Last updated: 2018-05-12

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    rmd fd54c84 LSun 2017-05-12 plot_diagnostic

Introduction

This file documents some simulations done for a May 12, 2017, NHS presentation on the diagnostic plots for ASH implemented by ashr::plot_diagnostic().

library(ashr)
library(qvalue)

The concept of a Q-Q plot

set.seed(777)
x = rnorm(100)
qqnorm(x)
qqline(x)

y = runif(100)
qqnorm(y)
qqline(y)

Diagnostic plots for ASH applied to different data sets

beta = runif(10000)
betahat = beta + rnorm(10000)
fit = ash(betahat, 1, mixcompdist = "normal", method = "fdr")
plot_diagnostic(fit)

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par(mfrow = c(2, 2))
fit = ash(rnorm(10000), 1, mixcompdist = "normal", method = "fdr")
plot_diagnostic(fit, breaks = 100)
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beta = sample(c(rnorm(5000, 1.5, 1), rnorm(5000, -1.5, 1)))
betahat = beta + rnorm(10000)
fit = ash(betahat, 1, mixcompdist = "normal", method = "fdr")
plot_diagnostic(fit, breaks = 100)
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The peculiarities of the correlated null

z = readRDS("../output/z_null_liver_777_select.RDS")
z = z$typical[[5]]

hist(z, breaks = 100, prob = TRUE, xlab = "Correlated N(0, 1) Z Scores", ylim = c(0, dnorm(0)), main = "Histogram of Correlated Z Scores")
lines(seq(-6, 6, 0.01), dnorm(seq(-6, 6, 0.01)), col = "red")

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hist(z, breaks = 100, prob = TRUE, xlab = "Correlated N(0, 1) Z Scores", ylim = c(0, 0.1), main = "Histogram of Correlated Z Scores: Left Tail", xlim = c(-5, -2.5))
lines(seq(-6, 6, 0.01), dnorm(seq(-6, 6, 0.01)), col = "red")

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pval = (1 - pnorm(abs(z))) * 2
q = qvalue(pval)
hist(pval, breaks = 100, main = "Histogram of Correlated Z Scores' p-values", xlab = "p-values", prob = TRUE)
abline(h = q$pi0, col = "red", lty = 2)
legend("topright", lty = 2, col = "red", expression(paste(hat(pi)[0], " by qvalue")))

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0f36d99 LSun 2017-12-21
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Diagnostic plots for ASH applied to the correlated null.

library(ashr)
fit = ashr::ash(z, 1, mixcompdist = "normal", method = "fdr")
par(mfrow = c(2, 2))
plot_diagnostic(fit, breaks = 100)
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ff94dae LSun 2017-05-14
5607fdb LSun 2017-05-12

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 10.13.4

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] qvalue_2.10.0 ashr_2.2-2   

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.16      pillar_1.0.1      compiler_3.4.3   
 [4] git2r_0.21.0      plyr_1.8.4        workflowr_1.0.1  
 [7] R.methodsS3_1.7.1 R.utils_2.6.0     iterators_1.0.9  
[10] tools_3.4.3       digest_0.6.15     evaluate_0.10.1  
[13] tibble_1.4.1      gtable_0.2.0      lattice_0.20-35  
[16] rlang_0.1.6       Matrix_1.2-12     foreach_1.4.4    
[19] yaml_2.1.18       parallel_3.4.3    stringr_1.3.0    
[22] knitr_1.20        REBayes_1.2       rprojroot_1.3-2  
[25] grid_3.4.3        rmarkdown_1.9     reshape2_1.4.3   
[28] ggplot2_2.2.1     magrittr_1.5      whisker_0.3-2    
[31] splines_3.4.3     backports_1.1.2   scales_0.5.0     
[34] codetools_0.2-15  htmltools_0.3.6   MASS_7.3-47      
[37] assertthat_0.2.0  colorspace_1.3-2  stringi_1.1.6    
[40] Rmosek_8.0.69     lazyeval_0.2.1    doParallel_1.0.11
[43] pscl_1.5.2        munsell_0.4.3     truncnorm_1.0-7  
[46] SQUAREM_2017.10-1 R.oo_1.21.0      



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