Multiple testing under dependence via graphical models
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Publication:2403086
DOI10.1214/16-AOAS956zbMath1391.62231MaRDI QIDQ2403086
Chunming Zhang, David Page, Jie Liu
Publication date: 15 September 2017
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Markov random fieldgraphical modelsgenome-wide association studylocal index of significancemultiple testing under dependence
Random fields; image analysis (62M40) Applications of statistics to biology and medical sciences; meta analysis (62P10) Protein sequences, DNA sequences (92D20) Paired and multiple comparisons; multiple testing (62J15)
Related Items (6)
LAWS: A Locally Adaptive Weighting and Screening Approach to Spatial Multiple Testing ⋮ Powerful multiple testing of paired null hypotheses using a latent graph model ⋮ Covariate-adjusted multiple testing in genome-wide association studies via factorial hidden Markov models ⋮ Covariate-modulated large-scale multiple testing under dependence ⋮ False discovery variance reduction in large scale simultaneous hypothesis tests ⋮ FWER goes to zero for correlated normal
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