An adaptive two-sample test for high-dimensional means

Gongjun Xu, Lifeng Lin, Peng Wei, Wei Pan

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Several two-sample tests for high-dimensional data have been proposed recently, but they are powerful only against certain alternative hypotheses. In practice, since the true alternative hypothesis is unknown, it is unclear how to choose a powerful test. We propose an adaptive test that maintains high power across a wide range of situations and study its asymptotic properties. Its finite-sample performance is compared with that of existing tests. We apply it and other tests to detect possible associations between bipolar disease and a large number of single nucleotide polymorphisms on each chromosome based on data from a genome-wide association study. Numerical studies demonstrate the superior performance and high power of the proposed test across a wide spectrum of applications.

Original languageEnglish (US)
Pages (from-to)609-624
Number of pages16
Issue number3
StatePublished - Sep 1 2016


  • Genome-wide association study
  • Single nucleotide polymorphism
  • Sum-of-powers test

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