Inherent Nonlinear Distribution of High-Dimensional Genotypic Data Identified as a Possible Source of Confounding Factors in Population Structure Analysis.

Abstract excerpt

It has become routing work to detect and correct for population structure in genome-wide association analysis. A variety of methods have been proposed. Particularly, the methods based on spectral graph theory have shown superior performance. We discovered that the inherent nonlinear distribution of high-dimensional genotypic data was a possible source of confounding factors in population structure analysis, and...

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