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DNA evidence is widely used in the modern justice system. Statistical methodology plays a key role in ensuring that this evidence is collected, interpreted, analysed and presented correctly. This book is a guide to assessing DNA evidence and presenting that evidence in a courtroom setting. It offers practical guidance to forensic scientists with little dependence on mathematical ability, and provides the scientist with the understanding they require to apply the methods in their work. Since the publication of the first edition of this book in 2005 there have been many incremental changes, and one dramatic change which is the emergence of low template DNA (LTDNA) profiles. This second edition is edited and expanded to cover the basics of LTDNA technology. The author's own open-source R code likeLTD is described and used for worked examples in the book. Commercial and free software are also covered.
Autorentext
David J. Balding, University of Melbourne, Australia; and University College London, UK.
Christopher D. Steele, University College London, UK.
Klappentext
A revised and updated edition of this practical guide to assessing DNA evidence and presenting that evidence in a courtroom setting.
Throughout its history, DNA profiling has been controversial. As some controversies are resolved, ever more sensitive profiling techniques introduce new difficulties for the evaluation of evidential weight. Today, usable DNA profiles can be obtained from just a few cells, but such profiles may be affected by a range of stochastic effects. Faced with noisy evidence, courts and commentators tend to focus on the question of whether the technology is reliable, but this concept is too vague to be useful. What matters is whether the evaluation of evidential weight is meaningful to jurors and fair to defendants, allowing sufficiently for different sources of uncertainty.
This book provides a thorough presentation of the basic theory of evidence evaluation for DNA profiles, and aims to equip forensic scientists with practical tools to allow them to present DNA evidence in court effectively. It will also be useful to lawyers who need to understand the meaning of statements of evidential weight for DNA evidence, and to challenge them.
Requiring little expertise in either statistics or population genetics, Weight-of-Evidence for Forensic DNA Profiles:
Inhalt
Preface to the 2nd edition xvi
Preface to the 1st edition xvii
1 Introduction 1
1.1 Weight-of-evidence theory 1
1.2 About the book 3
1.3 DNA profiling technology 4
1.4 What you need to know already 5
1.5 Other resources 6
2 Crime on an island 9
2.1 Warm-up examples 10
2.1.1 People v. Collins (California, 1968) 10
2.1.2 Disease testing: Positive Predictive Value (PPV) 10
2.1.3 Coloured taxis 12
2.2 Rare trait identification evidence 14
2.2.1 The \island" problem 14
2.2.2 A first lesson from the island problem 15
2.3 Making the island problem more realistic 17
2.3.1 The effect of uncertainty about p 17
2.3.2 Uncertainty about N 19
2.3.3 The effect of possible typing errors 19
2.3.4 The effect of searches 20
2.3.5 The effect of other evidence 22
2.3.6 The effects of relatives and population subdivision 23
2.4 Weight-of-evidence exercises 24
3 Assessing evidence using likelihoods 27
3.1 Likelihoods and their ratios 28
3.2 The weight-of-evidence formula 29
3.2.1 Application to the island problem 31
3.3 General application of the formula 32
3.3.1 Several items of evidence 32
3.3.2 The role of the expert witness 34
3.4 Consequences for DNA evidence 35
3.4.1 Many possible culprits 35
3.4.2 Incorporating the non-DNA evidence 35
3.4.3 Relatives 38
3.4.4 Laboratory and handling errors 39
3.4.5 Database searches 40
3.5 Derivation of the weight-of-evidence formula y 42
3.5.1 Bayes Theorem 42
3.5.2 Uncertainty about p and N 43
3.5.3 Grouping the alternative possible culprits 44
3.5.4 Typing errors 45
3.6 Further weight-of-evidence exercises 46
4 Profiling technologies 49
4.1 STR typing 50
4.1.1 Anomalies 53
4.1.2 Contamination 56
4.1.3 Low-template DNA (LTDNA) profiling 56
4.2 mtDNA typing 58
4.3 Y-chromosome markers 59
4.4 X-chromosome markers 59
4.5 SNP profiles 60
4.6 Sequencing 62
4.7 Methylation 62
4.8 RNA 63
4.9 Fingerprints 63
5 Some population genetics for DNA evidence 65
5.1 A brief overview 65
5.1.1 Drift 65
5.1.2 Mutation 68
5.1.3 Migration 69
5.1.4 Selection 70
5.2 FST 71
5.2.1 Population genotype probabilities 73
5.3 A statistical model and sampling formula 74
5.3.1 Diallelic loci 74
5.3.2 Multi-allelic loci 79
5.4 Hardy-Weinberg equilibrium 80
5.4.1 Testing for deviations from HWE 81
5.4.2 Interpretation of test results 86
5.5 Linkage equilibrium 86
5.6 Coancestry 88
5.7 Likelihood-based estimation of FST 90
5.8 Population genetics exercises 92
6 Inferences of identity 95
6.1 Choosing the hypotheses 95
6.1.1 Post-data equivalence of hypotheses 97
6.2 Calculating LRs 99
6.2.1 The match probability 99
6.2.2 Single locus 100
6.2.3 Multiple loci: the \product rule" 103
6.2.4 Relatives of Q 105
6.2.5 Confidence limits 107
6.2.6 Other profiled individuals 108
6.3 Application to STR profiles 109
6.3.1 Values for the pj 109
6.3.2 The value of FST 111
6.3.3 Choice of population 112
6.3.4 Errors 113
6.4 Application to haploid profiles 114
6.4.1 mtDNA profiles 114
6.4.2 Y-chromosome markers 116
6.5 Mixtures 117 6.5.1 V...