Relationship Inference with Familias and R

Relationship Inference in Familias and R discusses the use of Familias and R software to understand genetic kinship of two or more DNA samples. This software is commonly used for forensic cases to establish paternity, identify victims or analyze genetic evidence at crime scenes when kinship is involved. The book explores utilizing Familias software and R packages for difficult situations including inbred families, mutations and missing data from degraded DNA. The book additionally addresses identification following mass disasters, familial searching, non-autosomal marker analysis and relationship inference using linked markers. The second part of the book focuses on more statistical issues such as estimation and uncertainty of model parameters. Although written for use with human DNA, the principles can be applied to non-human genetics for animal pedigrees and/or analysis of plants for agriculture purposes. The book contains necessary tools to evaluate any type of forensic case where kinship is an issue.

• This volume focuses on the core material and omits most general background material on probability, statistics and forensic genetics
• Each chapter includes exercises with available solutions
• The web page familias.name contains supporting material
  

Researchers and practitioners of forensic genetics, as well as students in graduate courses.

• Preface
• Chapter 1: Introduction
  • 1.1 Using This Book
  • 1.2 Warm-Up Examples
  • 1.3 Statistics and the Law
• Chapter 2: Basics
  • 2.1 Forensic Markers
  • 2.2 Probabilities of Genotypes
  • 2.3 Likelihoods and LRs
  • 2.4 Mutation
  • 2.5 Theta Correction
  • 2.6 Silent Allele
  • 2.7 Dropout
  • 2.8 Exclusion Probabilities
  • 2.9 Beyond Standard Markers and Data
  • 2.10 Simulation
  • 2.11 Several, Possibly Complex Pedigrees
  • 2.12 Case Studies
  • 2.13 Exercises
• Chapter 3: Searching for Relationships
  • 3.1 Introduction
  • 3.2 Disaster Victim Identification
  • 3.3 Blind Search
  • 3.4 Familial Searching
  • 3.5 Exercises
• Chapter 4: Dependent Markers
  • 4.1 Linkage
  • 4.2 Linkage Disequilibrium
  • 4.3 Haplotype Frequency Estimation
  • 4.4 Programs for Linked Markers
  • 4.5 Exercises
• Chapter 5: Relationship Inference with R
  • 5.1 Using R
  • 5.2 Exercises
• Chapter 6: Models for Pedigree Inference
  • 6.1 Population-Level Models
  • 6.2 Pedigree-Level Models
  • 6.3 Observational-Level Models
  • 6.4 Computations
  • 6.5 Exercises
• Chapter 7: Parameter Estimation and Uncertainty
  • 7.1 Allele Frequencies
  • 7.2 The Theta-Correction Parameter
  • 7.3 The Lambda Model for Haplotype Frequencies
  • 7.4 Mutations and Mutation Models
  • 7.5 Other Parameters
  • 7.6 Handling “Uncertainty” in LRs
  • 7.7 Exercise
• Chapter 8: Making Decisions
  • 8.1 Some Basic Decision Theory
  • 8.2 LR as a Random Variable
  • 8.3 Exercises
• Glossary for non-biologists
• Bibliography
• Index