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It has become widely accepted in forensics that, owing to a lack of sensible priors, the evidential value of matching DNA profiles in trace donor identification or kinship analysis is most sensibly communicated in the form of a likelihood ratio (LR). This restraint does not abate the fact that the posterior odds (PO) would be the preferred basis for returning a verdict. A completely different situation holds for Forensic DNA Phenotyping (FDP), which is aimed at predicting externally visible characteristics (EVCs) of a trace donor from DNA left behind at the crime scene. FDP is intended to provide leads to the police investigation helping them to find unknown trace donors that are unidentifiable by DNA profiling. The statistical models underlying FDP typically yield posterior odds (PO) for an individual possessing a certain EVC. This apparent discrepancy has led to confusion as to when LR or PO is the appropriate outcome of forensic DNA analysis to be communicated to the investigating authorities. We thus set out to clarify the distinction between LR and PO in the context of forensic DNA profiling and FDP from a statistical point of view. In so doing, we also addressed the influence of population affiliation on LR and PO. In contrast to the well-known population dependency of the LR in DNA profiling, the PO as obtained in FDP may be widely population-independent. The actual degree of independence, however, is a matter of (i) how much of the causality of the respective EVC is captured by the genetic markers used for FDP and (ii) by the extent to which non-genetic such as environmental causal factors of the same EVC are distributed equally throughout populations. The fact that an LR should be communicated in cases of DNA profiling whereas the PO are suitable for FDP does not conflict with theory, but rather reflects the immanent differences between these two forensic applications of DNA information., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Abstract: Estimation of match probabilities for singleton haplotypes of lineage markers, i.e. for haplotypes observed only once in a reference database augmented by a suspect profile, is an important problem in forensic genetics. We compared the performance of four estimators of singleton match probabilities for Y-STRs, namely the count estimate, both with and without Brenner''s so-called ‘kappa correction’, the surveying estimate, and a previously proposed, but rarely used, coalescent-based approach implemented in the BATWING software. Extensive simulation with BATWING of the underlying population history, haplotype evolution and subsequent database sampling revealed that the coalescent-based approach is characterized by lower bias and lower mean squared error than the uncorrected count estimator and the surveying estimator. Moreover, in contrast to the two count estimators, both the surveying and the coalescent-based approach exhibited a good correlation between the estimated and true match probabilities. However, although its overall performance is thus better than that of any other recognized method, the coalescent-based estimator is still computation-intense on the verge of general impracticability. Its application in forensic practice therefore will have to be limited to small reference databases, or to isolated cases of particular interest, until more powerful algorithms for coalescent simulation have become available. [Copyright &y& Elsevier]

Abstract: Reasonable formalized methods to estimate the frequencies of DNA profiles generated from lineage markers have been proposed in the past years and were discussed in the forensic community. Recently, collections of population data on the frequencies of variations in Y chromosomal STR profiles have reached a new quality with the establishment of the comprehensive neatly quality-controlled reference database YHRD. Grounded on such unrivalled empirical material from hundreds of populations studies the core assumption of the Haplotype Frequency Surveying Method originally described 10 years ago can be tested and improved. Here we provide new approaches to calculate the parameters used in the frequency surveying method: a maximum likelihood estimation of the regression parameters (r 1, r 2, s 1 and s 2) and a revised Frequency Surveying framework with variable binning and a database preprocessing to take the population sub-structure into account. We found good estimates for 11 metapopulations using both approaches and demonstrate that the statistical basis of the method is well supported and independent of the population under study. The results of the estimation process are reliable and robust if the underlying datasets are large and representative and show small average and pairwise genetic distances. [Copyright &y& Elsevier]

• New model for Y STR haplotype population frequency estimation. • Conceptually statistically simple. • Outperforms previous methods. Estimating Y haplotype population frequencies is a demanding task in forensic genetics. Despite the suggestion of various methods, none these have yet reached a level of accuracy and precision that is acceptable to the forensic genetics community. At the basis of this problem is the complex dependency structure between the involved STR loci. Here, we approximate this structure by the use of specific graphical models, namely t -cherry junction trees. We apply trees of order three by which dependencies between three STR loci can be taken into account, thereby extending the Chow–Liu method which is restricted to pairwise dependencies. We show that the t -cherry tree method outperforms the Chow–Liu method as well as the well-established discrete Laplace method in estimation accuracy. [ABSTRACT FROM AUTHOR]