MixTwice-package: Large-Scale Hypothesis Testing by Variance Mixing

In MixTwice: Large-Scale Hypothesis Testing by Variance Mixing

Large-Scale Hypothesis Testing by Variance Mixing

Description

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>.

Details

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Author(s)

Zihao Zheng and Michael A.Newton

Maintainer: Zihao Zheng <[e-mail]>

References

Zheng et al. MixTwice: Large scale hypothesis testing for peptide arrays by variance mixing. Bioinformatics, 2021.

Zheng et al. Disordered Antigens and Epitope Overlap Between Anti Citrullinated Protein Antibodies and Rheumatoid Factor in Rheumatoid Arthritis. Arthritis & Rheumatology 72.2 (2020): 262-272.

Examples

data(peptide_data)
## For more detail and example, use ?peptide_data and ?mixtwice

MixTwice documentation built on March 18, 2022, 6:29 p.m.