leekgroup/swfdr: Science-wise false discovery rate and proportion of true null hypotheses estimation
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.
Getting started
Browse package contents
Package details |
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| Author | Jeffrey T. Leek, Leah Jager, Simina M. Boca, Tomasz Konopka |
| Bioconductor views | MultipleComparison Software StatisticalMethod |
| Maintainer | Simina M. Boca <smb310@georgetown.edu>, Jeffrey T. Leek <jtleek@gmail.com> |
| License | GPL (>= 3) |
| Version | 1.18.0 |
| URL | https://github.com/leekgroup/swfdr |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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