wrGraph: staggerdCountsPlot – R documentation

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staggerdCountsPlot

Staggered Chart for Ploting Counts to Multiple Leveles of the Threshold used

Description

The basic idea of this plot is to show how counts data change while shifting a threshold-criterium. At each given threshold the counts are plotted like a staggered bar-chart (or staggered histogram) but without vertical lines to illustrated the almost continuous change from preceedig or following threshold-value. Initially this plot was designed for showing the absolute count-data used when constructing roc-curves (eg using the function summarizeForROC of package wrProteo ). The main input should furnish the panel of threshold as one column and the coresponding counts data as min 2 columns. The threshold coumns gets specified using the argument threColumn, the counts-data may either be specified using argument countsCol or be searched using grep using column-names containing the text given in argument varCountNa with may be combined with a fixed preceeding part given as argument fixedCountPat.

Usage

staggerdCountsPlot(
  roc,
  threColumn = 1,
  countsCol = NULL,
  fixedCountPat = "n.pos.",
  varCountNa = NULL,
  sortAscending = TRUE,
  vertLine = NULL,
  col = NULL,
  tit = NULL,
  logScale = FALSE,
  las.alph = 2,
  displMaxSpec = TRUE,
  silent = FALSE,
  callFrom = NULL
)

Arguments

`roc`	(numeric matrix or data.frame) main input: one column with thresholds and multiple columns of assoicated count data
`threColumn`	(integer or character) to specify the column with threshold-data, in typica proteomics benchmark studies this would be 'alph' (for the statistical test threshold)
`countsCol`	(character of integer, min length=2) choice of column(s) with count-data in 'roc' to be used for display, if not `NULL` will override alternative search of columns using 'varCountNa' and 'fixedCountPat'
`fixedCountPat`	(character) optional pattern to help identifying counts-data: if not `NULL` it will be used as fixed part in column names to get pasted to `varCountNa`. In proteomics benchmark studies this would typically be 'n.pos.'
`varCountNa`	(character) alternative way to select the columns from 'roc': searched using `grep` using column-names containing the text given in argument `varCountNa` with may be combined with a fixed preceeding part given as argument `fixedCountPat` In proteomics benchmark studies this would typically be the species-abbreciations (eg 'H','S','E')
`sortAscending`	(logical) decide if data should be sorted ascending or descending
`vertLine`	(numeric) for optional vertical line, typically used to highlight alpha 0.05
`col`	(character) custom colors, see also `par`
`tit`	(character) cutom title
`logScale`	(logical) display threshld values (x-axis) on log-scale
`las.alph`	(numeric) orientation of label of alpha-cutoff, see also `par`
`displMaxSpec`	(logical) display on right side of figure max count value of contributing group species
`silent`	(logical) suppress messages
`callFrom`	(character) allow easier tracking of message(s) produced

Details

Investigate count data prepared for plotting ROC curves : cumulative counts plot by species (along different statistical test thresholds). Note : Package wrProteo may be used to prepare input (matrix of ROC data).

Value

plot only

Examples

set.seed(2019); test1 <- cbind(a=sample.int(n=7,size=50,repl=TRUE),
  b=sample.int(n=11,size=50,repl=TRUE),c=sample.int(n=18,size=50,repl=TRUE))
test1 <- cbind(alph=seq(0,1,length.out=50),a=cumsum(test1[,1]),b=cumsum(test1[,2]),
  c=cumsum(test1[,3]))
staggerdCountsPlot(test1,countsCol=c("a","b","c"))
## example below requires the package wrProteo

wrGraph

Graphics in the Context of Analyzing High-Throughput Data

v1.2.3

GPL-3

Authors

Wolfgang Raffelsberger [aut, cre]

Initial release