The genetic component of forensic genetic genealogy (FGG) is an estimate of kinship, often conducted at genome scales between a great number of individuals. The promise of FGG is substantial: in concert with genealogical records, it can identify a person of interest without a direct reference sample to compare against. However, at present there are no tools that allow FGG investigations when the sample is a DNA mixture. We present Demixtify (v2), a free open-source tool that deconvolves two-person mixtures from shotgun whole genome sequencing data. Demixtify estimates the mixture fraction (mf) using a broad sampling of intermediate frequency low FST markers. Next, it estimates the joint genotype likelihood of both contributors (given the mf), and it extracts the marginal (deconvolved) likelihoods and genotypes into a standard format for genomic information (VCF). Simple tools are also provided to convert these data into a GEDmatch-compliant file format. We evaluate Demixtify considering both in silico and in vitro DNA mixtures, and contrast its performance when a single contributor’s genotypes are known against its limits when there are two unknown contributors.
The genetic component of forensic genetic genealogy (FGG) is an estimate of kinship, often conducted at genome scales between a great number of individuals. The promise of FGG is substantial: in concert with genealogical records, it can identify a person of interest without a direct reference sample to compare against. However, at present there are no tools that allow FGG investigations when the sample is a DNA mixture. We present Demixtify (v2), a free open-source tool that deconvolves two-person mixtures from shotgun whole genome sequencing data. Demixtify estimates the mixture fraction (mf) using a broad sampling of intermediate frequency low FST markers. Next, it estimates the joint genotype likelihood of both contributors (given the mf), and it extracts the marginal (deconvolved) likelihoods and genotypes into a standard format for genomic information (VCF). Simple tools are also provided to convert these data into a GEDmatch-compliant file format. We evaluate Demixtify considering both in silico and in vitro DNA mixtures, and contrast its performance when a single contributor’s genotypes are known against its limits when there are two unknown contributors.
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Associate Professor, Center for Human Identification (CHI), University of North Texas Health Science Center
August Woerner is an Assistant Professor in the department of Microbiology, Immunology and Genetics at the University of North Texas Health Science Center. Much of August’s current research focuses on whole genome sequencing, particular, its application to forensic genetic genealogy.
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