An assessment of the information content of likelihood ratios derived from complex mixtures.

With the increasing sensitivity of DNA typing methodologies, as well as increasing awareness by law enforcement of the perceived capabilities of DNA typing, complex mixtures consisting of DNA from two or more contributors are increasingly being encountered. However, insufficient research has been conducted to characterize the ability to distinguish a true contributor (TC) from a known non-contributor (KNC) in these complex samples, and under what specific conditions. In order to investigate this question, sets of six 15-locus Caucasian genotype profiles were simulated and used to create mixtures containing 2-5 contributors. Likelihood ratios were computed for various situations, including varying numbers of contributors and unknowns in the evidence profile, as well as comparisons of the evidence profile to TCs and KNCs. This work was intended to illustrate the best-case scenario, in which all alleles from the TC were detected in the simulated evidence samples. Therefore the possibility of drop-out was not modeled in this study. The computer program DNAMIX was then used to compute LRs comparing the evidence profile to TCs and KNCs. This resulted in 140,000 LRs for each of the two scenarios. These complex mixture simulations show that, even when all alleles are detected (i.e. no drop-out), TCs can generate LRs less than 1 across a 15-locus profile. However, this outcome was rare, 7 of 140,000 replicates (0.005%), and associated only with mixtures comprising 5 contributors in which the numerator hypothesis includes one or more unknown contributors. For KNCs, LRs were found to be greater than 1 in a small number of replicates (75 of 140,000 replicates, or 0.05%). These replicates were limited to 4 and 5 person mixtures with 1 or more unknowns in the numerator. Only 5 of these 75 replicates (0.004%) yielded an LR greater than 1,000. Thus, overall, these results imply that the weight of evidence that can be derived from complex mixtures containing up to 5 contributors, under a scenario in which no drop-out is required to explain any of the contributors, is remarkably high. This is a useful benchmark result on top of which to layer the effects of additional factors, such as drop-out, peak height, and other variables.

The interpretation of single source and mixed DNA profiles.

A method for interpreting autosomal mixed DNA profiles based on continuous modelling of peak heights is described. MCMC is applied with a model for allelic and stutter heights to produce a probability for the data given a specified genotype combination. The theory extends to handle any number of contributors and replicates, although practical implementation limits analyses to four contributors. The probability of the peak data given a genotype combination has proven to be a highly intuitive probability that may be assessed subjectively by experienced caseworkers. Whilst caseworkers will not assess the probabilities per se, they can broadly judge genotypes that fit the observed data well, and those that fit relatively less well. These probabilities are used when calculating a subsequent likelihood ratio. The method has been trialled on a number of mixed DNA profiles constructed from known contributors. The results have been assessed against a binary approach and also compared with the subjective judgement of an analyst.

Caring for young adolescent sexual abuse victims in a hospital-based children's advocacy center.

OBJECTIVES: This study compared health care assessments, referrals, treatment, and outcomes for young adolescent sexual assault/sexual abuse victims seen at a hospital-based Child Advocacy Center (CAC), to that provided to similar victims evaluated by other community providers. A second purpose was to document how common DNA evidence is found among such cases. METHOD: A retrospective matched case-comparison design matched index CAC cases diagnosed with extra-familial sexual assault to non-CAC cases referred for prosecution in the same county, matched by age and sex of victim, age and sex of perpetrator, and type of assault (N=128 pairs). Since the case-comparison design produces paired data, analyses used paired t-tests, McNemars test, and Wilcoxon signed-rank tests. Health care outcomes included whether victims received a health exam, indicated tests, findings of trauma on genital exams and counseling referrals; legal outcomes included whether cases were prosecuted, verdicts, and length of sentences. RESULTS: CAC cases were significantly more likely to receive a physical exam, a genital exam when indicated, and referral for counseling (all p<.001). In the CAC group 26.7% vs. 4.8% had positive genital trauma findings, and only 6.3% of CAC cases failed to get indicated sexually transmitted infection (STI) tests or prophylactic treatment for STIs vs. 80% of the comparisons (p<.001). There were no differences in decisions to prosecute, convictions, or sentence lengths between the groups. DNA was documented in only 27.3% of acute cases, although evidence kits were completed. CONCLUSIONS: Young adolescent sexual abuse victims received markedly different health care in a hospital-based CAC compared to elsewhere. DNA is not commonly found in acute cases. IMPLICATIONS FOR PRACTICE: Community health care providers and law enforcement should be encouraged to refer victims to hospital-based CACs for specialized examinations and treatment.

Statistics of single-molecule measurements: applications in flow-cytometry sizing of DNA fragments.

BACKGROUND: The measurement of physical properties from single molecules has been demonstrated. However, the majority of single-molecule studies report values based on relatively large data sets (e.g., N > 50). While there are studies that report physical quantities based on small sample sets, there has not been a detailed statistical analysis relating sample size to the reliability of derived parameters. METHODS: Monte Carlo simulations and multinomial analysis, dependent on quantifiable experimental parameters, were used to determine the minimum number of single-molecule measurements required to produce an accurate estimate of a population mean. Simulation results were applied to the fluorescence-based sizing of DNA fragments by ultrasensitive flow cytometry (FCM). RESULTS: Our simulations show, for an analytical technique with a 10% CV, that the average of as few as five single-molecule measurements would provide a mean value within one SD of the population mean. Additional simulations determined the number of measurements required to obtain the desired number of replicates for each subpopulation within a mixture. Application of these results to flow cytometry data for lambda/HindIII and S. aureus Mu50/SmaI DNA digests produced accurate DNA fingerprints from as few as 98 single-molecule measurements. CONCLUSIONS: A surprisingly small number of single-molecule measurements are required to obtain a mean measurement descriptive of a normally-distributed parent population.

Evidence for a spontaneous C1840-T mutation in the RYR1 gene after DNA fingerprinting in a malignant hyperthermia susceptible family.

Malignant hyperthermia (MH) is a potentially lethal inherited pharmacogenetic syndrome due to a dysfunction of the intracellular calcium regulation of skeletal muscle following administration of volatile anaesthetics and depolarizing muscle relaxants. The ryanodine receptor of skeletal muscle (RYR1), which is an intracellular calcium release channel, has been proposed to be a candidate structure for the MH defect. In some families with a history of MH a C1840-T nucleotide exchange has been found in the RYR1 gene which cosegregates with the MH susceptible phenotype. Sixteen individuals (5 males and 11 females; age 8-68 years, 7 MH susceptible, 9 MH non-susceptible) of a family with a history of MH were screened for the C1840-T mutation in the RYR1 gene using standard methods. DNA fingerprinting was performed in order to verify the kinship. MH susceptibility was determined using the standard in vitro contracture test with halothane and caffeine. The present article describes a German MH pedigree carrying a spontaneous C1840-T mutation. The mutation was detected in one individual of the third generation. This person was classified as MH susceptible according to the in vitro contracture test protocol. None of the other family members (6 MH susceptible and 9 MH non-susceptible persons), including the parents of the child carrying the mutation, presented the C to T nucleotide exchange at position 1840.This novel observation clearly demonstrates that only the detection of the C1840-T mutation may lead to the diagnosis of MH susceptibility, but missing the mutation does not justify diagnosing a patient as non-susceptible within a single pedigree.

Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function.

Due to the recent progress of the DNA microarray technology, a large number of gene expression profile data are being produced. How to analyze gene expression data is an important topic in computational molecular biology. Several studies have been done using the Boolean network as a model of a genetic network. This paper proposes efficient algorithms for identifying Boolean networks of bounded indegree and related biological networks, where identification of a Boolean network can be formalized as a problem of identifying many Boolean functions simultaneously. For the identification of a Boolean network, an O(mnD+1) time naive algorithm and a simple O (mnD) time algorithm are known, where n denotes the number of nodes, m denotes the number of examples, and D denotes the maximum in degree. This paper presents an improved O(momega-2nD + mnD+omega-3) time Monte-Carlo type randomized algorithm, where omega is the exponent of matrix multiplication (currently, omega < 2.376). The algorithm is obtained by combining fast matrix multiplication with the randomized fingerprint function for string matching. Although the algorithm and its analysis are simple, the result is nontrivial and the technique can be applied to several related problems.