Multigroup equivalence analysis for high-dimensional expression data

Academic Article

Abstract

  • Hypothesis tests of equivalence are typically known for their application in bioequivalence studies and acceptance sampling. Their application to gene expression data, in particular high-dimensional gene expression data, has only recently been studied. In this paper, we examine how two multigroup equivalence tests, the F-test and the range test, perform when applied to microarray expression data. We adapted these tests to a well-known equivalence criterion, the difference ratio. Our simulation results showed that both tests can achieve moderate power while controlling the type I error at nominal level for typical expression microarray studies with the benefit of easy-to-interpret equivalence limits. For the range of parameters simulated in this paper, the F-test is more powerful than the range test. However, for comparing three groups, their powers are similar. Finally, the two multigroup tests were applied to a prostate cancer microarray dataset to identify genes whose expression follows a prespecified trajectory across five prostate cancer stages.
  • Published In

  • Cancer Informatics  Journal
  • Digital Object Identifier (doi)

    Pubmed Id

  • 21310338
  • Author List

  • Yang C; Bartolucci AA; Cui X
  • Start Page

  • 253
  • End Page

  • 263
  • Volume

  • 14