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The impact of a fine-scale population stratification on rare variant association test results

Author

Listed:
  • Elodie Persyn
  • Richard Redon
  • Lise Bellanger
  • Christian Dina

Abstract

Population stratification is a well-known confounding factor in both common and rare variant association analyses. Rare variants tend to be more geographically clustered than common variants, because of their more recent origin. However, it is not yet clear if population stratification at a very fine scale (neighboring administrative regions within a country) would lead to statistical bias in rare variant analyses. As the inclusion of convenience controls from external studies is indeed a common procedure, in order to increase the power to detect genetic associations, this problem is important. We studied through simulation the impact of a fine scale population structure on different rare variant association strategies, assessing type I error and power. We showed that principal component analysis (PCA) based methods of adjustment for population stratification adequately corrected type I error inflation at the largest geographical scales, but not at finest scales. We also showed in our simulations that adding controls obviously increased power, but at a considerably lower level when controls were drawn from another population.

Suggested Citation

  • Elodie Persyn & Richard Redon & Lise Bellanger & Christian Dina, 2018. "The impact of a fine-scale population stratification on rare variant association test results," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-17, December.
  • Handle: RePEc:plo:pone00:0207677
    DOI: 10.1371/journal.pone.0207677
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    References listed on IDEAS

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