Last updated: 2018-10-17

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    File Version Author Date Message
    rmd 2bc9fa8 LSun 2018-10-17 wflow_publish(“cash_paper_fig_mouseheart.rmd”)

Introduction

Analysis of a mouse heart gene expression data set with 2 vs 2 samples.

source("../code/gdash_lik.R")
Loading required package: EQL
Loading required package: ttutils
Loading required package: SQUAREM
Loading required package: REBayes
Loading required package: Matrix
Warning: package 'Matrix' was built under R version 3.4.4
Loading required package: CVXR

Attaching package: 'CVXR'
The following object is masked from 'package:stats':

    power
Loading required package: PolynomF
Loading required package: Rmosek
Loading required package: ashr
counts.mat = read.table("../data/smemo.txt", header = T, row.name = 1)
counts.mat = counts.mat[, -5]
counts = counts.mat[rowSums(counts.mat) >= 5, ]
design = model.matrix(~c(0, 0, 1, 1))
dgecounts = edgeR::calcNormFactors(edgeR::DGEList(counts = counts, group = design[, 2]))
v = limma::voom(dgecounts, design, plot = FALSE)
lim = limma::lmFit(v)
r.ebayes = limma::eBayes(lim)
p = r.ebayes$p.value[, 2]
t = r.ebayes$t[, 2]
z = -sign(t) * qnorm(p/2)
fit.locfdr <- locfdr::locfdr(z)

fit.qvalue <- qvalue::qvalue(p)
x = lim$coefficients[, 2]
s = x / z
fit.cash <- gdash(x, s)
fit.ash <- ashr::ash(x, s, mixcompdist = "normal", method = "fdr")
x.plot <- seq(-10, 10, length = 1000)
gd.ord <- 10
hermite = Hermite(gd.ord)
gd0.std = dnorm(x.plot)
matrix_lik_plot = cbind(gd0.std)
for (i in 1 : gd.ord) {
  gd.std = (-1)^i * hermite[[i]](x.plot) * gd0.std / sqrt(factorial(i))
  matrix_lik_plot = cbind(matrix_lik_plot, gd.std)
}
y.plot = matrix_lik_plot %*% fit.cash$w * fit.cash$fitted_g$pi[1]

method.col <- scales::hue_pal()(5)
setEPS()
postscript("../output/paper/mouseheart.eps", height = 5, width = 7)

hist(z, prob = TRUE, main = "", xlab = expression(paste(z, "-scores")), cex.lab = 1.25, breaks = 20)
lines(x.plot, y.plot, col = method.col[5], lwd = 2)
lines(x.plot, dnorm(x.plot), col = "orange", lty = 2, lwd = 2)
lines(x.plot, dnorm(x.plot, fit.locfdr$fp0[3, 1], fit.locfdr$fp0[3, 2]) * fit.locfdr$fp0[3, 3], col = method.col[3], lty = 2, lwd = 2)

text(-2.7, 0.2, "N(0,1)", col = "orange")
arrows(-2.1, 0.2, -1.2, 0.195, length = 0.1, angle = 20, col = "orange")

text(-4.4, 0.13, bquote(atop(" locfdr empirical null", .(round(fit.locfdr$fp0[3, 3], 2)) %*% N(.(round(fit.locfdr$fp0[3, 1], 2)), .(round(fit.locfdr$fp0[3, 2], 2))^2))), col = method.col[3])
arrows(-2.9, 0.13, -2, 0.125, length = 0.1, angle = 20, col = method.col[3])

text(4.2, 0.08, "cashr", col = method.col[5])
arrows(3.7, 0.08, 2.8, 0.075, length = 0.1, angle = 20, col = method.col[5])

dev.off()
quartz_off_screen 
                2

Session information

sessionInfo()
R version 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6

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     

other attached packages:
[1] ashr_2.2-7        Rmosek_8.0.69     PolynomF_1.0-2    CVXR_0.95        
[5] REBayes_1.3       Matrix_1.2-14     SQUAREM_2017.10-1 EQL_1.0-0        
[9] ttutils_1.0-1    

loaded via a namespace (and not attached):
 [1] qvalue_2.10.0     locfit_1.5-9.1    reshape2_1.4.3   
 [4] splines_3.4.3     lattice_0.20-35   colorspace_1.3-2 
 [7] htmltools_0.3.6   yaml_2.1.19       gmp_0.5-13.1     
[10] rlang_0.2.0       R.oo_1.22.0       pillar_1.2.2     
[13] Rmpfr_0.7-0       R.utils_2.6.0     bit64_0.9-7      
[16] scs_1.1-1         foreach_1.4.4     plyr_1.8.4       
[19] stringr_1.3.1     munsell_0.4.3     gtable_0.2.0     
[22] workflowr_1.1.1   R.methodsS3_1.7.1 codetools_0.2-15 
[25] evaluate_0.10.1   knitr_1.20        doParallel_1.0.11
[28] pscl_1.5.2        parallel_3.4.3    Rcpp_0.12.16     
[31] edgeR_3.20.9      backports_1.1.2   scales_0.5.0     
[34] limma_3.34.9      locfdr_1.1-8      truncnorm_1.0-8  
[37] bit_1.1-13        ggplot2_2.2.1     digest_0.6.15    
[40] stringi_1.2.2     grid_3.4.3        rprojroot_1.3-2  
[43] ECOSolveR_0.4     tools_3.4.3       magrittr_1.5     
[46] lazyeval_0.2.1    tibble_1.4.2      whisker_0.3-2    
[49] MASS_7.3-50       assertthat_0.2.0  rmarkdown_1.9    
[52] iterators_1.0.9   R6_2.2.2          git2r_0.21.0     
[55] compiler_3.4.3

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