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

DOI10.1016/J.SPL.2013.03.019zbMath1278.62175OpenAlexW2087837270MaRDI QIDQ383945

Moonsu Kang, Pranab Kumar Sen

Publication date: 6 December 2013

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2013.03.019

zbMATH Keywords

HDLSSbivariate extremesFDRFWERmicroarray data model

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40) Genetics and epigenetics (92D10)

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Optimal False Discovery Rate Control with Kernel Density Estimation in a Microarray Experiment ⋮ Generalized Mann-Whitney Type Tests for Microarray Experiments

Cites Work

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• Bivariate extreme statistics. I
• Kendall's tau-type rank statistics in genome data.
• On methods controlling the false discovery rate
• Poisson approximation for dependent trials
• Some probability inequalities for ordered MTP\(_2\) random variables: a proof of the Simes conjecture
• An improved Bonferroni procedure for multiple tests of significance
• High-Dimension, Low–Sample Size Perspectives in Constrained Statistical Inference

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