Last updated: 2017-05-21
Code version: 5d9639e
We are comparing our method with ASH and SVA.
library(ashr)
library(edgeR)
library(limma)
library(seqgendiff)
library(sva)
library(pROC)
source("../code/gdash.R")
Artefactual effects \(\pi_0\delta_0 + \left(1 - \pi_0\right)N\left(0, \sigma^2\right)\) are added to the real GTEx data.
mat = read.csv("../data/liver.csv")
We are using \(10K\) genes, \(5\) v \(5\) experimental design, and \(100\) independent simulation trials.
ngene = 1e4
nsamp = 10
N = 100
pi0 = 0.9
sd = 1
set.seed(777)
system.time(gdash.comp <- N_simulations(N, mat, nsamp, ngene, pi0, sd))
     user    system   elapsed 
18421.805  1175.855  3889.120 



pi0 = 0.9
sd = sqrt(2)
set.seed(777)
system.time(gdash.comp <- N_simulations(N, mat, nsamp, ngene, pi0, sd))
     user    system   elapsed 
19523.364  1271.100  4140.141 



pi0 = 0.9
sd = sqrt(3)
set.seed(777)
system.time(gdash.comp <- N_simulations(N, mat, nsamp, ngene, pi0, sd))
     user    system   elapsed 
17770.699  1169.506  3854.622 



sessionInfo()
R version 3.3.3 (2017-03-06)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra 10.12.4
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_0.12.10    stringi_1.1.5  
 [9] rmarkdown_1.5   knitr_1.16      git2r_0.18.0    stringr_1.2.0  
[13] digest_0.6.12   evaluate_0.10  
This R Markdown site was created with workflowr