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 journalArticlepeer-review

10 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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