The university of colorado anschutz medical campus proposes a computational biology project focused on DNA interpretation of single nucleotide polymorphism (SNP) sequencing data for investigative…

The University of Colorado Anschutz Medical Campus received a $120,000 Project Grant from the National Institute of Justice (NIJ) Research, Evaluation, and Development Project Grants program (CFDA 16.560) to conduct a computational biology research project focused on improving DNA interpretation of single nucleotide polymorphism (SNP) sequencing data for use in investigative genetic genealogy. The project aims to increase the number of forensic samples eligible for genetic genealogy by investigating SNP mixture data characteristics, developing a model to deconvolute 2-person DNA mixtures, and evaluating the accuracy of genetic genealogy searches using deconvoluted profiles across different populations. The expected outcomes include a bioinformatics framework for detecting and deconvoluting SNP mixture data, recommendations for mixture detection in forensic samples, and an assessment of the accuracy of investigative genetic genealogy with deconvoluted profiles. This research is intended to benefit forensic scientists, crime laboratories, and investigative genetic genealogy companies, ultimately increasing public safety and providing closure for crime victims.

The university of colorado anschutz medical campus proposes a computational biology project focused on DNA interpretation of single nucleotide polymorphism (SNP) sequencing data for investigative genetic genealogy. The purpose is to increase the number of samples that are eligible for genetic genealogy in forensic investigations. The project activities include investigating the characteristics and patterns of SNP mixture data to establish a limit of detection; develop a model that deconvolutes 2-person mixtures with or without a known reference sample (e.g., victim); and evaluate the accuracy of genetic genealogy searches of deconvoluted profiles across different populations. The expected outcomes include a transparent and user-friendly bioinformatics framework that detects SNP mixture data and deconvolutes 2-person mixtures, recommendations for the detection of mixtures in forensic samples and an evaluation of the accuracy of investigative genetic genealogy when using deconvoluted profiles. Informed by our results, forensic scientists, crime laboratories and partnering investigative genetic genealogy companies are the intended beneficiaries of the project. Importantly, the increased number of forensic samples eligible for investigative genetic genealogy will increase public safety and help bring closure to crime victims, therefore, communities across the nation will also benefit from this research project. CA/NCF