Package: swfdr
Title: Estimation of the science-wise false discovery rate and the
        false discovery rate conditional on covariates
Version: 1.32.0
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
git_url: https://git.bioconductor.org/packages/swfdr
git_branch: RELEASE_3_20
git_last_commit: 14086a6
git_last_commit_date: 2024-10-29
Repository: Bioconductor 3.20
Date/Publication: 2024-11-23
NeedsCompilation: no
Packaged: 2024-11-23 13:11:43 UTC; biocbuild
Built: R 4.4.2; ; 2024-11-24 01:13:43 UTC; unix
