TY  - JOUR
AB  - © 2016, Springer-Verlag Berlin Heidelberg. DNA can provide forensic intelligence regarding a donor?s biogeographical ancestry (BGA) and other externally visible characteristics (EVCs). A number of algorithms have been proposed to assign individual human genotypes to a BGA using ancestry informative marker (AIM) panels. This study compares the BGA assignment accuracy of the population clustering program STRUCTURE and three generic classification approaches including a Bayesian algorithm, genetic distance, and multinomial logistic regression (MLR). A selection of 142 ancestry informative single nucleotide polymorphisms (SNPs) were chosen from existing marker panels (SNPforID 34-plex, Eurasiaplex, Seldin, and Kidd?s AIM panels) to assess BGA classification at the continental level for Africans, Europeans, East Asians, and Amerindians. A training set of 1093 individuals with self-declared BGA from the 1000 Genomes phase 1 database was used by each classifier to predict BGA in a test set of 516 individuals from the HGDP-CEPH (Stanford) cell line panel. Tests were repeated with 0, 10, 50, 70, and 90% of the genotypes missing. Comparison of the area under the receiver operating characteristic curves (AUROCs) showed high accuracy in STRUCTURE and the generic Bayesian approach. The latter algorithm offers a computationally simpler alternative to STRUCTURE with little loss in accuracy and is suitable for phenotype prediction while STRUCTURE is not.
AU  - Cheung, EYY
AU  - Gahan, ME
AU  - McNevin, D
DA  - 2017/07/01
DO  - 10.1007/s00414-016-1504-3
EP  - 912
JO  - International Journal of Legal Medicine
PY  - 2017/07/01
SP  - 901
TI  - Prediction of biogeographical ancestry from genotype: a comparison of classifiers
VL  - 131
Y1  - 2017/07/01
Y2  - 2026/06/28
ER  -