Description Usage Arguments Details Value References Examples
Multi-trait association test based on GWAS summary statistics under common genetic effect assumption
1 | cmats(Z, Sig, rho = 0:10/10)
|
Z |
summary Z-statistics across multiple traits |
Sig |
estimated trait correlation matrix |
rho |
sequence of weights assigned to the PT. Default to 0:10/10 |
Under pleiotropy of common effects across traits, an 1-DF pleiotropy test (PT) can be constructed. The omnibus K-DF chi-square test (OT) is generally robust and powerful. We then define the adaptive test (AT) as the minium p-values of weighted sums of PT (ρ) and OT (1-ρ). An efficient algorithm is developed to exactly compute the analytical p-value of AT. We recommend using the LD score regression (Bulik-Sullivan et al.) to accurately estimate the trait correlation matrix.
vector of p-values for: AT, OT and PT
the list of all p-values
estimated optimal ρ value
Bulik-Sullivan B et al. (2015) LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nature Genetics, 47(3):291–295.
Bulik-Sullivan B et al. (2015) An atlas of genetic correlations across human diseases and traits. Nature Genetics, 47(11):1236–1241.
Massoti M*, Guo B* and Wu B. (2018) Pleiotropy informed adaptive association test of multiple traits using GWAS summary data. Biometrics, to appear (* contribute equallly).
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