Hierarchical correction of p-values via an ultrametric tree running Ornstein-Uhlenbeck process - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Article Dans Une Revue Computational Statistics Année : 2022

Hierarchical correction of p-values via an ultrametric tree running Ornstein-Uhlenbeck process

Résumé

Abstract 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 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 .
Fichier principal
Vignette du fichier
s00180-021-01148-6.pdf (1.64 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-04072108 , version 1 (17-04-2023)

Licence

Paternité

Identifiants

Citer

Antoine Bichat, Christophe Ambroise, Mahendra Mariadassou. Hierarchical correction of p-values via an ultrametric tree running Ornstein-Uhlenbeck process. Computational Statistics, 2022, 37 (3), pp.995-1013. ⟨10.1007/s00180-021-01148-6⟩. ⟨hal-04072108⟩
22 Consultations
9 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More