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[null,"1.","Record Nr.",null,"UNINA9910798064903321"]
[null,null,"Autore",null,"Egeland Thore"]
[null,null,"Titolo",null,"Relationship inference with familias and r : statistical methods in forensic genetics / / Thore Egeland, Daniel Kling, Petter Mostad"]
[null,null,"Pubbl/distr/stampa",null,"London, England : , : Academic Press, , 2016"]
[{"$nulls":4},"©2016"]
[null,null,"ISBN",null,"0-12-802626-X"]
[null,null,"Descrizione fisica",null,"1 online resource (255 p.)"]
[null,null,"Disciplina",null,"363.25"]
[null,null,"Soggetti",null,"Forensic sciences - Research - History"]
[{"$nulls":4},"Forensic sciences - Standards"]
[{"$nulls":4},"R (Computer program language)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Front Cover; Relationship Inference with Familias and R: Statistical Methods in Forensic Genetics; Copyright; Contents; Preface; Acknowledgments; Chapter 1: Introduction; 1.1 Using This Book; 1.2 Warm-Up Examples; 1.3 Statistics and the Law; 1.3.1 Context; 1.3.2 Terminology; 1.3.3 Principles; 1.3.4 Fallacies; Chapter 2: Basics; 2.1 Forensic Markers; 2.2 Probabilities of Genotypes; 2.3 Likelihoods and LRs; 2.3.1 Standard Hypotheses; 2.3.2 The LR; 2.3.3 Identical by Descent and Pairwise Relationships; 2.3.4 Probability of Paternity: W; 2.3.5 Bayes's Theorem in Odds Form; 2.4 Mutation"]
[{"$nulls":4},"2.4.1 Biological Background2.4.2 Mutation Example; 2.4.3 Mutation for Duos; 2.4.4 Dealing with Mutations in Practice; 2.5 Theta Correction; 2.5.1 Sampling Formula; 2.6 Silent Allele; 2.7 Dropout; 2.8 Exclusion Probabilities; 2.8.1 Random Match Probability; 2.9 Beyond Standard Markers and Data; 2.9.1 X-Chromosomal Markers; 2.9.2 Y-Chromosomal and mtDNA Markers; 2.9.3 DNA Mixtures; 2.10 Simulation; 2.11 Several, Possibly Complex Pedigrees; 2.12 Case Studies; 2.12.1 Paternity Case with Mutation; 2.12.2 Wine Grapes; Prior model for wine grapes; Likelihoods for wine grapes; 2.13 Exercises"]
[{"$nulls":4},"Chapter 3: Searching for relationships3.1 Introduction; 3.2 Disaster Victim Identification; 3.2.1 Identification Process; 3.2.2 Prior Information; 3.2.3 Implementation in Familias; 3.2.4 Extensions; Quick searching; Multiple relatives; 3.3 Blind Search; 3.3.1 Kinship Matching; 3.3.2 Direct Matching; 3.4 Familial Searching; 3.4.1 Implementation; "]
[{"$nulls":4},"3.4.2 *Relatives and Mixtures; 3.4.3 Select Subsets; Top k; LR threshold; Profile centered; Conditional; 3.5 Exercises; Chapter 4: Dependent markers; 4.1 Linkage; 4.1.1 Recombination; 4.1.2 Introduction to Calculations"]
[{"$nulls":4},"4.1.3 Generalization and the Lander-Green Algorithm4.1.4 Extensions; X-chromosomal markers; Mutations; Subpopulation correction; Dropouts and silent alleles; 4.2 Linkage Disequilibrium; 4.2.1 Introduction to Calculations; 4.2.2 *Generalization; Cluster approach; Exact calculations; 4.3 Haplotype Frequency Estimation; 4.4 Programs for Linked Markers; 4.4.1 FamLink; 4.4.2 FamLinkX; 4.5 Exercises; 4.5.1 Autosomal Markers and FamLink; 4.5.2 X-Chromosomal Markers and FamLinkX; Chapter 5: Relationship inference with R; 5.1 Using R; 5.1.1 R Packages for Relationship Inference"]
[{"$nulls":4},"5.1.2 The Familias Package5.2 Exercises; Chapter 6: Models for pedigree inference; 6.1 Population-Level Models; 6.1.1 *Frequency Uncertainty; 6.1.2 *Taking Frequency Uncertainty into Account; 6.1.3 *Population Structure and Subpopulations; 6.1.4 *Haplotype Models; 6.1.5 Population Models for Nonautosomal Markers; 6.2 Pedigree-Level Models; 6.2.1 Mutation Models; The \"\"Equal'' model; The \"\"Stepwise'' model; *Stationary mutation models; *Model based on frequencies; *Stabilizing existing mutation models; 6.3 Observational-Level Models; 6.4 Computations; 6.4.1 Identical by Descent"]
[{"$nulls":4},"Assuming independent markers, two tested persons, and no inbreeding"]
[null,null,null,"Sommario/riassunto","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.--"]