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