Estimating Haplotype Frequency and Coverage of Databases

A variety of forensic, population, and disease studies are based on haploid DNA (e.g. mitochondrial DNA or Y-chromosome data). For any set of genetic markers databases of conventional size will normally contain only a fraction of all haplotypes. For several applications, reliable estimates of haplotype frequencies, the total number of haplotypes and coverage of the database (the probability that the next random haplotype is contained in the database) will be useful. We propose different approaches to the problem based on classical methods as well as new applications of Principal Component Analysis (PCA). We also discuss previous proposals based on saturation curves. Several conclusions can be inferred from simulated and real data. First, classical estimates of the fraction of unseen haplotypes can be seriously biased. Second, there is no obvious way to decide on required sample size based on traditional approaches. Methods based on testing of hypotheses or length of confidence intervals may appear artificial since no single test or parameter stands out as particularly relevant. Rather the coverage may be more relevant since it indicates the percentage of different haplotypes that are contained in a database; if the coverage is low, there is a considerable chance that the next haplotype to be observed does not appear in the database and this indicates that the database needs to be expanded. Finally, freeware and example data sets accompany the methods discussed in this paper: http://folk.uio.no/thoree/nhap/

Using Object Oriented Bayesian Networks to Model Linkage, Linkage Disequilibrium and Mutations between STR Markers

In a number of applications there is a need to determine the most likely pedigree for a group of persons based on genetic markers. Adequate models are needed to reach this goal. The markers used to perform the statistical calculations can be linked and there may also be linkage disequilibrium (LD) in the population. The purpose of this paper is to present a graphical Bayesian Network framework to deal with such data. Potential LD is normally ignored and it is important to verify that the resulting calculations are not biased. Even if linkage does not influence results for regular paternity cases, it may have substantial impact on likelihood ratios involving other, more extended pedigrees. Models for LD influence likelihoods for all pedigrees to some degree and an initial estimate of the impact of ignoring LD and/or linkage is desirable, going beyond mere rules of thumb based on marker distance. Furthermore, we show how one can readily include a mutation model in the Bayesian Network; extending other programs or formulas to include such models may require considerable amounts of work and will in many case not be practical. As an example, we consider the two STR markers vWa and D12S391. We estimate probabilities for population haplotypes to account for LD using a method based on data from trios, while an estimate for the degree of linkage is taken from the literature. The results show that accounting for haplotype frequencies is unnecessary in most cases for this specific pair of markers. When doing calculations on regular paternity cases, the markers can be considered statistically independent. In more complex cases of disputed relatedness, for instance cases involving siblings or so-called deficient cases, or when small differences in the LR matter, independence should not be assumed. (The networks are freely available at http://arken.umb.no/~dakl/BayesianNetwor​ks.

A Statistical Framework for the Interpretation of mtDNA Mixtures: Forensic and Medical Applications

BACKGROUND: Mitochondrial DNA (mtDNA) variation is commonly analyzed in a wide range of different biomedical applications. Cases where more than one individual contribute to a stain genotyped from some biological material give rise to a mixture. Most forensic mixture cases are analyzed using autosomal markers. In rape cases, Y-chromosome markers typically add useful information. However, there are important cases where autosomal and Y-chromosome markers fail to provide useful profiles. In some instances, usually involving small amounts or degraded DNA, mtDNA may be the only useful genetic evidence available. Mitochondrial DNA mixtures also arise in studies dealing with the role of mtDNA variation in tumorigenesis. Such mixtures may be generated by the tumor, but they could also originate in vitro due to inadvertent contamination or a sample mix-up. METHODS/PRINCIPAL FINDINGS: We present the statistical methods needed for mixture interpretation and emphasize the modifications required for the more well-known methods based on conventional markers to generalize to mtDNA mixtures. Two scenarios are considered. Firstly, only categorical mtDNA data is assumed available, that is, the variants contributing to the mixture. Secondly, quantitative data (peak heights or areas) on the allelic variants are also accessible. In cases where quantitative information is available in addition to allele designation, it is possible to extract more precise information by using regression models. More precisely, using quantitative information may lead to a unique solution in cases where the qualitative approach points to several possibilities. Importantly, these methods also apply to clinical cases where contamination is a potential alternative explanation for the data. CONCLUSIONS/SIGNIFICANCE: We argue that clinical and forensic scientists should give greater consideration to mtDNA for mixture interpretation. The results and examples show that the analysis of mtDNA mixtures contributes substantially to forensic casework and may also clarify erroneous claims made in clinical genetics regarding tumorigenesis

Response to: DNA identification by pedigree likelihood ratio accommodating population substructure and mutations.

Mutation models are important in many areas of genetics including forensics. This letter criticizes the model of the paper 'DNA identification by pedigree likelihood ratio accommodating population substructure and mutations' by Ge et al. (2010). Furthermore, we argue that the paper in some cases misrepresents previously published papers.Please see related letter: http://www.investigativegenetics.com/content/2/1/8.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Making decisions in missing person identification cases with low statistical power

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Does prolonged labor affect the birth experience and subsequent wish for cesarean section among first-time mothers? A quantitative and qualitative analysis of a survey from Norway

Background: Prolonged labor might contribute to a negative birth experience and influence first-time mothers’ attitudes towards future pregnancies. Previous studies have not adjusted for possible confounding factors, such as operative delivery, induction and postpartum hemorrhage. We aimed to determine the impact of prolonged labor on birth experience and a wish for cesarean section in subsequent pregnancies. Methods: A survey including the validated “Childbirth Experience Questionnaire”. First-time mothers giving birth between 2012 and 2014 at a Norwegian university hospital participated. Data from deliveries were collected. Regression analysis and thematic content analysis were performed. Results: 459 (71%) women responded. Women with labor duration > 12 h had significantly lower scores on two out of four sub-items of the questionnaire: own capacity (p = 0.040) and perceived safety (p = 0.023). Other factors contributing to a negative experience were: Cesarean section vs vaginal birth: own capacity (p = 0.001) and perceived safety (p = 0.007). Operative vaginal vs spontaneous birth: own capacity (p = 0.001), perceived safety (p < 0.001) and participation (p = 0.047). Induced vs spontaneous start: own capacity (p = 0.039) and participation (p = 0.050). Postpartum hemorrhage ≥500 ml vs < 500 ml: perceived safety (p = 0.002) and participation (p = 0.031). In the unadjusted analysis, prolonged labor more than doubled the risk (odds ratio (OR) 2.66, 95%CI 1.42–4.99) of a subsequent wish for cesarean delivery. However, when adjustments were made for mode of delivery and induction, emergency cesarean section (OR 8.86,95%CI 3.85–20.41) and operative vaginal delivery (OR 3.05, 95%CI 1.46–6.38) remained the only factors significantly increasing the probability of wanting a cesarean section in subsequent pregnancies. The written comments on prolonged labor (n = 46) indicated four main themes: – Difficulties gaining access to the labor ward. – Being left alone during the unexpectedly long, painful early stage of labor. – Stressful operative deliveries and worse pain than imagined. – Lack of support and too little or contradictory information from the staff. Conclusions: Women with prolonged labors are at risk of a negative birth experience. Prolonged labor per se did not predict a wish for a cesarean section in a subsequent pregnancy. However, women with long labors more often experience operative delivery, which is a risk factor of a later wish for a cesarean section.publishedVersio

Strategies for pairwise searches in forensic kinship analysis

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A CLEC16A variant confers risk for juvenile idiopathic arthritis and anti-cyclic citrullinated peptide antibody negative rheumatoid arthritis

Objective Variants in CLEC16A have conferred susceptibility to autoimmune diseases in genome-wide association studies. The present work aimed to investigate the locus' involvements in juvenile idiopathic arthritis (JIA) and further explore the association with rheumatoid arthritis (RA), type 1 diabetes (T1D) and Addison's disease (AD) in the Norwegian population. Methods Three single nucleotide polymorphisms (SNPs) were genotyped in patients with RA (n=809), JIA (n=509), T1D (n=1211) and AD (n=414) and in healthy controls (n=2149). Results All diseases were associated with CLEC16A, but with different SNPs. The intron 22 SNP, rs6498169, was associated with RA (p=0.006) and JIA (p=0.016) and the intron 19 SNPs, rs12708716/rs12917716, with T1D (p=1×10−5) and AD (p=2×10−4). The RA association was confined to the anti-cyclic citrullinated peptide antibody (anti-CCP) negative subgroup (p=2×10−4). Conclusion This is the first report of a CLEC16A association with JIA and a split of the RA association according to anti-CCP status. Different causative variants underlie the rheumatic versus the organ specific diseases

The DNA database search controversy revisited: Bridging the Bayesian - Frequentistic gap

Two different quantities have been suggested for quantification of evidence in cases where a suspect is found by a search through a database of DNA profiles. The likelihood ratio, typically motivated from a Bayesian setting, is preferred by most experts in the field. The so-called $np$ rule has been suggested through more frequentistic arguments and has been suggested by i.e. American National Research Council and Stockmarr (1999). The two quantities differ substantially and have lead to what is called the DNA database search controversy. Although several authors have criticized the different approaches, a full explanation of why these differences appear is still lacking. In this paper we show that a quantity approximately equal to the $np$ rule can be seen as a P-value in a frequentistic hypothesis setting. We argue however that a more reasonable procedure in this case is to use conditional testing, in which case a P-value directly related to posterior probabilities and the likelihood ratio is obtained. This way of viewing the problem bridge the gap between the Bayesian and frequentistic approaches. At the same time it indicates that the $np$ rule should not be used as a quantity of evidence