PT  - JOURNAL ARTICLE
AU  - Il-Youp Kwak
AU  - Wei Pan
TI  - Gene- and pathway-based association tests for multiple traits with GWAS summary statistics
AID  - 10.1101/052068
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 052068
4099  - http://biorxiv.org/content/early/2016/05/07/052068.short
4100  - http://biorxiv.org/content/early/2016/05/07/052068.full
AB  - 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.The methods are implemented in R package aSPU, freely and publicly available on CRAN at: https://cran.r-project.org/web/packages/aSPU/.