Last updated: 2017-07-21
It’s a classic microarray data set used many times by Efron to illustrate his “empirical null” idea. The data set is downloaded online
Pipeline can generate null \(z\) scores when it’s null?
brca.ratio <- read.table("../data/hedenfalk.txt", header = TRUE)
brca.logratio <- as.matrix(log2(brca.ratio[, c(1 : 6, 17, 7 : 10, 18 : 21)]))




















source("../code/gdash_lik.R")
fit <- gdash(betahat, sebetahat)
cat(fit$w)
1 0.0363335 0.7005092 0.03116099 0.3066148 -0.02737636 2.826299e-08 -0.05660896 -6.044775e-09 -0.012571 5.774521e-10
sum(fit$qvalue <= 0.1)
[1] 0

sessionInfo()
R version 3.3.3 (2017-03-06)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra 10.12.5
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     
loaded via a namespace (and not attached):
 [1] backports_1.0.5 magrittr_1.5    rprojroot_1.2   tools_3.3.3    
 [5] htmltools_0.3.6 yaml_2.1.14     Rcpp_0.12.11    stringi_1.1.2  
 [9] rmarkdown_1.6   knitr_1.16      stringr_1.2.0   digest_0.6.12  
[13] evaluate_0.10  
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