R: Plot the empirical FDR as a function of the cutoff level
plot.FDR.result
R Documentation
Plot the empirical FDR as a function of the cutoff level
Description
Plots the output from EOC. The resulting graph is the empirical counterpart to those produced by TOC, i.e. the estimated FDR as a function of the cutoff-level on the t-statistic.
logical value indicating whether to add to an existing plot or start a new one
sensitivity.show
logical value indicating whether to show the classical sensitivity for testing one hypothesis as a function of the cutoff level.
legend.show
logical value indicating whether to add a legend to the plot
xlim, ylim
limits for the horizontal and vertical axis
xlab, ylab
axis labels
main
plot title
...
the usual graphical parameters, passed to plot
Author(s)
A. Ploner
See Also
EOC
Examples
# We simulate a small example with 5 percent regulated genes and
# a rather large effect size
set.seed(2003)
xdat = matrix(rnorm(50000), nrow=1000)
xdat[1:25, 1:25] = xdat[1:25, 1:25] - 2
xdat[26:50, 1:25] = xdat[26:50, 1:25] + 2
grp = rep(c("Sample A","Sample B"), c(25,25))
# Compute the EOC without plotting
ret = EOC(xdat, grp, plot=FALSE)
# Some possible arrangements
par(mfrow=c(2,2))
plot(ret)
plot(ret, legend=TRUE)
plot(ret, sensitivity=FALSE)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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> library(OCplus)
Loading required package: akima
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/OCplus/plot.FDR.result.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot.FDR.result
> ### Title: Plot the empirical FDR as a function of the cutoff level
> ### Aliases: plot.FDR.result
> ### Keywords: hplot aplot
>
> ### ** Examples
>
> # We simulate a small example with 5 percent regulated genes and
> # a rather large effect size
> set.seed(2003)
> xdat = matrix(rnorm(50000), nrow=1000)
> xdat[1:25, 1:25] = xdat[1:25, 1:25] - 2
> xdat[26:50, 1:25] = xdat[26:50, 1:25] + 2
> grp = rep(c("Sample A","Sample B"), c(25,25))
>
> # Compute the EOC without plotting
> ret = EOC(xdat, grp, plot=FALSE)
>
> # Some possible arrangements
> par(mfrow=c(2,2))
> plot(ret)
> plot(ret, legend=TRUE)
> plot(ret, sensitivity=FALSE)
>
>
>
>
>
>
> dev.off()
null device
1
>