ABSTRACT
The data management, interpretation and comparison of sets of DNA profiles can be complex, time-consuming and error-prone when performed manually. This, combined with the growing numbers of genetic markers in forensic identification systems calls for expert systems that can automatically compare genotyping results within (large) sets of DNA profiles and assist in profile interpretation. To that aim, we developed a user-friendly software program or DNA eXpert System that is denoted DNAxs. This software includes features to view, infer and match autosomal short tandem repeat profiles with connectivity to up and downstream software programs. Furthermore, DNAxs has imbedded the 'DNAStatistX' module, a statistical library that contains a probabilistic algorithm to calculate likelihood ratios (LRs). This algorithm is largely based on the source code of the quantitative probabilistic genotyping system EuroForMix [1]. The statistical library, DNAStatistX, supports parallel computing which can be delegated to a computer cluster and enables automated queuing of requested LR calculations. DNAStatistX is written in Java and is accessible separately or via DNAxs. Using true and non-contributors to DNA profiles with up to four contributors, the DNAStatistX accuracy and precision were assessed by comparing the DNAStatistX results to those of EuroForMix. Results were the same up to rare differences that could be attributed to the different optimizers used in both software programs. Implementation of dye specific detection thresholds resulted in larger likelihood values and thus a better explanation of the data used in this study. Furthermore, processing time, robustness of DNAStatistX results and the circumstances under which model validations failed were examined. Finally, guidelines for application of the software are shared as an example. The DNAxs software is future-proof as it applies a modular approach by which novel functionalities can be incorporated.
Subject(s)
DNA Fingerprinting , Data Management , Likelihood Functions , Software , Algorithms , DNA, Mitochondrial/genetics , Datasets as Topic , Genotyping Techniques , High-Throughput Nucleotide Sequencing , Humans , Microsatellite Repeats , Software Design , Statistics as TopicABSTRACT
DNA analysis has become an essential intelligence tool in the criminal justice system for the identification of possible offenders. However, it appears that about half of the processed DNA samples contains too little DNA for analysis. This study looks at DNA success rates within 28 different categories of trace exhibits and relates the DNA concentration to the characteristics of the DNA profile. Data from 2260 analyzed crime samples show that cigarettes, bloodstains, and headwear have relatively high success rates. Cartridge cases, crowbars, and tie-wraps are on the other end of the spectrum. These objective data can assist forensics in their selection process.The DNA success probability shows a positive relation with the DNA concentration. This finding enables the laboratory to set an evidence-based threshold value in the DNA analysis process. For instance, 958 DNA extracts had a concentration value of 6 pg/µL or less. Only 46 of the 958 low-level extracts provided meaningful DNA profiling data.
Subject(s)
Blood Stains , DNA Fingerprinting , DNA/analysis , Crime , Criminals , HumansABSTRACT
We present a case of acquired von Willebrand syndrome (AVWS) due to a monoclonal gammopathy of undetermined significance. Initially this case was diagnosed as congenital von Willebrand disease (VWD); however, re-examination of the medical history rendered a congenital bleeding disorder unlikely. A normal plasma von Willebrand factor (VWF) propeptide level and a very short half-life of VWF after a test infusion with factor VIII/VWF concentrate confirmed the diagnosis AVWS. Two major surgical procedures were successfully managed using high-dose intravenous immunoglobulin. The differential diagnosis with congenital VWD and the diagnostic and therapeutic approaches of AVWS are discussed. We conclude that the diagnosis of AVWS relies primarily on clinical suspicion and a careful bleeding history. A correct diagnosis is essential for optimal perioperative management and treatment of bleeding episodes.
