plot_fdrnbrcurve: Plot number of significant features vs FDR

In csoneson/iCOBRA: Comparison and Visualization of Ranking and Assignment Methods

Plot number of significant features vs FDR

Description

Plot the number of features considered significant vs observed false discovery rate (FDR), for given adjusted p-value thresholds and/or as curves traced out by considering all threshold values.

Usage

plot_fdrnbrcurve(
  cobraplot,
  title = "",
  stripsize = 15,
  titlecol = "black",
  pointsize = 5,
  xaxisrange = c(0, 1),
  plottype = c("curve", "points"),
  linewidth = 1
)

Arguments

cobraplot	A COBRAPlot object.
title	A character string giving the title of the plot.
stripsize	A numeric value giving the size of the strip text, when the results are stratified by an annotation.
titlecol	A character string giving the color of the title.
pointsize	A numeric value giving the size of the plot characters.
xaxisrange	A numeric vector with two elements, giving the lower and upper boundary of the x-axis, respectively.
plottype	A character vector giving the type of plot to construct. Can be any combination of the two elements "curve" and "points".
linewidth	The line width used for plotting

Value

A ggplot object

Author(s)

Charlotte Soneson

Examples

data(cobradata_example)
cobraperf <- calculate_performance(cobradata_example,
                                   binary_truth = "status",
                                   aspects = c("fdrnbr", "fdrnbrcurve"))
cobraplot <- prepare_data_for_plot(cobraperf, colorscheme = "Dark2",
                                   incltruth = TRUE)
plot_fdrnbrcurve(cobraplot, plottype = c("curve", "points"))

csoneson/iCOBRA documentation built on Nov. 5, 2024, 7:20 p.m.