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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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COMBAT: A Combined Association Test for Genes Using Summary Statistics.

Minghui Wang1, Jianfei Huang2,3, Yiyuan Liu4

  • 1Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York 10029.

Genetics
|September 8, 2017
PubMed
Summary
This summary is machine-generated.

We developed a combined association test (COMBAT) to improve the detection of genetic variants linked to complex diseases. This method enhances the power of gene-based association studies using summary statistics from genome-wide association studies (GWAS).

Keywords:
GWASassociationcomplex diseasegene-based testsummary statistics

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Area of Science:

  • Genetics
  • Biostatistics
  • Complex disease genetics

Background:

  • Genome-wide association studies (GWAS) identify common variants for complex diseases.
  • Single nucleotide polymorphism (SNP)-level analysis has limited power for detecting variants with small effect sizes.
  • Existing gene-based tests have variable power depending on the genetic model.

Purpose of the Study:

  • To develop a robust and powerful gene-based association test.
  • To overcome the limitations of individual gene-based tests in complex disease genetics.
  • To provide a method that utilizes readily available GWAS summary statistics.

Main Methods:

  • Proposed a combined association test (COMBAT) integrating strengths of existing gene-based tests.
  • Developed COMBAT to use SNP-level P-values and SNP correlations, not raw data.
  • Evaluated COMBAT using extensive simulations and reanalysis of bipolar disorder GWAS data.

Main Results:

  • COMBAT demonstrated appropriate type I error rates in simulations.
  • COMBAT maintained higher statistical power across diverse genetic models compared to individual tests.
  • COMBAT showed superior performance and robustness in analyzing bipolar disorder GWAS data.

Conclusions:

  • COMBAT offers a more powerful approach for gene-based association analysis in complex diseases.
  • The method is broadly applicable due to its reliance on public GWAS summary results.
  • COMBAT enhances the utility of GWAS for understanding the genetic architecture of complex diseases.