GAGA: a new algorithm for genomic inference of geographic ancestry reveals fine level population substructure in Europeans.

ABSTRACT: Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the

SUBMITTER: Lao O 

PROVIDER: S-EPMC3930519 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature