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

doi:10.1016/j.fsigss.2013.10.032

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 journal › Article › peer-review

11 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 language	English
Pages (from-to)	63-64
Number of pages	2
Journal	Forensic Science International: Genetics Supplement Series
Volume	4
Issue number	1
DOIs	https://doi.org/10.1016/j.fsigss.2013.10.032
Publication status	Published - 2013

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10.1016/j.fsigss.2013.10.032

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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 na{\"i}ve Bayesian classifier.",

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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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AB - 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.

KW - Biogeographical ancestry

KW - Multinomial logistic regression

KW - Phenotype prediction

KW - Structure

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DO - 10.1016/j.fsigss.2013.10.032

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JF - Forensic Science International: Genetics Supplement Series

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ER -

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

Abstract

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