An assessment of Bayesian and multinomial logistic regression classification systems to analyse admixed individuals

Dennis MCNEVIN, C. Santos, A. Gómez-Tato, J. Álvarez-Dios, M. Casares de Cal, R. Daniel, C. Phillips, M. V. Lareu

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Multinomial logistic regression (MLR) has been applied to the prediction of hair and eye colour. Here we apply it to the prediction of biogeographical ancestry (BGA) in a test set of 1092 admixed and non-admixed genotypes from the 1000 Genomes Project using a training set of 571 non-admixed genotypes from the HGDP CEPH cell line panel. Predicted BGAs are consistent with those of Structure, a naïve Bayesian classifier.
Original languageEnglish
Pages (from-to)63-64
Number of pages2
JournalForensic Science International: Genetics Supplement Series
Volume4
Issue number1
DOIs
Publication statusPublished - 2013

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Logistic Models
Genotype
Hair Color
Eye Color
Genome
Cell Line

Cite this

MCNEVIN, Dennis ; Santos, C. ; Gómez-Tato, A. ; Álvarez-Dios, J. ; de Cal, M. Casares ; Daniel, R. ; Phillips, C. ; Lareu, M. V. / An assessment of Bayesian and multinomial logistic regression classification systems to analyse admixed individuals. In: Forensic Science International: Genetics Supplement Series. 2013 ; Vol. 4, No. 1. pp. 63-64.
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An assessment of Bayesian and multinomial logistic regression classification systems to analyse admixed individuals. / MCNEVIN, Dennis; Santos, C.; Gómez-Tato, A.; Álvarez-Dios, J.; de Cal, M. Casares; Daniel, R.; Phillips, C.; Lareu, M. V.

In: Forensic Science International: Genetics Supplement Series, Vol. 4, No. 1, 2013, p. 63-64.

Research output: Contribution to journalArticle

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AU - MCNEVIN, Dennis

AU - Santos, C.

AU - Gómez-Tato, A.

AU - Álvarez-Dios, J.

AU - de Cal, M. Casares

AU - Daniel, R.

AU - Phillips, C.

AU - Lareu, M. V.

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KW - Phenotype prediction

KW - Structure

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