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 |
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