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The user can directly compute and display false discovery rates from inputted p-values or z-scores under a variety of assumptions. p.fdr() computes FDRs, adjusted p-values and decision reject vectors from inputted p-values or z-values. get.pi0() estimates the proportion of data that are truly null. plot.p.fdr() plots the FDRs, adjusted p-values, and the raw p-values points against their rejection threshold lines.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.4.0) |
| Imports: | stats, utils, graphics, Rdpack |
| Published: | 2022-04-01 |
| Author: | Megan Murray [aut, cre], Jeffrey Blume [aut] |
| Maintainer: | Megan Murray <megan.c.hollister at vanderbilt.edu> |
| License: | MIT + file LICENSE |
| URL: | <doi:10.12688/f1000research.52999.2> |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | FDRestimation results |
| Reference manual: | FDRestimation.pdf |
| Package source: | FDRestimation_1.0.1.tar.gz |
| Windows binaries: | r-devel: FDRestimation_1.0.1.zip, r-release: FDRestimation_1.0.1.zip, r-oldrel: FDRestimation_1.0.1.zip |
| macOS binaries: | r-release (arm64): FDRestimation_1.0.1.tgz, r-oldrel (arm64): FDRestimation_1.0.1.tgz, r-release (x86_64): FDRestimation_1.0.1.tgz, r-oldrel (x86_64): FDRestimation_1.0.1.tgz |
| Old sources: | FDRestimation archive |
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