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Relationship inference with Familias and R : statistical methods in forensic genetics /

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 invol...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Egeland, Thore (Autor), Kling, Daniel (Autor), Mostad, Petter, 1964- (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Academic Press, an imprint of Elsevier, [2016]
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Egeland, Thore,  |e author. 
245 1 0 |a Relationship inference with Familias and R :  |b statistical methods in forensic genetics /  |c Thore Egeland, Daniel Kling, Petter Mostad. 
264 1 |a London :  |b Academic Press, an imprint of Elsevier,  |c [2016] 
264 4 |c �2016 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
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338 |a online resource  |b cr  |2 rdacarrier 
588 0 |a Online resource; title from PDF title page (EBSCO, viewed January 21, 2016). 
504 |a Includes bibliographical references and index. 
520 |a 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. 
505 0 |a 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 
505 8 |a 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 
505 8 |a 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; 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 
505 8 |a 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 
505 8 |a 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 
650 0 |a Forensic genetics  |x Statistical methods. 
650 2 |a Forensic Genetics  |x methods  |0 (DNLM)D053803Q000379 
650 6 |a G�en�etique l�egale  |0 (CaQQLa)201-0186718  |x M�ethodes statistiques.  |0 (CaQQLa)201-0373903 
650 7 |a MEDICAL  |x Forensic Medicine.  |2 bisacsh 
650 7 |a MEDICAL  |x Preventive Medicine.  |2 bisacsh 
650 7 |a MEDICAL  |x Public Health.  |2 bisacsh 
650 7 |a Forensic genetics  |x Statistical methods.  |2 fast  |0 (OCoLC)fst00931965 
700 1 |a Kling, Daniel,  |e author. 
700 1 |a Mostad, Petter,  |d 1964-  |e author. 
776 0 8 |i Erscheint auch als:  |n Druck-Ausgabe  |a Egeland, Thore. Relationship Inference with Familias and R .  |t Statistical Methods in Forensic Genetics 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780128024027  |z Texto completo