Hierarchical correction of p-values via an ultrametric tree running Ornstein-Uhlenbeck process
Keyword(s):
AbstractStatistical testing is classically used as an exploratory tool to search for association between a phenotype and many possible explanatory variables. This approach often leads to multiple testing under dependence. We assume a hierarchical structure between tests via an Ornstein-Uhlenbeck process on a tree. The process correlation structure is used for smoothing the p-values. We design a penalized estimation of the mean of the Ornstein-Uhlenbeck process for p-value computation. The performances of the algorithm are assessed via simulations. Its ability to discover new associations is demonstrated on a metagenomic dataset. The corresponding R package is available from https://github.com/abichat/zazou.
2017 ◽
Vol 36
(6-9)
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pp. 1039-1056
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2017 ◽
Vol 13
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pp. 0-0
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2012 ◽
Vol 28
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pp. 1529-1547
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1975 ◽
Vol 12
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pp. 600-604
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2020 ◽
Vol 31
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pp. 2050176
2020 ◽
Vol 23
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pp. 450-483
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