swfdr
Estimation of the science-wise false discovery rate and the false discovery rate conditional on covariates
Bioconductor version: 3.23 · Package version: 1.38.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("swfdr") Details
| Maintainer | Simina M. Boca <smb310@georgetown.edu>, Jeffrey T. Leek <jtleek@gmail.com> |
| Author | Jeffrey T. Leek, Leah Jager, Simina M. Boca, Tomasz Konopka |
| License | GPL (>= 3) |
| URL | https://github.com/leekgroup/swfdr |
| Bug Reports | https://github.com/leekgroup/swfdr/issues |
| Downloads rank | 466 |
| Source branch | RELEASE_3_23 |
| biocViews | MultipleComparison, Software, StatisticalMethod |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | swfdr_1.38.0.tar.gz |
| Windows binary (x86_64) | swfdr_1.38.0.zip |
| macOS binary (arm64) | swfdr_1.38.0.tgz |
| macOS binary (x86_64) | swfdr_1.38.0.tgz |