chapter 15 Bayesian Multiple QTL Mapping
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    Chapter 16 Empirical Bayesian QTL Mapping
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    Chapter 17 Microarray Differential Expression Analysis
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    Chapter 18 Hierarchical Clustering of Microarray Data
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    Chapter 19 Model-Based Clustering of Microarray Data
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    Chapter 20 Gene-Specific Analysis of Variances
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    Chapter 21 Factor Analysis of Microarray Data
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    Chapter 22 Classification of Tissue Samples Using Microarrays
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    Chapter 23 Time-Course Microarray Data Analysis
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    Chapter 24 Quantitative Trait-Associated Microarray Data Analysis
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    Chapter 25 Mapping Expression Quantitative Trait Loci
Attention for Chapter 7: Segregation Analysis
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Citations

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Chapter title
Segregation Analysis
Chapter number 7
Book title
Principles of Statistical Genomics
Published by
Springer, New York, NY, January 2013
DOI 10.1007/978-0-387-70807-2_7
Book ISBNs
978-0-387-70806-5, 978-0-387-70807-2
Authors

Shizhong Xu