Lab Retriever: a software tool for calculating likelihood ratios incorporating a probability of drop-out for forensic DNA profiles.

BackgroundTechnological advances have enabled the analysis of very small amounts of DNA in forensic cases. However, the DNA profiles from such evidence are frequently incomplete and can contain contributions from multiple individuals. The complexity of such samples confounds the assessment of the statistical weight of such evidence. One approach to account for this uncertainty is to use a likelihood ratio framework to compare the probability of the evidence profile under different scenarios. While researchers favor the likelihood ratio framework, few open-source software solutions with a graphical user interface implementing these calculations are available for practicing forensic scientists.ResultsTo address this need, we developed Lab Retriever, an open-source, freely available program that forensic scientists can use to calculate likelihood ratios for complex DNA profiles. Lab Retriever adds a graphical user interface, written primarily in JavaScript, on top of a C++ implementation of the previously published R code of Balding. We redesigned parts of the original Balding algorithm to improve computational speed. In addition to incorporating a probability of allelic drop-out and other critical parameters, Lab Retriever computes likelihood ratios for hypotheses that can include up to four unknown contributors to a mixed sample. These computations are completed nearly instantaneously on a modern PC or Mac computer.ConclusionsLab Retriever provides a practical software solution to forensic scientists who wish to assess the statistical weight of evidence for complex DNA profiles. Executable versions of the program are freely available for Mac OSX and Windows operating systems

Forensic SNP genotyping using nanopore MinION sequencing

One of the latest developments in next generation sequencing is the Oxford Nanopore Technologies' (ONT) MinION nanopore sequencer. We studied the applicability of this system to perform forensic genotyping of the forensic female DNA standard 9947 A using the 52 SNP-plex assay developed by the SNPforID consortium. All but one of the loci were correctly genotyped. Several SNP loci were identified as problematic for correct and robust genotyping using nanopore sequencing. All these loci contained homopolymers in the sequence flanking the forensic SNP and most of them were already reported as problematic in studies using other sequencing technologies. When these problematic loci are avoided, correct forensic genotyping using nanopore sequencing is technically feasible

Microbial Similarity between Students in a Common Dormitory Environment Reveals the Forensic Potential of Individual Microbial Signatures.

The microbiota of the built environment is an amalgamation of both human and environmental sources. While human sources have been examined within single-family households or in public environments, it is unclear what effect a large number of cohabitating people have on the microbial communities of their shared environment. We sampled the public and private spaces of a college dormitory, disentangling individual microbial signatures and their impact on the microbiota of common spaces. We compared multiple methods for marker gene sequence clustering and found that minimum entropy decomposition (MED) was best able to distinguish between the microbial signatures of different individuals and was able to uncover more discriminative taxa across all taxonomic groups. Further, weighted UniFrac- and random forest-based graph analyses uncovered two distinct spheres of hand- or shoe-associated samples. Using graph-based clustering, we identified spheres of interaction and found that connection between these clusters was enriched for hands, implicating them as a primary means of transmission. In contrast, shoe-associated samples were found to be freely interacting, with individual shoes more connected to each other than to the floors they interact with. Individual interactions were highly dynamic, with groups of samples originating from individuals clustering freely with samples from other individuals, while all floor and shoe samples consistently clustered together.IMPORTANCE Humans leave behind a microbial trail, regardless of intention. This may allow for the identification of individuals based on the "microbial signatures" they shed in built environments. In a shared living environment, these trails intersect, and through interaction with common surfaces may become homogenized, potentially confounding our ability to link individuals to their associated microbiota. We sought to understand the factors that influence the mixing of individual signatures and how best to process sequencing data to best tease apart these signatures

Evaluation of nucleosome forming potentials (NFPs) of forensically important STRs

Degraded forensic samples have proved difficult to analyze and interpret. New analysis techniques are constantly being discovered and improved but researchers have overlooked the structural properties that could prevent or slow the process of degradation. In theory, DNA that are bound to histones as nucleosomes are less prone to degradation, because nucleosomes prevent DNA from being exposed to degradative enzymes. In this study we determined the probability of 60 forensic DNA markers to be bound to histones based on their base sequence composition. Two web-based tools - NXSensor and nuScore - were used to analyze four hundred base pairs surrounding each DNA marker for properties that inhibit or promote the binding of DNA to histones. Our results showed that the majority of markers analyzed were likely to be bound as nucleosomes. Selection of the markers that are more protected to form a multiplex could increase the chance of obtaining a better balanced, easier to interpret DNA profile from degraded sample

Effects of preservation method on canine (Canis lupus familiaris) fecal microbiota.

Studies involving gut microbiome analysis play an increasing role in the evaluation of health and disease in humans and animals alike. Fecal sampling methods for DNA preservation in laboratory, clinical, and field settings can greatly influence inferences of microbial composition and diversity, but are often inconsistent and under-investigated between studies. Many laboratories have utilized either temperature control or preservation buffers for optimization of DNA preservation, but few studies have evaluated the effects of combining both methods to preserve fecal microbiota. To determine the optimal method for fecal DNA preservation, we collected fecal samples from one canine donor and stored aliquots in RNAlater, 70% ethanol, 50:50 glycerol:PBS, or without buffer at 25 °C, 4 °C, and -80 °C. Fecal DNA was extracted, quantified, and 16S rRNA gene analysis performed on Days 0, 7, 14, and 56 to evaluate changes in DNA concentration, purity, and bacterial diversity and composition over time. We detected overall effects on bacterial community of storage buffer (F-value = 6.87, DF = 3, P < 0.001), storage temperature (F-value=1.77, DF = 3, P = 0.037), and duration of sample storage (F-value = 3.68, DF = 3, P < 0.001). Changes in bacterial composition were observed in samples stored in -80 °C without buffer, a commonly used method for fecal DNA storage, suggesting that simply freezing samples may be suboptimal for bacterial analysis. Fecal preservation with 70% ethanol and RNAlater closely resembled that of fresh samples, though RNAlater yielded significantly lower DNA concentrations (DF = 8.57, P < 0.001). Although bacterial composition varied with temperature and buffer storage, 70% ethanol was the best method for preserving bacterial DNA in canine feces, yielding the highest DNA concentration and minimal changes in bacterial diversity and composition. The differences observed between samples highlight the need to consider optimized post-collection methods in microbiome research

Make Research Data Public? -- Not Always so Simple: A Dialogue for Statisticians and Science Editors

Putting data into the public domain is not the same thing as making those data accessible for intelligent analysis. A distinguished group of editors and experts who were already engaged in one way or another with the issues inherent in making research data public came together with statisticians to initiate a dialogue about policies and practicalities of requiring published research to be accompanied by publication of the research data. This dialogue carried beyond the broad issues of the advisability, the intellectual integrity, the scientific exigencies to the relevance of these issues to statistics as a discipline and the relevance of statistics, from inference to modeling to data exploration, to science and social science policies on these issues.Comment: Published in at http://dx.doi.org/10.1214/10-STS320 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Effect of multiple allelic drop-outs in forensic RMNE calculations

Technological advances such as massively parallel sequencing enable increasing amounts of genetic information to be obtained from increasingly challenging samples. Certainly on low template, degraded and multi-contributor samples, drop-outs will increase in number for many profiles simply by analyzing more loci, making it difficult to probabilistically assess how many drop-outs have occurred and at which loci they might have occurred. Previously we developed a Random Man Not Excluded (RMNE) method that can take into account allelic drop-out while avoiding detailed estimations of the probability that drop-outs have occurred, nor making assumptions about at which loci these drop-outs might have occurred. The number of alleles that have dropped out, does not need to be exactly known. Here we report a generic Python algorithm to calculate the RMNE probabilities for any given number of loci. The number of allowed drop-outs can be set between 0 and twice the number of analyzed loci. The source code has been made available on https://github.com/fvnieuwe/rmne. An online web-based RMNE calculation tool has been made available on http://forensic.ugent.be/rmne. The tool can calculate these RMNE probabilities from a custom list of probabilities of the observed and non-observed alleles from any given number of loci. Using this tool, we explored the effect of allowing allelic drop-outs on the evidential value of random forensic profiles with a varying number of loci. Our results give insight into how the number of allowed drop-outs affects the evidential value of a profile and how drop-out can be managed in the RMNE approach

The effects of death and post-mortem cold ischemia on human tissue transcriptomes

Post-mortem tissues samples are a key resource for investigating patterns of gene expression. However, the processes triggered by death and the post-mortem interval (PMI) can significantly alter physiologically normal RNA levels. We investigate the impact of PMI on gene expression using data from multiple tissues of post-mortem donors obtained from the GTEx project. We find that many genes change expression over relatively short PMIs in a tissue-specific manner, but this potentially confounding effect in a biological analysis can be minimized by taking into account appropriate covariates. By comparing ante- and post-mortem blood samples, we identify the cascade of transcriptional events triggered by death of the organism. These events do not appear to simply reflect stochastic variation resulting from mRNA degradation, but active and ongoing regulation of transcription. Finally, we develop a model to predict the time since death from the analysis of the transcriptome of a few readily accessible tissues.Peer ReviewedPostprint (published version

Deriving chemosensitivity from cell lines: Forensic bioinformatics and reproducible research in high-throughput biology

High-throughput biological assays such as microarrays let us ask very detailed questions about how diseases operate, and promise to let us personalize therapy. Data processing, however, is often not described well enough to allow for exact reproduction of the results, leading to exercises in "forensic bioinformatics" where aspects of raw data and reported results are used to infer what methods must have been employed. Unfortunately, poor documentation can shift from an inconvenience to an active danger when it obscures not just methods but errors. In this report we examine several related papers purporting to use microarray-based signatures of drug sensitivity derived from cell lines to predict patient response. Patients in clinical trials are currently being allocated to treatment arms on the basis of these results. However, we show in five case studies that the results incorporate several simple errors that may be putting patients at risk. One theme that emerges is that the most common errors are simple (e.g., row or column offsets); conversely, it is our experience that the most simple errors are common. We then discuss steps we are taking to avoid such errors in our own investigations.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS291 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Beyond DNA: Epigenetics and Proteomics in Forensic Science

The use of genetic evidence in criminal cases is well established and has improved the public opinion and credibility of forensic science. However, several shortcomings associated with current genetic profiling techniques exist. Scientific research aimed at increasing the overall knowledge and understanding of biological factors will lead to the development of methods capable of improving the discriminating power of DNA evidence, overcoming limitations associated with DNA evidence, or complementing current methods of DNA profiling. Increased research in the fields of epigenetics and proteomics are particularly promising and relevant to forensic science. Research suggests that epigenetic biomarkers can be used to approximate the age of biological sample donors, differentiate between DNA of monozygotic twins, distinguish between natural and synthesized DNA, and identify body fluid sources from forensic material. Proteomic research studies indicate that mass spectrometry can be used to identify biological matrices and tissue sources from forensic biological samples without compromising DNA evidence. The demand for improved forensic techniques necessitates further research into these fields and, specifically, how the associated methods can be used in forensic science