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sffdr: Surrogate Functional False Discovery Rates for Genome-Wide Association Studies

Pleiotropy-informed significance analysis of genome-wide association studies (GWAS) with surrogate functional false discovery rates (sfFDR). The sfFDR framework adapts the fFDR to leverage informative data from multiple sets of GWAS summary statistics to increase power in study while accommodating for linkage disequilibrium. sfFDR provides estimates of key FDR quantities in a significance analysis such as the functional local FDR and q-value, and uses these estimates to derive a functional p-value for type I error rate control and a functional local Bayes' factor for post-GWAS analyses (e.g., fine mapping and colocalization). The sfFDR framework is described in Bass and Wallace (2024) <doi:10.1101/2024.09.24.24314276>.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: locfit, splines, dplyr, ggplot2 (≥ 3.5.1), patchwork (≥ 1.3.0), gam, qvalue, tibble, tidyr, Rcpp
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2024-12-02
DOI: 10.32614/CRAN.package.sffdr
Author: Andrew Bass [aut, cre], Chris Wallace [aut]
Maintainer: Andrew Bass <ab3105 at cam.ac.uk>
License: LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL]
URL: https://github.com/ajbass/sffdr
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: sffdr results

Documentation:

Reference manual: sffdr.pdf
Vignettes: sffdr: Surrogate Functional False Discovery Rates (source, R code)

Downloads:

Package source: sffdr_1.0.0.tar.gz
Windows binaries: r-devel: sffdr_1.0.0.zip, r-release: sffdr_1.0.0.zip, r-oldrel: sffdr_1.0.0.zip
macOS binaries: r-release (arm64): sffdr_1.0.0.tgz, r-oldrel (arm64): sffdr_1.0.0.tgz, r-release (x86_64): sffdr_1.0.0.tgz, r-oldrel (x86_64): sffdr_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.