Journal
BIOMETRICS
Volume 69, Issue 2, Pages 427-435Publisher
WILEY
DOI: 10.1111/biom.12006
Keywords
Genome-wide association studies; Imputation; k-sample problem; Nonparametric test; Probabilistic data; Ranks
Funding
- NSERC [250053-2008]
- CIHR of Canada [MOP 84287]
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Motivated by genetic association studies of SNPs with genotype uncertainty, we propose a generalization of the Kruskal-Wallis test that incorporates group uncertainty when comparing k samples. The extended test statistic is based on probability-weighted rank-sums and follows an asymptotic chi-square distribution with k - 1 degrees of freedom under the null hypothesis. Simulation studies confirm the validity and robustness of the proposed test in finite samples. Application to a genome-wide association study of type 1 diabetic complications further demonstrates the utilities of this generalized Kruskal-Wallis test for studies with group uncertainty. The method has been implemented as an open-resource R program, GKW.
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