An Optimal Bahadur-Efficient Method in Detection of Sparse Signals with Applications to Pathway Analysis in Sequencing Association Studies

Hongying Dai, Guodong Wu, Michael Wu and Degui Zhi

PLOS ONE, 2016, vol. 11, issue 7, 1-18

Abstract: Next-generation sequencing data pose a severe curse of dimensionality, complicating traditional "single marker—single trait" analysis. We propose a two-stage combined p-value method for pathway analysis. The first stage is at the gene level, where we integrate effects within a gene using the Sequence Kernel Association Test (SKAT). The second stage is at the pathway level, where we perform a correlated Lancaster procedure to detect joint effects from multiple genes within a pathway. We show that the Lancaster procedure is optimal in Bahadur efficiency among all combined p-value methods. The Bahadur efficiency,limε→0N(2)/N(1)=ϕ12(θ), compares sample sizes among different statistical tests when signals become sparse in sequencing data, i.e. ε →0. The optimal Bahadur efficiency ensures that the Lancaster procedure asymptotically requires a minimal sample size to detect sparse signals (PN(i)

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0152667

DOI: 10.1371/journal.pone.0152667

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