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A nonparametric estimator of population structure unifying admixture models and principal components analysis

Irineo Cabreros, John D. Storey
doi: https://doi.org/10.1101/240812
Irineo Cabreros
Program in Applied and Computational Mathematics, Princeton University, Princeton, NJ 08544 USA. Email: cabreros@math.princeton.edu.
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  • For correspondence: cabreros@math.princeton.edu
John D. Storey
Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544 USA. Email: jstorey@princeton.edu.
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  • For correspondence: jstorey@princeton.edu
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Abstract

We introduce a simple and computationally efficient method for fitting the admixture model of genetic population structure, called ALStructure. The strategy of ALStructure is to first estimate the low-dimensional linear subspace of the population admixture components and then search for a model within this subspace that is consistent with the admixture model’s natural probabilistic constraints. Central to this strategy is the observation that all models belonging to this constrained space of solutions are risk-minimizing and have equal likelihood, rendering any additional optimization unnecessary. The low-dimensional linear subspace is estimated through a recently introduced principal components analysis method that is appropriate for genotype data, thereby providing a solution that has both principal components and probabilistic admixture interpretations. Our approach differs fundamentally from other existing methods for estimating admixture, which aim to fit the admixture model directly by searching for parameters that maximize the likelihood function or the posterior probability. We observe that ALStructure typically outperforms existing methods both in accuracy and computational speed under a wide array of simulated and real human genotype datasets. Throughout this work we emphasize that the admixture model is a special case of a much broader class of models for which algorithms similar to ALStructure may be successfully employed.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted December 29, 2017.
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A nonparametric estimator of population structure unifying admixture models and principal components analysis
Irineo Cabreros, John D. Storey
bioRxiv 240812; doi: https://doi.org/10.1101/240812
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A nonparametric estimator of population structure unifying admixture models and principal components analysis
Irineo Cabreros, John D. Storey
bioRxiv 240812; doi: https://doi.org/10.1101/240812

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