CASH Simulation, Part 5: pFDP Variability

Introduction

We are using the data obtained from the large-scale simulation with real data to show the variability of the positive false discovery proportions obtained by different methods at nominal \(q\) value $ = 0.05$. The true effect distribution is \(0.6\delta_0 + 0.3N(0, 1) + 0.1N(0, 2^2)\).

z.mat <- readRDS("../output/z_null_liver_777.rds")
se.mat <- readRDS("../output/sebetahat_null_liver_777.rds")
beta.list <- readRDS("../output/beta.list.rds")
qvalue.list <- readRDS("../output/qvalue.list.rds")
qvalue.BH <- qvalue.list$qvalue.BH
qvalue.qvalue <- qvalue.list$qvalue.qvalue
qvalue.locfdr <- qvalue.list$qvalue.locfdr
qvalue.ash <- qvalue.list$qvalue.ash
qvalue.gdash <- qvalue.list$qvalue.gdash

Session information

sessionInfo()

R version 3.4.2 (2017-09-28)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.1

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] vioplot_0.2 sm_2.2-5.4 

loaded via a namespace (and not attached):
 [1] compiler_3.4.2  backports_1.1.1 magrittr_1.5    rprojroot_1.2  
 [5] tools_3.4.2     htmltools_0.3.6 yaml_2.1.14     Rcpp_0.12.13   
 [9] stringi_1.1.5   rmarkdown_1.6   knitr_1.17      git2r_0.19.0   
[13] stringr_1.2.0   digest_0.6.12   evaluate_0.10.1