What question did this study set out to answer?

To evaluate the performance of permutation, bootstrap, and gene-dropping methods for assessing statistical significance in association studies involving unequally related individuals.

December 25, 2012GeneticsOpen Access

A Simulation Study of Permutation, Bootstrap, and Gene Dropping for Assessing Statistical Significance in the Case of Unequal Relatedness

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Authors

RCRiyan ChengUniversity of California, San Diego APAbraham A. PalmerUniversity of California, San Diego

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Implication

Simulation study reveals that model-adjusted permutations control false positives in related samples, indicating gene dropping trades power for error control when relatedness is ignored.

Key Points

To evaluate the performance of permutation, bootstrap, and gene-dropping methods for assessing statistical significance in association studies involving unequally related individuals.
Conducted simulation experiments comparing resampling-based significance testing methods, including unrestricted permutation tests and gene dropping.
Evaluated type I error rates and statistical power under scenarios where the underlying statistical model either properly accounted for relatedness or omitted it.
Unrestricted permutation tests and select simulation-based methods effectively controlled type I error rates when the statistical model appropriately adjusted for familial relatedness.
Gene dropping was the only method capable of controlling type I error rates when models failed to account for relatedness, but it did so at the expense of statistical power.

Cite This Study

Cheng et al. (2012) studied this question.

synapsesocial.com/papers/6aaa0ec7f70411fa951bfa0a https://doi.org/10.1534/genetics.112.146332

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Implication

Simulation study reveals that model-adjusted permutations control false positives in related samples, indicating gene dropping trades power for error control when relatedness is ignored.

A Simulation Study of Permutation, Bootstrap, and Gene Dropping for Assessing Statistical Significance in the Case of Unequal Relatedness

Discussion

Member takes

Implication

Key Points

Cite This Study

A Simulation Study of Permutation, Bootstrap, and Gene Dropping for Assessing Statistical Significance in the Case of Unequal Relatedness

Discussion

Member takes

Implication

Key Points

Cite This Study

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