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Computing Power and Sample Size for Case-Control Association Studies with Copy Number Polymorphism: Application of Mixture-Based Likelihood Ratio Test

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  • Wonkuk Kim
  • Derek Gordon
  • Jonathan Sebat
  • Kenny Q Ye
  • Stephen J Finch

Abstract

Recent studies suggest that copy number polymorphisms (CNPs) may play an important role in disease susceptibility and onset. Currently, the detection of CNPs mainly depends on microarray technology. For case-control studies, conventionally, subjects are assigned to a specific CNP category based on the continuous quantitative measure produced by microarray experiments, and cases and controls are then compared using a chi-square test of independence. The purpose of this work is to specify the likelihood ratio test statistic (LRTS) for case-control sampling design based on the underlying continuous quantitative measurement, and to assess its power and relative efficiency (as compared to the chi-square test of independence on CNP counts). The sample size and power formulas of both methods are given. For the latter, the CNPs are classified using the Bayesian classification rule. The LRTS is more powerful than this chi-square test for the alternatives considered, especially alternatives in which the at-risk CNP categories have low frequencies. An example of the application of the LRTS is given for a comparison of CNP distributions in individuals of Caucasian or Taiwanese ethnicity, where the LRTS appears to be more powerful than the chi-square test, possibly due to misclassification of the most common CNP category into a less common category.

Suggested Citation

  • Wonkuk Kim & Derek Gordon & Jonathan Sebat & Kenny Q Ye & Stephen J Finch, 2008. "Computing Power and Sample Size for Case-Control Association Studies with Copy Number Polymorphism: Application of Mixture-Based Likelihood Ratio Test," PLOS ONE, Public Library of Science, vol. 3(10), pages 1-9, October.
    • Handle: RePEc:plo:pone00:0003475
    DOI: 10.1371/journal.pone.0003475
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    References listed on IDEAS

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    1. Timothy J. Aitman & Rong Dong & Timothy J. Vyse & Penny J. Norsworthy & Michelle D. Johnson & Jennifer Smith & Jonathan Mangion & Cheri Roberton-Lowe & Amy J. Marshall & Enrico Petretto & Matthew D. H, 2006. "Copy number polymorphism in Fcgr3 predisposes to glomerulonephritis in rats and humans," Nature, Nature, vol. 439(7078), pages 851-855, February.
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    Cited by:

    1. Jung Yeon Lee & Myeong-Kyu Kim & Wonkuk Kim, 2020. "Robust Linear Trend Test for Low-Coverage Next-Generation Sequence Data Controlling for Covariates," Mathematics, MDPI, vol. 8(2), pages 1-14, February.
    2. Ahn Kwangmi & Gordon Derek & Finch Stephen J, 2009. "Increase of Rejection Rate in Case-Control Studies with the Differential Genotyping Error Rates," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-11, May.

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