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A functional U-statistic method for association analysis of sequencing data.

Sneha Jadhav1, Xiaoran Tong2, Qing Lu2

  • 1Department of Statistics and Probability, Michigan State University, East Lansing, Michigan, United States of America.

Genetic Epidemiology
|August 30, 2017
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Summary
This summary is machine-generated.

We developed a new method for analyzing complex genetic sequencing data with multiple disease traits. This functional U-statistic method (FU) improves the identification of disease-associated genes, showing promise in real-world applications.

Keywords:
Functional data analysismultivariate methodnonparametric methodsimilarity measure

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Area of Science:

  • Genetics
  • Statistical genetics
  • Bioinformatics

Background:

  • Sequencing studies offer potential for discovering disease-predisposing variants.
  • High-dimensional sequencing data and multiple related phenotypes present significant analytical challenges.
  • Jointly analyzing diverse phenotypes can enhance the power to identify disease-associated genes.

Purpose of the Study:

  • To propose a novel nonparametric method for multivariate analysis of sequencing data.
  • To address challenges posed by multiple, diverse phenotypes in genetic association studies.
  • To develop a flexible framework for analyzing complex genetic data and phenotypes.

Main Methods:

  • Introduced the functional U-statistic method (FU) for multivariate sequencing data analysis.
  • Constructed smooth functions from individual sequencing data.
  • Utilized U-statistics to test associations between genetic functions and multiple phenotypes.
  • Incorporated gene structure complexities like linkage disequilibrium (LD) using smoothing functions.

Main Results:

  • The FU method demonstrated superior performance compared to the multivariate outcome score test (MOST) in simulations.
  • Applied FU to Minnesota Twin Study (MTS) sequencing data.
  • Identified potential associations between CHRN genes (e.g., CHRNB3) and nicotine or alcohol dependence.

Conclusions:

  • The functional U-statistic method provides a robust framework for multivariate genetic association analysis.
  • FU enhances the ability to detect gene-phenotype associations, particularly with complex traits.
  • The method shows promise for uncovering genetic underpinnings of complex diseases like substance dependence.