期刊
CANCER INFORMATICS
卷 14, 期 -, 页码 253-263出版社
LIBERTAS ACAD
DOI: 10.4137/CIN.S17304
关键词
equivalence; multiple group; high dimension; F-test; range test; prostate cancer
资金
- NHLBI NIH HHS [T32 HL079888] Funding Source: Medline
- NIAMS NIH HHS [P60 AR064172, P60 AR048095] Funding Source: Medline
- NIDDK NIH HHS [P30 DK079626] Funding Source: Medline
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.
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