Package: swfdr
Title: Science-wise false discovery rate and proportion of true null
        hypotheses estimation
Version: 1.13.0
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
        proportion of true null hypotheses in the presence of
        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: splines, stats4, stats
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: dplyr, ggplot2, BiocStyle, knitr, qvalue, reshape2,
        rmarkdown, testthat
VignetteBuilder: knitr
biocViews: MultipleComparison, StatisticalMethod, Software
git_url: https://git.bioconductor.org/packages/swfdr
git_branch: master
git_last_commit: 98ec539
git_last_commit_date: 2019-10-29
Date/Publication: 2019-11-06
NeedsCompilation: no
Packaged: 2019-11-07 04:30:22 UTC; biocbuild
Built: R 4.0.0; ; 2019-11-07 08:42:50 UTC; windows
