Package: swfdr
Title: Estimation of the science-wise false discovery rate and the
        false discovery rate conditional on covariates
Version: 1.39.0
Author: Jeffrey T. Leek, Leah Jager, Simina M. Boca, Tomasz Konopka
Maintainer: Simina M. Boca <smb310@georgetown.edu>, Jeffrey T. Leek
 <jtleek@gmail.com>
Description: 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.
Depends: R (>= 3.4)
Imports: methods, splines, stats4, stats
License: GPL (>= 3)
URL: https://github.com/leekgroup/swfdr
BugReports: https://github.com/leekgroup/swfdr/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: dplyr, ggplot2, BiocStyle, knitr, qvalue, reshape2,
        rmarkdown, testthat
VignetteBuilder: knitr
biocViews: MultipleComparison, StatisticalMethod, Software
Repository: https://bioc.r-universe.dev
Date/Publication: 2026-04-28 12:45:07 UTC
RemoteUrl: https://github.com/bioc/swfdr
RemoteRef: HEAD
RemoteSha: 658066d6abc1a261219b9c9d37ea33453de08150
NeedsCompilation: no
Packaged: 2026-07-16 05:17:52 UTC; root