Last updated: 2017-11-07

Code version: 2c05d59

Introduction

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")

The setting: \(\pi_0 = 0.5\), \(\sigma^2 = 9\)

N = 200
nsamp = 10
ngene = 1e4
pi0 = 0.5
sd = 3
set.seed(777)
system.time(gdash.comp <- N_simulations(N, mat, nsamp, ngene, pi0, sd))
     user    system   elapsed 
12622.459  1340.169 49686.171

Session information

sessionInfo()
R version 3.4.2 (2017-09-28)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6

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     

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

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