SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA

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Standard

SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA. / Köksal, Zehra; Børsting, Claus; Gusmao, Leonor; Pereira, Vania.

I: Genes, Bind 14, Nr. 10, 1837, 2023.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Köksal, Z, Børsting, C, Gusmao, L & Pereira, V 2023, 'SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA', Genes, bind 14, nr. 10, 1837. https://doi.org/10.3390/genes14101837

APA

Köksal, Z., Børsting, C., Gusmao, L., & Pereira, V. (2023). SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA. Genes, 14(10), [1837]. https://doi.org/10.3390/genes14101837

Vancouver

Köksal Z, Børsting C, Gusmao L, Pereira V. SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA. Genes. 2023;14(10). 1837. https://doi.org/10.3390/genes14101837

Author

Köksal, Zehra ; Børsting, Claus ; Gusmao, Leonor ; Pereira, Vania. / SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA. I: Genes. 2023 ; Bind 14, Nr. 10.

Bibtex

@article{8fcaa258b633405d90617eaa3cf2b527,
title = "SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA",
abstract = "Genetic variants on non-recombining DNA and the hierarchical order in which they accumulate are commonly of interest. This variant hierarchy can be established and combined with information on the population and geographic origin of the individuals carrying the variants to find population structures and infer migration patterns. Further, individuals can be assigned to the characterized populations, which is relevant in forensic genetics, genetic genealogy, and epidemiologic studies. However, there is currently no straightforward method to obtain such a variant hierarchy. Here, we introduce the software SNPtotree v1.0, which uniquely determines the hierarchical order of variants on non-recombining DNA without error-prone manual sorting. The algorithm uses pairwise variant comparisons to infer their relationships and integrates the combined information into a phylogenetic tree. Variants that have contradictory pairwise relationships or ambiguous positions in the tree are removed by the software. When benchmarked using two human Y-chromosomal massively parallel sequencing datasets, SNPtotree outperforms traditional methods in the accuracy of phylogenetic trees for sequencing data with high amounts of missing information. The phylogenetic trees of variants created using SNPtotree can be used to establish and maintain publicly available phylogeny databases to further explore genetic epidemiology and genealogy, as well as population and forensic genetics.",
author = "Zehra K{\"o}ksal and Claus B{\o}rsting and Leonor Gusmao and Vania Pereira",
year = "2023",
doi = "10.3390/genes14101837",
language = "English",
volume = "14",
journal = "Genes",
issn = "2073-4425",
publisher = "M D P I AG",
number = "10",

}

RIS

TY - JOUR

T1 - SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA

AU - Köksal, Zehra

AU - Børsting, Claus

AU - Gusmao, Leonor

AU - Pereira, Vania

PY - 2023

Y1 - 2023

N2 - Genetic variants on non-recombining DNA and the hierarchical order in which they accumulate are commonly of interest. This variant hierarchy can be established and combined with information on the population and geographic origin of the individuals carrying the variants to find population structures and infer migration patterns. Further, individuals can be assigned to the characterized populations, which is relevant in forensic genetics, genetic genealogy, and epidemiologic studies. However, there is currently no straightforward method to obtain such a variant hierarchy. Here, we introduce the software SNPtotree v1.0, which uniquely determines the hierarchical order of variants on non-recombining DNA without error-prone manual sorting. The algorithm uses pairwise variant comparisons to infer their relationships and integrates the combined information into a phylogenetic tree. Variants that have contradictory pairwise relationships or ambiguous positions in the tree are removed by the software. When benchmarked using two human Y-chromosomal massively parallel sequencing datasets, SNPtotree outperforms traditional methods in the accuracy of phylogenetic trees for sequencing data with high amounts of missing information. The phylogenetic trees of variants created using SNPtotree can be used to establish and maintain publicly available phylogeny databases to further explore genetic epidemiology and genealogy, as well as population and forensic genetics.

AB - Genetic variants on non-recombining DNA and the hierarchical order in which they accumulate are commonly of interest. This variant hierarchy can be established and combined with information on the population and geographic origin of the individuals carrying the variants to find population structures and infer migration patterns. Further, individuals can be assigned to the characterized populations, which is relevant in forensic genetics, genetic genealogy, and epidemiologic studies. However, there is currently no straightforward method to obtain such a variant hierarchy. Here, we introduce the software SNPtotree v1.0, which uniquely determines the hierarchical order of variants on non-recombining DNA without error-prone manual sorting. The algorithm uses pairwise variant comparisons to infer their relationships and integrates the combined information into a phylogenetic tree. Variants that have contradictory pairwise relationships or ambiguous positions in the tree are removed by the software. When benchmarked using two human Y-chromosomal massively parallel sequencing datasets, SNPtotree outperforms traditional methods in the accuracy of phylogenetic trees for sequencing data with high amounts of missing information. The phylogenetic trees of variants created using SNPtotree can be used to establish and maintain publicly available phylogeny databases to further explore genetic epidemiology and genealogy, as well as population and forensic genetics.

U2 - 10.3390/genes14101837

DO - 10.3390/genes14101837

M3 - Journal article

C2 - 37895186

VL - 14

JO - Genes

JF - Genes

SN - 2073-4425

IS - 10

M1 - 1837

ER -

ID: 367548345