|
Abstract:
|
The analysis of whole-genome sequencing studies is challenging due to the large number of noncoding rare variants, our limited understanding of their functional effects, and the lack of natural units for testing. Existing methods based on FWER control and marginal association tests often suffer from insufficient power owing to the expansion of the multiple testing problem, and increased risk of false positives due to the presence of linkage disequilibrium. We propose a scan statistic framework and a sequential Model-X knockoff statistic generator for whole-genome sequencing data analysis. The proposed method is able to simultaneously detects the existence and localizes association signals at genome-wide scale with guaranteed FDR control, and to significantly reduce false discoveries due to linkage disequilibrium.
|
