Hierarchical correction of p-values via a tree running Ornstein-Uhlenbeck process
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Statistical 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 dependence testing under dependence. We assume a hierarchical structure between tests via an Ornstein-Uhlenbeckprocess on a tree. The process correlation structure is used for smoothing the p-values. We design a penalized estimation of the mean of the OU 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.
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