TUM Library

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Cover; Half Title; Title Page; Copyright Page; Contents; Foreword; Preface; Acknowledgments; Authors; 1. An Introduction and Review of DNA Profile Interpretation; 1.1 A Very Basic Review of a DNA Profile; 1.2 Thresholds; 1.3 Mixture Interpretation; 1.4 The Clayton Rules; 1.5 CPI; 1.6 RMP; 1.7 A Three-Allele Example; 1.8 Higher-Order and Complex Mixtures; 1.9 Conclusion and the Case for Probabilistic Genotyping; 2. An Introduction to Statistics and Proposition Setting; 2.1 Probability; 2.2 Derivation of Bayes' Theorem; 2.3 Odds Form of Bayes' Theorem; 2.4 Principles of Evidence Interpretation

2.5 Setting Propositions2.6 The Likelihood Ratio; 2.7 Representing the Weight of Evidence and the Verbal Scale; 2.8 The Prosecutor and Defense Attorney's Fallacies; 2.9 Conclusion; 2.10 Practice Examples for the Reader; 3. Assigning the LR: Single-Source Examples and Population Genetic Models; 3.1 Population Parameters and Sampling Estimates; 3.2 Heterozygote Single-Source LR; 3.3 Homozygote Single-Source LR; 3.4 Theory -- Population Genetic Models; 3.5 Product Rule; 3.6 NRC II 4.1; 3.7 NRC II 4.2 (Balding and Nichols Formulae); 3.8 Theory -- Theta

3.9 Application of the Population Genetic Model to Single-Source Examples3.10 Theory -- Data below the Analytical Threshold (Dropout); 3.11 Drop-In; 3.12 Full-Profile Example; 3.13 Conclusion; 3.14 Practice Examples for the Reader; 4. Application of the Binary LR for Mixtures; 4.1 Two-Person Mixture with Conditioning; 4.2 Application of NRC II Recommendation 4.2 to Mixtures; 4.3 Two-Person Mixture without Conditioning; 4.4 Two-Person Resolvable Mixture; 4.5 Two-Person Partially Resolvable Mixture; 4.6 Two-Person Unresolvable Mixture; 4.7 Two-Person Unresolvable Mixture (Alleles below ST)

4.8 Three-Person Mixture Example4.9 Conclusion; 4.10 Practice Examples for the Reader; 5. LRs Considering Relatives as Alternate Contributors; 5.1 Theory (Identity by Descent Coefficients); 5.2 Single-Source LR Examples: Heterozygote; 5.3 Single-Source Examples: Homozygote; 5.4 Mixed DNA Profile Example; 5.5 Incorporating Subpopulation Correction; 5.6 Conclusion; 5.7 Practice Examples for the Reader; 6. Probabilistic Genotyping: Semicontinuous Models; 6.1 Probabilistic Methods of Interpretation; 6.2 Underlying Concepts; 6.3 Nomenclature; 6.4 Semicontinuous Methods: Single-Source Examples

6.5 Semicontinuous Methods: Mixture Example6.6 Application of the Balding and Nichols Formulae; 6.7 Conclusion; 6.8 Practice Examples for the Reader; 7. Probabilistic Genotyping: Continuous Models; 7.1 Theory; 7.2 Worked Examples; 7.3 Conclusion; 7.4 Practice Examples for the Reader; 8. Considerations on Validation of Probabilistic Genotyping Software; 8.1 SWGDAM and ISFG Recommendations; 8.2 Specificity and Sensitivity Experiments; 8.3 Precision; 8.4 Effect of Changing the Number of Contributors; 8.5 Effect of Varying Propositions; 8.6 Conclusion; Appendix 1: Allele Frequencies

Appendix 2: Model Answers

DNA testing and its forensic analysis are recognized as the gold standard in forensic identification science methods. However, there is a great need for a hands-on step-by-step guide to teach the forensic DNA community how to interpret DNA mixtures, how to assign a likelihood ratio, and how to use the subsequent likelihood ratio when reporting interpretation conclusions. Forensic DNA Profiling: A Practical Guide to Assigning Likelihood Ratios will provide a roadmap for labs all over the world and the next generation of analysts who need this foundational understanding. The techniques used in forensic DNA analysis are based upon the accepted principles of molecular biology. The interpretation of a good-quality DNA profile generated from a crime scene stain from a single-source donor provides an unambiguous result when using the most modern forensic DNA methods. Unfortunately, many crime scene profiles are not single source. They are described as mixed since they contain DNA from two or more individuals. Interpretation of DNA mixtures represents one of the greatest challenges to the forensic DNA analyst. As such, the book introduces terms used to describe DNA profiles and profile interpretation. Chapters explain DNA extraction methods, the polymerase chain reaction (PCR), capillary electrophoresis (CE), likelihood ratios (LRs) and their interpretation, and population genetic models--including Mendelian inheritance and Hardy-Weinberg equilibrium. It is important that analysts understand how LRs are generated in a probabilistic framework, ideally with an appreciation of both semicontinuous and fully continuous probabilistic approaches. KEY FEATURES:The first book to focus entirely on DNA mixtures and the complexities involved with interpreting the results Takes a hands-on approach offering theory with worked examples and exercises to be easily understood and implementable by laboratory personnel New methods, heretofore unpublished previously, provide a means to innovate deconvoluting a mixed DNA profile, assign an LR, and appropriately report the weight of evidence Includes a chapter on assigning LRs for close relatives (i.e., It's not me, it was my brother), and discusses strategies for the validation of probabilistic genotyping software Forensic DNA Profiling fills the void for labs unfamiliar with LRs, and moving to probabilistic solutions, and for labs already familiar with LRs, but wishing to understand how they are calculated in more detail. The book will be a welcome read for lab professionals and technicians, students, and legal professionals seeking to understand and apply the techniques covered.

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