Mixed DNA profiles
Optimized, Semi-Automated Differential DNA Extraction
An Automated Single Cell Separation Technique to Improve Mixture Deconvolution
This webinar will provide an evaluation of the DEPArray™, a system that enables the identification, separation, and recovery of single cells or groups of cells from heterogeneous mixtures. The workflow described in this webinar will highlight the impact this instrument, with standard forensic processes, will have on processing sexual assault evidence and improving the success of single cell analyses.
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PACE™: Rapid and Automated Artifact Identification and Number of Contributor Prediction
This webinar focused on the use of PACE™, a method developed by Syracuse University, to perform artifact management and probabilistically predict the number of contributors (NOC) in forensic DNA samples. This is performed using a combination of biological modeling and machine learning, permitting high accuracy NOC calls (greater than 90%) of complex mixtures. It does so rapidly (seconds to minutes) without the need for high performance computing resources.
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Highly Informative Short Tandem Repeat Markers for Enhanced DNA Mixture Deconvolution
Enhanced DNA Profiling of the Semen Donor in Late Reported Sexual Assaults: Use of Y-Chromosome-Targeted Pre-amplification and Next Generation Y-STR Amplification Systems
Study of CTS DNA Proficiency Tests with Regard to DNA Mixture Interpretation: A NIST Scientific Foundation Review
Development of a Nuclear SNP Probe Capture Assay for Massively Parallel Sequencing of Degraded and Mixed DNA Samples
Identification and Mixture Deconvolution of Ancient and Forensic DNA using Population Genomic Data
Resolving the Forensic DNA Mixture Problem through the Development of End-to-End Single-Cell Pipelines
Interpreting a Major Component From a Mixed DNA Profile With an Unknown Number of Minor Contributors
Best Practices for Forensic Laboratories Adopting Probabilistic Genotyping Systems
DNA Mixtures