Weight of the evidence of genetic investigations of ancestry informative markers.

Ancestry-informative markers (AIMs) are markers that give information about the ancestry of individuals. They are used in forensic genetics for predicting the geographic origin of the investigated individual in crime and identification cases. In the exploration of the genogeographic origin of an AIMs profile, the likelihoods of the AIMs profile in various populations may be calculated. However, there may not be an appropriate reference population in the database. The fact that the likelihood ratio (LR) of one population compared to that of another population is large does not imply that any of the populations is relevant. To handle this phenomena, we derived a likelihood ratio test (LRT) that is a measure of absolute concordance between an AIMs profile and a population rather than a relative measure of the AIMs profile's likelihood in two populations. The LRT is similar to a Fisher's exact test. By aggregating over markers, the central limit theorem suggests that the resulting quantity is approximately normally distributed. If only a few markers are genotyped or if the majority of the markers are fixed in a given population, the approximation may fail. We overcome this using importance sampling and show how exponential tilting results in an efficient proposal distribution. By simulations and published AIMs profiles, we demonstrate the applicability of the derived methodology. For the genotyped AIMs, the LRT approach achieves the nominal levels of rejection when tested on data from five major continental regions.

YfilerⓇ Plus population samples and dilution series: stutters, analytic thresholds, and drop-out probabilities.

The Yfiler Ⓡ Plus Amplification Kit amplifies 27 Y chromosomal small tandem repeat (STR) markers. The kit has five-fluorescent dye chemistry and the improved PCR buffer system of modern STR kits. We validated the kit for accredited investigations of crime scene samples by a thorough study of kit dynamics and performance. We determined dye-dependent analytical thresholds by receiver operating characteristics (ROC) and made a customised artefact filter that includes theoretical known artefacts by use of previously analysed population samples. Dilution series of known male DNA and a selection of crime scene samples were analysed with the customised thresholds and artefact filters. The Yfiler Ⓡ Plus Amplification Kit was sensitive giving full profiles down to 70 pg of male DNA. The balances between the fluorescent dyes as well as between loci were very good. The kit was able to produce full Y-STR profiles from crime scene samples containing small amounts of male DNA and large amounts of female DNA (although unspecific reactions were evident for very unbalanced mixtures). A decrease in the drop-out rate was found for both the dilution series and population samples, as well as a small increase in the drop-in rate for population samples, using the customised threshold and artefact filters compared to company-provided thresholds and artefact filters. The additional drop-ins were all of a nature that would be detected by inspection of the results. For the crime scene samples, large amounts of female DNA complicated the analysis by causing drop-ins of characteristic female DNA artefacts. Even though the customised analytical threshold in combination with the custom-made artefact filters gave more alleles, crime scene samples still needed special attention from the forensic geneticist.

Increasing the reference populations for the 55 AISNP panel: the need and benefits.

Ancestry inference for an individual can only be as good as the reference populations with allele frequency data on the SNPs being used. If the most relevant ancestral population(s) does not have data available for the SNPs studied, then analyses based on DNA evidence may indicate a quite distantly related population, albeit one among the more closely related of the existing reference populations. We have added reference population allele frequencies for 14 additional population samples (with >1100 individuals studied) to the 125 population samples previously published for the Kidd Lab 55 AISNP panel. Allele frequencies are now publicly available for all 55 SNPs in ALFRED and FROG-kb for a total of 139 population samples. This Kidd Lab panel of 55 ancestry informative SNPs has been incorporated in commercial kits by both ThermoFisher Scientific and Illumina for massively parallel sequencing. Researchers employing those kits will find the enhanced set of reference populations useful.

Pitfalls and challenges with population assignments of individuals from admixed populations: Applying Genogeographer on Brazilian individuals.

The assignment of individuals to a population can be of importance for the identification of mass disaster victims or criminal offenders in the field of forensic genetics. This assignment is based on biostatistical methods that process data of ancestry informative markers (AIMs), which are selected based on large allele frequency differences between the populations of interest. However, population assignments of individuals with an admixed genetic background are challenging. Admixed individuals are genetic mosaics of chromosomal segments from the parental populations, which may lead to ambiguous or no population assignment. This is problematic since admixture events are a substantial part of human history. In this study, we present challenges of interpreting the evidential weight of population assignments. We used Genogeographer for likelihood ratio (LR) calculations and Brazilians as examples of admixed individuals. Brazilians are a very heterogenous population representing a three-way admixture between Native Americans, Europeans, and Africans. Ancestry informative markers were typed in a total of 589 individuals from Brazil using the Precision ID Ancestry Panel. The Brazilians were assigned to six metapopulations (East Asia, Europe, Middle East, North Africa, South-Central Asia, Sub-Saharan Africa) defined in the Genogeographer software and LRs were calculated if the AIM profile was not an outlier in all metapopulations and simulated two-way (1:1) admixtures of the six metapopulations. Population assignments failed for 55% of the samples. These samples had significantly higher genetic contributions from East Asia, South-Central Asia and Sub-Saharan Africa, and significantly lower genetic contributions from Europe. Most of the individuals with population assignments were assigned to the metapopulations of Middle East (58%) or North Africa (36%), followed by Europe (4%), South-Central Asia (1%), and Sub-Saharan Africa (1%). For 8% of the samples, population assignments were only possible when assignments to simulated two-way (1:1) admixtures of the six metapopulations were considered. Most of these individuals were assigned to two-way admixtures of North Africa, South-Central Asia, or Sub-Saharan Africa. Relatively low median likelihood ratios (LRs<1000) were observed when comparing population likelihoods for Europe, Middle East, North Africa, South-Central Asia, or simulated 1:1 admixtures of these metapopulations. Comparisons including East Asian or Sub-Saharan African populations resulted in larger median LRs (LR>1010). The results suggested that the Precision ID Ancestry Panel provided too little information and that additional markers specifically selected for sub-continental differentiation may be required for accurate population assignment of admixed individuals. Furthermore, a Genogeographer database with additional populations including admixed populations would be advantageous for interpretation of admixed AIM profiles. It would likely increase the number of population assignments and illustrate alternatives to the most likely population, which would be valuable information for the case officer when writing the case report.

Development of an automated AmpliSeq™ library building workflow for biological stain samples on the Biomek® 3000.

Here, we present the development of an automated AmpliSeq™ (ThermoFischer, MA, USA) workflow for library building using the Biomek® 3000 Laboratory Automation Workstation (Beckman Coulter Inc., CA, USA), in which the total volume of PCR reagents and reagents for library preparation are reduced by one-half. The automated AmpliSeq workflow was tested using 43 stain samples (blood, bone, muscle tissue, semen, swab, nail scrape and cigarette butts) collected from crime scenes. The sequencing data were evaluated for locus balance, heterozygous allele balance and noise. The performance of libraries built with the automated AmpliSeq workflow using one-half of the recommended reagent volumes were similar to the performance of libraries built with the recommended (full) volumes of the reagents.

Quantification of massively parallel sequencing libraries - a comparative study of eight methods.

Quantification of massively parallel sequencing libraries is important for acquisition of monoclonal beads or clusters prior to clonal amplification and to avoid large variations in library coverage when multiple samples are included in one sequencing analysis. No gold standard for quantification of libraries exists. We assessed eight methods of quantification of libraries by quantifying 54 amplicon, six capture, and six shotgun fragment libraries. Chemically synthesized double-stranded DNA was also quantified. Light spectrophotometry, i.e. NanoDrop, was found to give the highest concentration estimates followed by Qubit and electrophoresis-based instruments (Bioanalyzer, TapeStation, GX Touch, and Fragment Analyzer), while SYBR Green and TaqMan based qPCR assays gave the lowest estimates. qPCR gave more accurate predictions of sequencing coverage than Qubit and TapeStation did. Costs, time-consumption, workflow simplicity, and ability to quantify multiple samples are discussed. Technical specifications, advantages, and disadvantages of the various methods are pointed out.

Stutter analysis of complex STR MPS data.

Stutters are common and well documented artefacts of amplification of short tandem repeat (STR) regions when using polymerase chain reaction (PCR) occurring as strands one or more motifs shorter or longer than the parental allele. Understanding the mechanism and rate by which stutters are created is especially important when the samples contain small amounts of DNA or DNA from multiple contributors. It has been shown that there is a linear relationship between the longest uninterrupted stretch (LUS) and the stutter ratio. This holds if there is only a single type of stutter variant. However, with massively parallel sequencing (MPS), we see that alleles may create different stutters corresponding to stuttering of different parts of the parental allele. This calls for a refinement of the LUS concept. We analysed all uninterrupted stretches, here called blocks, and identified the block from which the stutter originated. We defined the block length of the missing motif (BLMM) as the length of the identified block. We found that the relationship between the stutter ratio and BLMM was linear using a simple system of recurrence relations. We found that the mean square error decreased by a factor up to 17.5 for compound and complex autosomal markers when using BLMM instead of LUS.

Statistical modelling of Ion PGM HID STR 10-plex MPS data.

We investigated the results of short tandem repeat (STR) markers of dilution series experiments and reference profiles generated using the Ion PGM massively parallel sequencing platform utilising the HID STR 10-plex panel. The STR markers were identified by the marker specific flanking regions of the STR region. We investigated the following: (1) the usage of quality measures for identifying substitution errors, (2) the heterozygote balance and compared it to that of capillary electrophoresis (CE), (3) the stability of the coverage and the consequence of IonExpress Barcode adapter (IBA) sampling with decreasing amounts of template DNA, (4) the hypothesis that the parental longest uninterrupted stretch (LUS) is a better linear predictor of stutter ratio than the parent allele length, (5) the use of parental allele length as a predictor of shoulder ratio, and (6) the removal of non-systematic erroneous sequences using dynamic thresholds created by fitting the distribution of the non-systematic erroneous sequences. We found that, due to MID sampling, the average coverage on a marker could not be used as an apt predictor of the amount of template DNA. The parental LUS was shown to be better predictor of stutter ratio than the parental allele repeat length, when markers with compound and complex repeat patterns or markers which contained micro-variants were considered, such as marker TH01 showed R2 of 0.02 and 0.78 for parent allele repeat length and LUS, respectively. The one-inflated negative binomial method (OINB) and geometric model that can be used to remove non-systematic noise left on average 1.8 and 1.2 systematic errors per STR system, respectively.

Identifying the most likely contributors to a Y-STR mixture using the discrete Laplace method.

In some crime cases, the male part of the DNA in a stain can only be analysed using Y chromosomal markers, e.g. Y-STRs. This may be the case in e.g. rape cases, where the male components can only be detected as Y-STR profiles, because the fraction of male DNA is much smaller than that of female DNA, which can mask the male results when autosomal STRs are investigated. Sometimes, mixtures of Y-STRs are observed, e.g. in rape cases with multiple offenders. In such cases, Y-STR mixture analysis is required, e.g. by mixture deconvolution, to deduce the most likely DNA profiles from the contributors. We demonstrate how the discrete Laplace method can be used to separate a two person Y-STR mixture, where the Y-STR profiles of the true contributors are not present in the reference dataset, which is often the case for Y-STR profiles in real case work. We also briefly discuss how to calculate the weight of the evidence using the likelihood ratio principle when a suspect's Y-STR profile fits into a two person mixture. We used three datasets with between 7 and 21 Y-STR loci: Denmark (n=181), Somalia (n=201) and Germany (n=3443). The Danish dataset with 21 loci was truncated to 15 and 10 loci to examine the effect of the number of loci. For each of these datasets, an out of sample simulation study was performed: A total of 550 mixtures were composed by randomly sampling two haplotypes, h1 and h2, from the dataset. We then used the discrete Laplace method on the remaining data (excluding h1 and h2) to rank the contributor pairs by the product of the contributors' estimated haplotype frequencies. Successful separation of mixtures (defined by the observation that the true contributor pair was among the 10 most likely contributor pairs) was found in 42-52% of the cases for 21 loci, 69-75% for 15 loci and 92-99% for 10 loci or less depending on the dataset and how the discrete Laplace model was chosen. Y-STR mixtures with many loci are difficult to separate, but even haplotypes with 21 Y-STR loci can be separated.

Forensic and population genetic analyses of Danes, Greenlanders and Somalis typed with the Yfiler® Plus PCR amplification kit.

Recently, the Yfiler® Plus PCR Amplification Kit (Yfiler® Plus, Thermo Fisher Scientific, Waltham, MA, USA) was introduced. Yfiler® Plus amplifies 27 Y-chromosomal short tandem repeat loci (Y-STRs) and adds ten new Y-STRs to those analysed with the commonly used AmpFlSTR® Yfiler® PCR Amplification Kit (Yfiler®, Thermo Fisher Scientific, Waltham, MA, USA). Seven of the new Y-STRs are rapidly mutating Y-STRs (RM Y-STRs). In this study, 551 male individuals from Denmark, Greenland and Somalia were typed with Yfiler® Plus. The results were compared to those obtained with Yfiler® in the same individuals. Forensic and population genetic parameters were estimated for Yfiler® Plus. Yfiler® Plus had a higher power of discrimination than Yfiler® in all three populations. Compared to Yfiler®, Yfiler® Plus offers increased power of discrimination, which is obviously an advantage in crime case investigations. However, the inclusion of seven RM Y-STRs in Yfiler® Plus makes it less attractive for relationship testing because of the relatively high combined mutation rate, approximately 15%.

Second-generation sequencing of forensic STRs using the Ion Torrent™ HID STR 10-plex and the Ion PGM™.

Second-generation sequencing (SGS) using Roche/454 and Illumina platforms has proved capable of sequencing the majority of the key forensic genetic STR systems. Given that Roche has announced that the 454 platforms will no longer be supported from 2015, focus should now be shifted to competing SGS platforms, such as the MiSeq (Illumina) and the Ion Personal Genome Machine (Ion PGM™; Thermo Fisher). There are currently several challenges faced with amplicon-based SGS STR typing in forensic genetics, including current lengths of amplicons for CE-typing and lack of uniform data analysis between laboratories. Thermo Fisher has designed a human identification (HID) short tandem repeat (STR) 10-plex panel including amelogenin, CSF1PO, D16S539, D3S1358, D5S818, D7S820, D8S1179, TH01, TPOX and vWA, where the primers have been designed specifically for the purpose of SGS and the data analysis is supported by Ion Torrent™ software. Hence, the combination of the STR 10-plex and the Ion PGM™ represents the first fully integrated SGS STR typing solution from PCR to data analysis. In this study, four experiments were performed to evaluate the alpha-version of the STR 10-plex: (1) typing of control samples; (2) analysis of sensitivity; (3) typing of mixtures; and (4) typing of biological crime case samples. Full profiles and concordant results between replicate SGS runs and CE-typing were observed for all control samples. Full profiles were seen with DNA input down to 50 pg, with the exception of a single locus drop-out in one of the 100 pg dilutions. Mixtures were easily deconvoluted down to 20:1, although alleles from the minor contributor had to be identified manually as some signals were not called by the Ion Torrent™ software. Interestingly, full profiles were obtained for all biological samples from real crime and identification cases, in which only partial profiles were obtained with PCR-CE assays. In conclusion, the Ion Torrent™ HID STR 10-plex panel offers an all-in-one solution from amplification of STRs and amelogenin, and sequencing to data analysis.

Evaluation of the Ion Torrent™ HID SNP 169-plex: A SNP typing assay developed for human identification by second generation sequencing.

The Ion Torrent™ HID SNP assay amplified 136 autosomal SNPs and 33 Y-chromosome markers in one PCR and the markers were subsequently typed using the Ion PGM™ second generation sequencing platform. A total of 51 of the autosomal SNPs were selected from the SNPforID panel that is routinely used in our ISO 17025 accredited laboratory. Concordance between the Ion Torrent™ HID SNP assay and the SNPforID assay was tested by typing 44 Iraqis twice with the Ion Torrent™ HID SNP assay. The same samples were previously typed with the SNPforID assay and the Y-chromosome haplogroups of the individuals were previously identified by typing 45 Y-chromosome SNPs. Full concordance between the assays were obtained except for the SNP genotypes of two SNPs. These SNPs were among the eight SNPs (rs2399332, rs1029047, rs10776839, rs4530059, rs8037429, rs430046, rs1031825 and rs1523537) with inconsistent allele balance among samples. These SNPs should be excluded from the panel. The optimal amount of DNA in the PCR seemed to be ≥0.5ng. Allele drop-outs were rare and only seen in experiments with <0.5ng input DNA and with a coverage of <50reads. No allele drop-in was observed. The great majority of the heterozygote allele balances were between 0.6 and 1.6, which is comparable to the heterozygote balances of STRs typed with PCR-CE. The number of reads with base calls that differed from the genotype call was typically less than five. This allowed detection of 1:100 mixtures with a high degree of certainty in experiments with a high total depth of coverage. In conclusion, the Ion PGM™ is a very promising platform for forensic genetics. However, the secondary sequence analysis software made wrong genotype calls from correctly sequenced alleles. These types of errors must be corrected before the platform can be used in case work. Furthermore, the sequence analysis software should be further developed and include quality settings for each SNP based on validation studies.

Forensic genetic SNP typing of low-template DNA and highly degraded DNA from crime case samples.

Heterozygote imbalances leading to allele drop-outs and disproportionally large stutters leading to allele drop-ins are known stochastic phenomena related to STR typing of low-template DNA (LtDNA). The large stutters and the many drop-ins in typical STR stutter positions are artifacts from the PCR amplification of tandem repeats. These artifacts may be avoided by typing bi-allelic markers instead of STRs. In this work, the SNPforID multiplex assay was used to type LtDNA. A sensitized SNP typing protocol was introduced, that increased signal strengths without increasing noise and without affecting the heterozygote balance. Allele drop-ins were only observed in experiments with 25 pg of DNA and not in experiments with 50 and 100 pg of DNA. The allele drop-in rate in the 25 pg experiments was 0.06% or 100 times lower than what was previously reported for STR typing of LtDNA. A composite model and two different consensus models were used to interpret the SNP data. Correct profiles with 42-49 SNPs were generated from the 50 and 100 pg experiments, whereas a few incorrect genotypes were included in the generated profiles from the 25 pg experiments. With the strict consensus model, between 35 and 48 SNPs were correctly typed in the 25 pg experiments and only one allele drop-out (error rate: 0.07%) was observed in the consensus profiles. A total of 28 crime case samples were selected for typing with the sensitized SNPforID protocol. The samples were previously typed with old STR kits during the crime case investigation and only partial profiles (0-6 STRs) were obtained. Eleven of the samples could not be quantified with the Quantifiler™ Human DNA Quantification kit because of partial or complete inhibition of the PCR. For eight of these samples, SNP typing was only possible when the buffer and DNA polymerase used in the original protocol was replaced with the AmpFℓSTR(®) SEfiler Plus™ Master Mix, which was developed specifically for challenging forensic samples. All the crime case samples were successfully typed with the SNPforID multiplex assay and the match probabilities ranged from 1.1×10(-15) to 7.9×10(-23). In comparison, four of the samples could not be typed with the AmpFℓSTR(®) SEfiler Plus™ kit and the match probabilities were higher than 10(-7) for another six samples.

Estimating Y-STR allelic drop-out rates and adjusting for interlocus balances.

Y chromosome short tandem repeats (Y-STRs) are valuable genetic markers in certain areas of forensic case-work. However, when the Y-STR DNA profile is weak, the observed Y-STR profile may not be complete--i.e. locus drop-out may have occurred. Another explanation could be that the stain DNA did not have a Y-STR allele that was detectable with the method used (the allele is a 'null allele'). If the Y-STR profile of a stain is strong, one would be reluctant to consider drop-out as a reasonable explanation of lack of a Y-STR allele and would maybe consider 'null allele' as an explanation. On the other hand, if the signal strengths are weak, one would most likely accept drop-out as a possible explanation. We created a logistic regression model to estimate the probability of allele drop-out with the Life Technologies/Applied Biosystems AmpFlSTR(®) Yfiler(®) kit such that the trade-off between drop-outs and null alleles could be quantified using a statistical model. The model to estimate the probability of drop-out uses information about locus imbalances, signal strength, the number of PCR cycles, and the fragment size of Yfiler. We made two temporarily separated experiments and found no evidence of temporal variation in the probability of drop-out. Using our model, we found that for 30 PCR cycles with a 150 bp allele, the probability of drop-out was 1:5000 corresponding to the average estimate of the probability of Y-STR null alleles at a signal strength of 1249 RFU. This means that the probability of a null allele is higher than that of an allele drop-out at e.g. 4000 RFU and the probability of drop-out is higher than that of a null allele at e.g. 75 RFU.

Statistical model for degraded DNA samples and adjusted probabilities for allelic drop-out.

DNA samples found at a scene of crime or obtained from the debris of a mass disaster accident are often subject to degradation. When using the STR DNA technology, the DNA profile is observed via a so-called electropherogram (EPG), where the alleles are identified as signal peaks above a certain level or above a signal to noise threshold. Degradation implies that these peak intensities decrease in strength for longer short tandem repeat (STR) sequences. Consequently, long STR loci may fail to produce peak heights above the limit of detection resulting in allelic or locus drop-outs. In this paper, we present a method for measuring the degree of degradation of a sample and demonstrate how to incorporate this in estimating the probability of allelic drop-out. This is done by extending an existing method derived for non-degraded samples. The performance of the methodology is evaluated using data from degraded DNA, where cases with varying amounts of DNA and levels of degradation are investigated.

Identifying contributors of DNA mixtures by means of quantitative information of STR typing.

Estimating the weight of evidence in forensic genetics is often done in terms of a likelihood ratio, LR. The LR evaluates the probability of the observed evidence under competing hypotheses. Most often, probabilities used in the LR only consider the evidence from the genomic variation identified using polymorphic genetic markers. However, modern typing techniques supply additional quantitative data, which contain very important information about the observed evidence. This is particularly true for cases of DNA mixtures, where more than one individual has contributed to the observed biological stain. This article presents a method for including the quantitative information of short tandem repeat (STR) DNA mixtures in the LR. Also, an efficient algorithmic method for finding the best matching combination of DNA mixture profiles is derived and implemented in an on-line tool for two- and three-person DNA mixtures. Finally, we demonstrate for two-person mixtures how this best matching pair of profiles can be used in estimating the likelihood ratio using importance sampling. The reason for using importance sampling for estimating the likelihood ratio is the often vast number of combinations of profiles needed for the evaluation of the weight of evidence. Online tool is available at http://people.math.aau.dk/~tvede/dna/.

Performance of two 17 locus forensic identification STR kits-Applied Biosystems's AmpFℓSTR® NGMSElect™ and Promega's PowerPlex® ESI17 kits.

We compared the performance of two recently released 17 loci STR multiplexes for human identification: Applied Biosystems's AmpFℓSTR(®) NGMSElect™ and Promega's PowerPlex(®) ESI17. The comparative parameters were chosen by their relevance in forensic identification and particularly in crime cases. The comparative analyses encompass: amplification ability, heterozygote balance, allelic drop-out, drop-in, stutter analysis and inter-locus balance. Four DNA profiles were analysed in various concentrations in a serial dilution experiment. The amounts of DNA in the PCR ranged from 3 pg to 420 pg and were analysed in triplicate using 28, 29 and 30 PCR cycles. In order to compare the kits, aliquots from each sample were analysed with both kits under identical conditions. Furthermore, DNA profiles from 200 reference profiles were analysed using both kits. The results from the statistical analyses did not indicate any substantial differences of practical relevance between the kits for forensic case work. For all parameters included in this comparative study, the two kits showed no departure from previously observed patterns relative to e.g. the amounts of DNA or amplicon lengths. Based on our analyses, both kits are considered applicable for forensic crime case work.

Allelic drop-out probabilities estimated by logistic regression--further considerations and practical implementation.

We discuss the model for estimating drop-out probabilities presented by Tvedebrink et al. [7] and the concerns, that have been raised. The criticism of the model has demonstrated that the model is not perfect. However, the model is very useful for advanced forensic genetic work, where allelic drop-out is occurring. With this discussion, we hope to improve the drop-out model, so that it can be used for practical forensic genetics and stimulate further discussions. We discuss how to estimate drop-out probabilities when using a varying number of PCR cycles and other experimental conditions.

Analysis of matches and partial-matches in a Danish STR data set.

Over the recent years, the national databases of STR profiles have grown in size due to the success of forensic DNA analysis in solving crimes. The accumulation of DNA profiles implies that the probability of a random match or near match of two randomly selected DNA profiles in the database increases. We analysed 53,295 STR profiles from individuals investigated in relation to crime case investigations at the Department of Forensic Medicine, Faculty of Health Sciences, University of Copenhagen, Denmark. Incomplete STR profiles (437 circa 0.8% of the total), 48 redundant STR profiles from monozygotic twins (0.09%), 6 redundant STR profiles of unknown cause and 1283 STR profiles from repeated testing of individuals were removed leaving 51,517 complete 10 locus STR profiles for analysis. The number corresponds to approximately 1% of the Danish population. We compared all STR profiles to each other, i.e. 1.3×10(9) comparisons. With these large number of comparisons, it is likely to observe DNA profiles that coincide on many loci, which has concerned some commentators and raised questions about "overstating" the power of DNA evidence. We used the method of Weir [11,12] and Curran et al. [3] to compare the observed and expected number of matches and near matches in the data set. We extended the methods by computing the covariance matrix of the summary statistic and used it for the estimation of the identical-by-descent parameter, θ. The analysis demonstrated a number of close relatives in the Danish data set and substructure. The main contribution to the substructure comes from close relatives. An overall θ-value of 1% compensated for the observed substructure, when close familial relationships were accounted for.

Estimating the probability of allelic drop-out of STR alleles in forensic genetics.

In crime cases with available DNA evidence, the amount of DNA is often sparse due to the setting of the crime. In such cases, allelic drop-out of one or more true alleles in STR typing is possible. We present a statistical model for estimating the per locus and overall probability of allelic drop-out using the results of all STR loci in the case sample as reference. The methodology of logistic regression is appropriate for this analysis, and we demonstrate how to incorporate this in a forensic genetic framework.