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Provides a step-down procedure for controlling the False Discovery Proportion (FDP) in a competition-based setup, implementing Dong et al. (2020) <doi:10.48550/arXiv.2011.11939>. Such setups include target-decoy competition (TDC) in computational mass spectrometry and the knockoff construction in linear regression.
Version: | 1.0.0 |
Imports: | pracma, stats |
Published: | 2022-03-16 |
DOI: | 10.32614/CRAN.package.stepdownfdp |
Author: | Arya Ebadi [aut, cre], Dong Luo [aut], Kristen Emery [aut], Yilun He [aut], William Stafford Noble [aut], Uri Keich [aut] |
Maintainer: | Arya Ebadi <aeba3842 at uni.sydney.edu.au> |
License: | MIT + file LICENSE |
URL: | https://github.com/uni-Arya/stepdownfdp |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | stepdownfdp results |
Reference manual: | stepdownfdp.pdf |
Package source: | stepdownfdp_1.0.0.tar.gz |
Windows binaries: | r-devel: stepdownfdp_1.0.0.zip, r-release: stepdownfdp_1.0.0.zip, r-oldrel: stepdownfdp_1.0.0.zip |
macOS binaries: | r-release (arm64): stepdownfdp_1.0.0.tgz, r-oldrel (arm64): stepdownfdp_1.0.0.tgz, r-release (x86_64): stepdownfdp_1.0.0.tgz, r-oldrel (x86_64): stepdownfdp_1.0.0.tgz |
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These binaries (installable software) and packages are in development.
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