Relationship Inference with Familias and R

Relationship Inference with Familias and R

Statistical Methods in Forensic Genetics

1st Edition - December 24, 2015
This is the Latest Edition
  • Authors: Thore Egeland, Daniel Kling, Petter Mostad
  • Hardcover ISBN: 9780128024027
  • eBook ISBN: 9780128026267

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Description

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.

Key Features

  • 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

Readership

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

Table of Contents

    • 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

Product details

  • No. of pages: 256
  • Language: English
  • Copyright: © Academic Press 2015
  • Published: December 24, 2015
  • Imprint: Academic Press
  • Hardcover ISBN: 9780128024027
  • eBook ISBN: 9780128026267

About the Authors

Thore Egeland

Thore Egeland
Thore Egeland is a professor of statistics at the Norwegian University of Life Sciences. He has worked in many areas including geostatistics, medicine, and reliability, and he and Petter Mostad started the Familias project. He has coauthored more than 100 scientific papers in forensic genetics. Currently, his research focuses on statistical methods applied to forensic genetics.Thore Egeland is a professor of statistics at the Norwegian University of Life Sciences. He has worked in many areas including geostatistics, medicine, and reliability, and he and Petter Mostad started the Familias project. He has coauthored more than 100 scientific papers in forensic genetics. Currently, his research focuses on statistical methods applied to forensic genetics.

Affiliations and Expertise

Norwegian University of Life Sciences, Oslo, Norway

Daniel Kling

Daniel Kling
Daniel Kling holds a PhD in biostatistics and is the author of several publications in forensic genetics including the book "Relationship inference using Familias and RdStatistical methods in Forensic Genetics". His current research includes topics such as linked markers in relationship inference, software developments, and population genetics. He is the developer of the software Familias, FamLink, and FamLinkX, all of which are widely used in forensics.

Affiliations and Expertise

National Board of Forensic Medicine, Link€oping, Sweden Oslo University Hospital, Department of Forensic Sciences, Oslo, Norway

Petter Mostad

Petter Mostad
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.

Affiliations and Expertise

Chalmers University of Techonology, Göteborg, Sweden

Latest reviews

(Total rating for all reviews)

  • Michele R. Tue May 15 2018

    Good interesting book to deal

    Good interesting book to deal with relationship biostatistics