Bickel, David R. Error-rate and decision-theoretic methods of multiple testing: which genes have high objective probabilities of differential expression? (English) Zbl 1072.62106 Stat. Appl. Genet. Mol. Biol. 3, No. 1, Article 8 (2004). Summary: Given a multiple testing situation, the null hypotheses that appears to have sufficiently low probabilities of truth may be rejected using a simple, nonparametric method based on decision theory. This applies not only to posterior levels of belief, but also to conditional probabilities in the sense of relative frequencies, as seen from their equality to local false discovery rates (dFDRs). This approach neither requires the estimation of probability densities, nor of their ratios. Decision theory can also inform the selection of false discovery rate weights. An application to gene expression microarrays is presented with a discussion of the applicability of the assumption of “clumpy dependence”. Cited in 2 Documents MSC: 62P10 Applications of statistics to biology and medical sciences; meta analysis 62G10 Nonparametric hypothesis testing 62C99 Statistical decision theory 92D10 Genetics and epigenetics 62J15 Paired and multiple comparisons; multiple testing PDFBibTeX XMLCite \textit{D. R. Bickel}, Stat. Appl. Genet. Mol. Biol. 3, No. 1, Article 8 (2004; Zbl 1072.62106) Full Text: DOI arXiv Link