MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies

Toomas Haller, Liis Leitsalu, Krista Fischer, Marja-Liisa Nuotio, Tonu Esko, Dorothea Irene Boomsma, Kirsten Ohm Kyvik, Tim D Spector, Markus Perola, Andres Metspalu

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Resumé

Ancestry information at the individual level can be a valuable resource for personalized medicine, medical, demographical and history research, as well as for tracing back personal history. We report a new method for quantitatively determining personal genetic ancestry based on genome-wide data. Numerical ancestry component scores are assigned to individuals based on comparisons with reference populations. These comparisons are conducted with an existing analytical pipeline making use of genotype phasing, similarity matrix computation and our addition-multidimensional best fitting by MixFit. The method is demonstrated by studying Estonian and Finnish populations in geographical context. We show the main differences in the genetic composition of these otherwise close European populations and how they have influenced each other. The components of our analytical pipeline are freely available computer programs and scripts one of which was developed in house (available at: www.geenivaramu.ee/en/tools/mixfit).

OriginalsprogEngelsk
Artikelnummere0170325
TidsskriftPLOS ONE
Vol/bind12
Udgave nummer1
Antal sider14
ISSN1932-6203
DOI
StatusUdgivet - 2017

Fingeraftryk

Computing Methodologies
computer techniques
ancestry
Pipelines
Population
Medicine
Computer program listings
Precision Medicine
Genes
medicine
History
Chemical analysis
history
genome
genotype
methodology
Research

Citer dette

Haller, Toomas ; Leitsalu, Liis ; Fischer, Krista ; Nuotio, Marja-Liisa ; Esko, Tonu ; Boomsma, Dorothea Irene ; Kyvik, Kirsten Ohm ; Spector, Tim D ; Perola, Markus ; Metspalu, Andres. / MixFit : Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies. I: PLOS ONE. 2017 ; Bind 12, Nr. 1.
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abstract = "Ancestry information at the individual level can be a valuable resource for personalized medicine, medical, demographical and history research, as well as for tracing back personal history. We report a new method for quantitatively determining personal genetic ancestry based on genome-wide data. Numerical ancestry component scores are assigned to individuals based on comparisons with reference populations. These comparisons are conducted with an existing analytical pipeline making use of genotype phasing, similarity matrix computation and our addition-multidimensional best fitting by MixFit. The method is demonstrated by studying Estonian and Finnish populations in geographical context. We show the main differences in the genetic composition of these otherwise close European populations and how they have influenced each other. The components of our analytical pipeline are freely available computer programs and scripts one of which was developed in house (available at: www.geenivaramu.ee/en/tools/mixfit).",
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Haller, T, Leitsalu, L, Fischer, K, Nuotio, M-L, Esko, T, Boomsma, DI, Kyvik, KO, Spector, TD, Perola, M & Metspalu, A 2017, 'MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies', PLOS ONE, bind 12, nr. 1, e0170325. https://doi.org/10.1371/journal.pone.0170325

MixFit : Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies. / Haller, Toomas; Leitsalu, Liis; Fischer, Krista; Nuotio, Marja-Liisa; Esko, Tonu; Boomsma, Dorothea Irene; Kyvik, Kirsten Ohm; Spector, Tim D; Perola, Markus; Metspalu, Andres.

I: PLOS ONE, Bind 12, Nr. 1, e0170325, 2017.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

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AU - Leitsalu, Liis

AU - Fischer, Krista

AU - Nuotio, Marja-Liisa

AU - Esko, Tonu

AU - Boomsma, Dorothea Irene

AU - Kyvik, Kirsten Ohm

AU - Spector, Tim D

AU - Perola, Markus

AU - Metspalu, Andres

PY - 2017

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AB - Ancestry information at the individual level can be a valuable resource for personalized medicine, medical, demographical and history research, as well as for tracing back personal history. We report a new method for quantitatively determining personal genetic ancestry based on genome-wide data. Numerical ancestry component scores are assigned to individuals based on comparisons with reference populations. These comparisons are conducted with an existing analytical pipeline making use of genotype phasing, similarity matrix computation and our addition-multidimensional best fitting by MixFit. The method is demonstrated by studying Estonian and Finnish populations in geographical context. We show the main differences in the genetic composition of these otherwise close European populations and how they have influenced each other. The components of our analytical pipeline are freely available computer programs and scripts one of which was developed in house (available at: www.geenivaramu.ee/en/tools/mixfit).

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