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This package allows users to estimate the sciencewise 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 


Author  Jeffrey T. Leek, Leah Jager, Simina M. Boca, Tomasz Konopka 
Bioconductor views  MultipleComparison Software StatisticalMethod 
Maintainer  Simina M. Boca <smb310@georgetown.edu>, Jeffrey T. Leek <jtleek@gmail.com> 
License  GPL (>= 3) 
Version  1.16.0 
URL  https://github.com/leekgroup/swfdr 
Package repository  View on Bioconductor 
Installation 
Install the latest version of this package by entering the following in R:

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