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MixDeR: A SNP mixture deconvolution workflow for forensic genetic genealogy
Rebecca Mitchell1, Michelle Peck2, Erin Gorden2
1National Bioforensic Analysis Center, National Biodefense Analysis and Countermeasures Center, Operated by Battelle National Biodefense Institute for the US. Department of Homeland Security Science and Technology Directorate, 8300 Research Plaza, Fort Detrick, MD 21702, USA.
Abstract:
The generation of forensic DNA profiles consisting of single nucleotide polymorphisms (SNPs) is now being facilitated by wider adoption of next-generation sequencing (NGS) methods in casework laboratories. At the same time, and in part because of this advance, there is an intense focus on the generation of SNP profiles from evidentiary specimens for so-called forensic or investigative genetic genealogy (FGG or IGG) applications. However, FGG methods are constrained by the algorithms for genealogical database searches, which were designed for use with single-source profiles, and the fact that many forensic samples are mixtures. To enable the use of two-person mixtures for FGG, we developed a workflow, MixDeR, for the deconvolution of mixed SNP profiles. MixDeR, a flexible and easy to use R package and Shiny app, processes ForenSeq Kintelligence® (QIAGEN, Inc.) SNP genotyping results and directs deconvolution of the profiles in EuroForMix (EFM). MixDeR then filters the EFM outputs to produce inferred single-source genotypes in reports formatted for use with GEDmatch® PRO. An optional MixDeR output includes metrics that assist with testing and validation of the workflow. As the Shiny app provides a graphical user interface and the software is designed to be run offline, MixDeR should be suitable for use by any laboratory developing FGG capabilities, no matter their bioinformatic resources or expertise.
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