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Combining dependent p-values by gamma distributions.

Li-Chu Chien1

  • 1Center for Fundamental Science, Kaohsiung Medical University, Kaohsiung, Taiwan.

Statistical Applications in Genetics and Molecular Biology
|November 6, 2020
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Summary
This summary is machine-generated.

This study introduces an empirical method based on the gamma distribution (EMGD) for combining correlated p-values in genetic data analysis. EMGD offers robust type I error control and good statistical power for multiple hypothesis testing.

Keywords:
correlated p-valuesempirical Brown’s methodgamma distributionmultiple hypothesis testing

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Area of Science:

  • Genetics and Genomics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Combining p-values from multiple hypothesis testing is crucial for genetic and genomic data analysis.
  • Existing methods often fail with correlated p-values, limiting their application in complex genetic studies.
  • A need exists for methods that robustly control errors and maintain power when combining dependent p-values.

Purpose of the Study:

  • To propose a novel method for combining dependent p-values in multiple hypothesis testing.
  • To develop a method that accommodates highly correlated p-values effectively.
  • To ensure robust type I error control and good statistical power in genetic association studies.

Main Methods:

  • An empirical method based on the gamma distribution (EMGD) was developed.
  • EMGD integrates dependent p-values into a unified p-value for combined hypothesis testing.
  • The method builds upon the strengths of the empirical Brown's method (EBM) and gamma distribution approaches.

Main Results:

  • The proposed EMGD method demonstrates flexibility in handling highly correlated p-values.
  • EMGD retains the robustness of EBM for pooling dependent p-values.
  • Simulations and real data applications show EMGD maintains robust power for combining dependent p-values.

Conclusions:

  • The EMGD method provides a robust approach for combining correlated p-values in genetic analyses.
  • EMGD offers an effective solution for integrating information from multiple hypothesis tests with dependent p-values.
  • This method enhances the power and reliability of genetic and genomic data analysis.