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Front Genet. 2018 Jul 30;9:266. doi: 10.3389/fgene.2018.00266. eCollection 2018.

Correcting for Population Stratification Reduces False Positive and False Negative Results in Joint Analyses of Host and Pathogen Genomes.

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School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Precision Medicine Unit, Lausanne University Hospital, Lausanne, Switzerland.


Studies of host genetic determinants of pathogen sequence variations can identify sites of genomic conflicts, by highlighting variants that are implicated in immune response on the host side and adaptive escape on the pathogen side. However, systematic genetic differences in host and pathogen populations can lead to inflated type I (false positive) and type II (false negative) error rates in genome-wide association analyses. Here, we demonstrate through a simulation that correcting for both host and pathogen stratification reduces spurious signals and increases power to detect real associations in a variety of tested scenarios. We confirm the validity of the simulations by showing comparable results in an analysis of paired human and HIV genomes.


escape variants; genome-wide association study; host-pathogen genomics; population stratification; simulation study

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