wrProteo: plotROC – R documentation

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plotROC

Plot ROC curves

Description

plotROC plots ROC curves based on results from summarizeForROC. This function plots only, it does not return any data. It allows printing simultaneously multiple ROC curves from different studies, it is also compatible with data from 3 species mix as in proteomics benchmark. Input can be prepared using moderTest2grp followed by summarizeForROC.

Usage

plotROC(
  dat,
  ...,
  useColumn = 2:3,
  methNames = NULL,
  col = NULL,
  pch = 1,
  bg = NULL,
  tit = NULL,
  xlim = NULL,
  ylim = NULL,
  point05 = 0.05,
  pointSi = 0.85,
  nByMeth = NULL,
  speciesOrder = NULL,
  txtLoc = NULL,
  legCex = 0.72,
  las = 1,
  addSuplT = TRUE,
  silent = FALSE,
  callFrom = NULL
)

Arguments

`dat`	(matrix) from testing (eg `summarizeForROC` )
`...`	optional additional data-sets to include as seprate ROC-curves to same plot (must be of same type of format as 'dat')
`useColumn`	(integer or character, length=2) columns from `dat` to be used for pecificity and sensitivity
`methNames`	(character) names of methods (data-sets) to be displayed
`col`	(character) custom colors for lines and text (choose one color for each different data-set)
`pch`	(integer) type of symbol to be used (see also `par`)
`bg`	(character) background color in plot (see also `par`)
`tit`	(character) custom title
`xlim`	(numeric, length=2) custom x-axis limits
`ylim`	(numeric, length=2) custom y-axis limits
`point05`	(numeric) specific point to highlight in plot (typically at alpha=0.05)
`pointSi`	(numeric) size of points (as expansion factor `cex`)
`nByMeth`	(integer) value of n to display
`speciesOrder`	(integer) custom order of species in legend
`txtLoc`	(numeric, length=3) location for text (x, y and proportional factor for line-offset, default is c(0.4,0.3,0.04))
`legCex`	(numeric) cex expansion factor for legend (see also `par`)
`las`	(numeric) factor for text-orientation (see also `par`)
`addSuplT`	(logical) add text with information about precision,accuracy and FDR
`silent`	(logical) suppress messages
`callFrom`	(character) allows easier tracking of messages produced

Value

plot with ROC curves only

Examples

roc0 <- cbind(alph=c(2e-6,4e-5,4e-4,2.7e-3,1.6e-2,4.2e-2,8.3e-2,1.7e-1,2.7e-1,4.1e-1,5.3e-1,
	 6.8e-1,8.3e-1,9.7e-1), spec=c(1,1,1,1,0.957,0.915,0.915,0.809,0.702,0.489,0.362,0.234,
  0.128,0.0426), sens=c(0,0,0.145,0.942,2.54,2.68,3.33,3.99,4.71,5.87,6.67,8.04,8.77,
  9.93)/10, n.pos.a=c(0,0,0,0,2,4,4,9,14,24,36,41) )
plotROC(roc0)

wrProteo

Proteomics Data Analysis Functions

v1.4.1

GPL-3

Authors

Wolfgang Raffelsberger [aut, cre]

Initial release