Package: sffdr
Type: Package
Title: Surrogate Functional False Discovery Rates for Genome-Wide
        Association Studies
Version: 1.0.0
Authors@R: c(person("Andrew", "Bass", email ="ab3105@cam.ac.uk", role = c("aut", "cre")),
             person("Chris", "Wallace", email ="chris.wallace@cam.ac.uk", role = c("aut")))
Maintainer: Andrew Bass <ab3105@cam.ac.uk>
Description: 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>.
URL: https://github.com/ajbass/sffdr
License: LGPL
Encoding: UTF-8
VignetteBuilder: knitr
LazyData: true
Depends: R (>= 3.5.0)
Imports: locfit, splines, dplyr, ggplot2 (>= 3.5.1), patchwork (>=
        1.3.0), gam, qvalue, tibble, tidyr, Rcpp
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
LinkingTo: Rcpp
RoxygenNote: 7.3.1
NeedsCompilation: yes
Packaged: 2024-11-29 14:22:57 UTC; andrewbass
Author: Andrew Bass [aut, cre],
  Chris Wallace [aut]
Repository: CRAN
Date/Publication: 2024-12-02 12:30:08 UTC
Built: R 4.3.3; aarch64-apple-darwin20; 2024-12-02 13:02:24 UTC; unix
Archs: sffdr.so.dSYM
