Bivariate high-level exceedance and the Chen–Stein theorem in genomics multiple hypothesis testing perspectives

Pranab K. Sen and Moonsu Kang

Statistics & Probability Letters, 2013, vol. 83, issue 7, 1725-1730

Abstract: In genomic studies, generally the genes are neither independent nor marginally identically distributed, though in microarray studies and DNA/RNA SNP models, often they are assumed to be independent and identically distributed. A version of the Chen–Stein theorem on Poisson approximation for dependent binary variables has been adopted for a mathematical justification of this approach in a general genomic setup.

Keywords: Bivariate extreme; FDR; FWER; HDLSS; Microarray data model (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1016/j.spl.2013.03.019

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