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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.
- 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
- No. of pages:
- © Academic Press 2016
- 31st December 2015
- Academic Press
- Hardcover ISBN:
- eBook ISBN:
Dr Thore Egeland is professor of applied statistics at the Norwegian University of Life Sciences. He is also affiliated with the Division of Forensic Genetics at Norwegian Institute of Public Health. His interest in forensic genetics began in 1995 when the collaboration with Petter Mostad started. In recent years the activity has increased as the joint work with Daniel Kling started. In addition to traditional activities, Egeland has been responsible for a large number of courses, most of them in Europe. These courses have been important to understand the relevant problems facing case workers in labs working with forensic genetics.
Norwegian University of Life Sciences, Norway
Daniel Kling holds a PhD in applied statistics, specializing in forensics. His current employment is at the Division of Forensic Services, Norwegian Institute of Public Health, dealing with research within inference of relationships. The author has developed the software FamLink and FamLinkX for linked markers and continued the development of the software Familias. These tools have provided crucial assistance for forensic scientists and have risen to be considered as gold standards in the field. In addition, Dr Kling has been teaching a number of courses focusing on statistical challenges when establishing relationships.
Norwegian Institute of Public Health, Norway
Petter Mostad is associate professor in mathematical statistics at Chalmers University of Technology in Sweden. After graduating from Princeton with a PhD in pure mathematics, his interests have expanded in several directions and now focus on Bayesian inference and modeling, with forensic genetics as an important area of application. He initiated the implementation of the precursor of the Familias program in 1995, and has together with Thore Egeland and later Daniel Kling developed Familias, which is now one of the most used programs world-wide in the area of relationship inference based on DNA data.
Chalmers University of Techonology, Göteborg, Sweden
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