IHW: Independent Hypothesis Weighting
Version 1.4.0

Independent hypothesis weighting (IHW) is a multiple testing procedure that increases power compared to the method of Benjamini and Hochberg by assigning data-driven weights to each hypothesis. The input to IHW is a two-column table of p-values and covariates. The covariate can be any continuous-valued or categorical variable that is thought to be informative on the statistical properties of each hypothesis test, while it is independent of the p-value under the null hypothesis.

Package details

AuthorNikos Ignatiadis [aut, cre], Wolfgang Huber [aut]
Bioconductor views MultipleComparison RNASeq
MaintainerNikos Ignatiadis <[email protected]>
Package repositoryView on Bioconductor
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IHW documentation built on May 31, 2017, 11:24 a.m.