Pedigree Analysis in R

Front Cover
Pedigree Analysis in R
Copyright
Contents
Preface
	Who is this book for?
		What does the book contain?
	What is not in this book?
Biography
Chapter 1:  Prerequisites
	1.1  Genetics
	1.2  Pedigrees
	1.3  R and the ped suite
		1.3.1  How to Get R
		1.3.2  How Much R Do I Need to Know?
		1.3.3  R Code in This Book
		1.3.4  The ped suite Packages
		1.3.5  Getting Help
	1.4  Datasets
Chapter 2:  Pedigrees and Marker Data
	2.1  Creating Pedigrees
		2.1.1  Getting Started
		2.1.2  Tools for Pedigree Building
		2.1.3  A Pedigree Construction Example
		2.1.4  Pedigree Subsets
		2.1.5  The Internal Structure of ped Objects
	2.2  Markers
		2.2.1  Creating Marker Objects
		2.2.2  Attached Markers
		2.2.3  Plotting Pedigrees With Marker Data
		2.2.4  The Internal Structure of Marker Objects
		2.2.5  Accessing and Modifying Markers
		2.2.6  Handling Marker Data
			Applying a Frequency Database
	2.3  Loading Pedigree Data From Files
		2.3.1  Files in ped Format
		2.3.2  Importing Familias Files
Chapter 3:  Coefficients of Relatedness
	3.1  Identity by Descent
	3.2  Inbreeding Coefficients
		3.2.1  Computing f With ribd
	3.3  Kinship Coefficients
		3.3.1  Computing φ With ribd
	3.4  IBD Coefficients of Noninbred Individuals
		3.4.1  Computing \kab With ribd
		3.4.2  The IBD Triangle
		3.4.3  Inseparable Relationships: H–U–G
		3.4.4  Worked Example: 3/4-Siblings
		3.4.5  The IBD Triangle in 3D
	3.5  Identity Coefficients
		3.5.1  Computing \deb With ribd
	3.6  Constructibility of Kappa
Chapter 4:  Realised Relatedness
	4.1  Recombination
		4.1.1  Physical and Genetic Distance
		4.1.2  Recombination Maps
		4.1.3  Recombination Models
			Haldane's model
			χ2 model
	4.2  The ibdsim2 Package
		4.2.1  The ibdsim() Function
		4.2.2  A First Example
		4.2.3  Recombination Maps in ibdsim2
			Built-in maps
			Uniform maps
	4.3  Variation in Realised Coefficients
		4.3.1  First-Cousin Inbreeding
		4.3.2  Some Siblings Are More Equal Than Others
	4.4  Distributions of IBD Segments
		4.4.1  The Importance of Sex
		4.4.2  Separating the Inseparable: H–U–G
	4.5  The Probability of No IBD Sharing
Chapter 5:  Probabilities on Pedigrees
	5.1  Computing Pedigree Likelihoods
		5.1.1  Basic Likelihood Calculations
		5.1.2  The General Likelihood Expression
		5.1.3  The Elston–Stewart Algorithm
		5.1.4  Likelihoods With pedprobr
	5.2  Factors Affecting Performance
		5.2.1  Allele Lumping
		5.2.2  Pedigree Loops
	5.3  Likelihoods With Linked Markers
		5.3.1  Linked Markers in R: Two Markers
		5.3.2  Linked Markers in R: More Than Two Markers
	5.4  Modelling Mutations
		5.4.1  Properties of Mutation Models
			Reversibility
			Lumpability
	5.5  Modelling Deviation From HWE
		5.5.1  Founder Inbreeding
		5.5.2  Theta Correction
Chapter 6:  Kinship Testing
	6.1  Theory and Methods
		6.1.1  Kinship Testing vs. Classical Hypothesis Testing
		6.1.2  The Likelihood Ratio
		6.1.3  Alternatives to LR
		6.1.4  Kinship Testing With forrel
	6.2  Paternity Testing
		6.2.1  Manual Calculation of \LR
		6.2.2  Paternity Testing With forrel
		6.2.3  Direct Computation of \LR
	6.3  A Relationship Riddle
	6.4  Missing Person Identification
		6.4.1  Terminology and Hypotheses
		6.4.2  A Case Study
	6.5  Power Analysis for Kinship Testing
		6.5.1  Exclusion Power
		6.5.2  Inclusion Power
		6.5.3  Power Analysis for Missing Person Cases
	6.6  Dealing With Mutations
Chapter 7:  Inference of Pairwise Relatedness
	7.1  Maximum-Likelihood Estimation of Kappa
		7.1.1  The Likelihood Function
		7.1.2  The Maximum-Likelihood Estimate
		7.1.3  Inadmissible Estimates?
		7.1.4  What About the Kinship Coefficient?
	7.2  Estimation of Identity Coefficients
	7.3  ML Estimation in forrel
		7.3.1  Example: The Relationship Riddle
		7.3.2  Confidence and Uncertainty
	7.4  Quality Control of Pedigree Data
	7.5  Violating the Assumptions
		7.5.1  Inaccurate Allele Frequencies
		7.5.2  Linkage Between Markers
		7.5.3  Inbreeding
Chapter 8:  Pedigree Reconstruction
	8.1  Reconstruction by Pairwise Inference
	8.2  Maximum-Likelihood Pedigree Reconstruction
		8.2.1  Restrictions on the Space of Pedigrees
		8.2.2  Solving the Relationship Riddle
Chapter 9:  Linkage Analysis
	9.1  Theoretical Background
		9.1.1  Hypothesis Testing and the LOD Score
			Example
		9.1.2  Unknown Phase
		9.1.3  Parametric Disease Models
		9.1.4  What Is a Significant LOD Score?
		9.1.5  Multipoint Analysis
		9.1.6  Power Assessment
	9.2  LOD Scores in paramlink2
		9.2.1  An X-Linked Example
		9.2.2  More About the lod() Function
			Disease Models
	9.3  A Case Study
		9.3.1  Power Assessment
		9.3.2  Loading the Data
		9.3.3  Quality Control
		9.3.4  Disease Model and Preliminary Analysis
		9.3.5  Multipoint Analysis
		9.3.6  Liability Classes
		9.3.7  Summarising LOD Peaks
Chapter 10:  Segregation Analysis for Variant Interpretation
	10.1  Background
	10.2  The Bayes Factor
		10.2.1  Using the Bayes Factor in the ACMG Framework
	10.3  Bayes Factors With the segregatr Package
	10.4  A Case Study
Bibliography
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