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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