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Tvedebrink T. Review of the Forensic Applicability of Biostatistical Methods for Inferring Ancestry from Autosomal Genetic Markers. Genes (Basel) 2022; 13:genes13010141. [PMID: 35052480 PMCID: PMC8774801 DOI: 10.3390/genes13010141] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/10/2022] [Accepted: 01/11/2022] [Indexed: 02/01/2023] Open
Abstract
The inference of ancestry has become a part of the services many forensic genetic laboratories provide. Interest in ancestry may be to provide investigative leads or identify the region of origin in cases of unidentified missing persons. There exist many biostatistical methods developed for the study of population structure in the area of population genetics. However, the challenges and questions are slightly different in the context of forensic genetics, where the origin of a specific sample is of interest compared to the understanding of population histories and genealogies. In this paper, the methodologies for modelling population admixture and inferring ancestral populations are reviewed with a focus on their strengths and weaknesses in relation to ancestry inference in the forensic context.
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Affiliation(s)
- Torben Tvedebrink
- Department of Mathematical Sciences, Aalborg University, DK-9220 Aalborg, Denmark;
- Section of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, DK-1165 Copenhagen, Denmark
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Frégeau CJ. A multiple predictive tool approach for phenotypic and biogeographical ancestry inferences. CANADIAN SOCIETY OF FORENSIC SCIENCE JOURNAL 2021. [DOI: 10.1080/00085030.2021.2016206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Chantal J. Frégeau
- Royal Canadian Mounted Police, Forensic Science & Identification Services, Biology Policy & Program Support, Ottawa, ON, Canada
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Orozco-Acosta E, LLinás-Solano H, Fonseca-Rodríguez J. Convergence Theorems in Multinomial Saturated and Logistic Models. REVISTA COLOMBIANA DE ESTADÍSTICA 2020. [DOI: 10.15446/rce.v43n2.79151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
In this paper, we develop a theoretical study about the logistic and saturated multinomial models when the response variable takes one of R ≥ 2 levels. Several theorems on the existence and calculations of the maximum likelihood (ML) estimates of the parameters of both models are presented and demonstrated. Furthermore, properties are identified and, based on an asymptotic theory, convergence theorems are tested for score vectors and information matrices of both models. Finally, an application of this theory is presented and assessed using data from the R statistical program.
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Differentiation of Hispanic biogeographic ancestry with 80 ancestry informative markers. Sci Rep 2020; 10:7745. [PMID: 32385290 PMCID: PMC7210943 DOI: 10.1038/s41598-020-64245-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 04/03/2020] [Indexed: 11/09/2022] Open
Abstract
Ancestry informative single nucleotide polymorphisms (SNPs) can identify biogeographic ancestry (BGA); however, population substructure and relatively recent admixture can make differentiation difficult in heterogeneous Hispanic populations. Utilizing unrelated individuals from the Genomic Origins and Admixture in Latinos dataset (GOAL, n = 160), we designed an 80 SNP panel (Setser80) that accurately depicts BGA through STRUCTURE and PCA. We compared our Setser80 to the Seldin and Kidd panels via resampling simulations, which models data based on allele frequencies. We incorporated Admixed American 1000 Genomes populations (1000 G, n = 347), into a combined populations dataset to determine robustness. Using multinomial logistic regression (MLR), we compared the 3 panels on the combined dataset and found overall MLR classification accuracies: 93.2% Setser80, 87.9% Seldin panel, 71.4% Kidd panel. Naïve Bayesian classification had similar results on the combined dataset: 91.5% Setser80, 84.7% Seldin panel, 71.1% Kidd panel. Although Peru and Mexico were absent from panel design, we achieved high classification accuracy on the combined populations for Peru (MLR = 100%, naïve Bayes = 98%), and Mexico (MLR = 90%, naïve Bayes = 83.4%) as evidence of the portability of the Setser80. Our results indicate the Setser80 SNP panel can reliably classify BGA for individuals of presumed Hispanic origin.
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Neparáczki E, Maróti Z, Kalmár T, Maár K, Nagy I, Latinovics D, Kustár Á, Pálfi G, Molnár E, Marcsik A, Balogh C, Lőrinczy G, Gál SS, Tomka P, Kovacsóczy B, Kovács L, Raskó I, Török T. Y-chromosome haplogroups from Hun, Avar and conquering Hungarian period nomadic people of the Carpathian Basin. Sci Rep 2019; 9:16569. [PMID: 31719606 PMCID: PMC6851379 DOI: 10.1038/s41598-019-53105-5] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 10/26/2019] [Indexed: 01/08/2023] Open
Abstract
Hun, Avar and conquering Hungarian nomadic groups arrived to the Carpathian Basin from the Eurasian Steppes and significantly influenced its political and ethnical landscape, however their origin remains largely unknown. In order to shed light on the genetic affinity of above groups we have determined Y chromosomal haplogroups and autosomal loci, suitable to predict biogeographic ancestry, from 49 individuals, supposed to represent the power/military elit. Haplogroups from the Hun-age are consistent with Xiongnu ancestry of European Huns. Most of the Avar-age individuals carry east Eurasian Y haplogroups typical for modern north-eastern Siberian and Buryat populations and their autosomal loci indicate mostly un-admixed Asian characteristics. In contrast the conquering Hungarians seem to be a recently assembled population incorporating un-admixed European, Asian as well as admixed components. Their heterogeneous paternal and maternal lineages indicate similar supposed phylogeographic origin of males and females, derived from Central-Inner Asian and European Pontic Steppe sources.
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Affiliation(s)
- Endre Neparáczki
- Department of Genetics, University of Szeged, Szeged, H-6726, Hungary
| | - Zoltán Maróti
- Department of Pediatrics and Pediatric Health Center, University of Szeged, Szeged, H-6720, Hungary
| | - Tibor Kalmár
- Department of Pediatrics and Pediatric Health Center, University of Szeged, Szeged, H-6720, Hungary
| | - Kitti Maár
- Department of Genetics, University of Szeged, Szeged, H-6726, Hungary
| | - István Nagy
- SeqOmics Biotechnology Ltd., Mórahalom, H-6782, Hungary.,Institute of Biochemistry, Biological Research Centre of the Hun. Acad. Sci, Szeged, H-6726, Hungary
| | | | - Ágnes Kustár
- Department of Anthropology, Hungarian Natural History Museum, Budapest, H-1083, Hungary
| | - György Pálfi
- Department of Biological Anthropology, University of Szeged, Szeged, H-6726, Hungary
| | - Erika Molnár
- Department of Biological Anthropology, University of Szeged, Szeged, H-6726, Hungary
| | - Antónia Marcsik
- Department of Biological Anthropology, University of Szeged, Szeged, H-6726, Hungary
| | - Csilla Balogh
- Department of Art History, Istanbul Medeniyet University, Istanbul, 34700, Turkey
| | | | | | - Péter Tomka
- Department of Archaeology, Flóris Rómer Museum of Art and History, H-9024, Győr, Hungary
| | | | - László Kovács
- Institute of Archaeology of the Center for Humanities of the Hun. Acad. Sci, Budapest, Hungary
| | - István Raskó
- Institute of Genetics, Biological Research Centre of the Hun. Acad. Sci, Szeged, H-6726, Hungary
| | - Tibor Török
- Department of Genetics, University of Szeged, Szeged, H-6726, Hungary.
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