MixTwice: Large-Scale Hypothesis Testing by Variance Mixing

Implements large-scale hypothesis testing by variance mixing. It takes two statistics per testing unit – an estimated effect and its associated squared standard error – and fits a nonparametric, shape-constrained mixture separately on two latent parameters. It reports local false discovery rates (lfdr) and local false sign rates (lfsr). Manuscript describing algorithm of MixTwice: Zheng et al(2021) <doi:10.1093/bioinformatics/btab162>.

Version: 2.0
Depends: R (≥ 3.5.0)
Imports: alabama, ashr, fdrtool, Iso, stats
Published: 2022-03-02
Author: Zihao Zheng and Michael A.Newton
Maintainer: Zihao Zheng <zihao.zheng at wisc.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: MixTwice results

Documentation:

Reference manual: MixTwice.pdf

Downloads:

Package source: MixTwice_2.0.tar.gz
Windows binaries: r-devel: MixTwice_2.0.zip, r-release: MixTwice_2.0.zip, r-oldrel: MixTwice_2.0.zip
macOS binaries: r-release (arm64): MixTwice_2.0.tgz, r-oldrel (arm64): MixTwice_2.0.tgz, r-release (x86_64): MixTwice_2.0.tgz
Old sources: MixTwice archive

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