swfdr: Science-wise false discovery rate and proportion of true null hypotheses estimation

This package allows users to estimate the science-wise false discovery rate from Jager and Leek, "Empirical estimates suggest most published medical research is true," 2013, Biostatistics, using an EM approach due to the presence of rounding and censoring. It also allows users to estimate the false discovery rate conditional on covariates, using a regression framework, as per Boca and Leek, "A direct approach to estimating false discovery rates conditional on covariates," 2018, PeerJ.

Package details

AuthorJeffrey T. Leek, Leah Jager, Simina M. Boca, Tomasz Konopka
Bioconductor views MultipleComparison Software StatisticalMethod
MaintainerSimina M. Boca <smb310@georgetown.edu>, Jeffrey T. Leek <jtleek@gmail.com>
LicenseGPL (>= 3)
URL https://github.com/leekgroup/swfdr
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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swfdr documentation built on Nov. 8, 2020, 8:29 p.m.