StoreyLab/fFDR: Functional FDR for multiple hypothesis testing

The functional FDR (fFDR) methodology utilizes an informative variable as well as p-value for multiple hypothesis testing. It models the likelihood of a true null hypothesis as a function of the informative variable (referred to as the "functional proportion""), and models the power of a statistical test also as a function of the informative variable. When neither the functional proportion nor the statistical test depends on the informtaive variable, the fFDR methodology reduces to the traditional q-value based FDR methodology.

install.packages("remotes")
remotes::install_github("StoreyLab/fFDR")