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fcfdr: Flexible cFDR

Provides functions to implement the Flexible cFDR (Hutchinson et al. (2021) <doi:10.1371/journal.pgen.1009853>) and Binary cFDR (Hutchinson et al. (2021) <doi:10.1101/2021.10.21.465274>) methodologies to leverage auxiliary data from arbitrary distributions, for example functional genomic data, with GWAS p-values to generate re-weighted p-values.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: locfdr, MASS, ggplot2, cowplot, fields, dplyr, spatstat.geom, polyCub, hexbin, bigsplines, data.table, grDevices, Hmisc
Suggests: stats, knitr, rmarkdown, digest, testthat (≥ 3.0.0)
Published: 2022-02-07
DOI: 10.32614/CRAN.package.fcfdr
Author: Anna Hutchinson ORCID iD [aut, cre], Chris Wallace [aut], Thomas Willis [ctb, aut], James Liley [ctb]
Maintainer: Anna Hutchinson <annahutchinson1995 at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: fcfdr results

Documentation:

Reference manual: fcfdr.pdf
Vignettes: Extra Information
Introductory vignette
LDAK vignette
T1D Application

Downloads:

Package source: fcfdr_1.0.0.tar.gz
Windows binaries: r-devel: fcfdr_1.0.0.zip, r-release: fcfdr_1.0.0.zip, r-oldrel: fcfdr_1.0.0.zip
macOS binaries: r-release (arm64): fcfdr_1.0.0.tgz, r-oldrel (arm64): fcfdr_1.0.0.tgz, r-release (x86_64): fcfdr_1.0.0.tgz, r-oldrel (x86_64): fcfdr_1.0.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.