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bioRxiv · 10.1101/052068

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics

Il-Youp Kwak·Wei Pan
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Abstract

To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene-or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP-and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or p-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods.\n\nThe methods are implemented in R package aSPU, freely and publicly available on CRAN at: https://cran.r-project.org/web/packages/aSPU/.

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Il-Youp Kwak, Wei Pan. 2016-05-07. Gene- and pathway-based association tests for multiple traits with GWAS summary statistics. https://doi.org/10.1101/052068

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