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iCheck (version 1.2.0)

plotCurves: Plot trajectories of probe profiles across arrays

Description

Plot trajectories of probe profiles across arrays

Usage

plotCurves( dat, curveNames, fileName, plotOutPutFlag=FALSE, requireLog2 = FALSE, cex = 1, ylim = NULL, xlab = "", ylab = "intensity", lwd = 3, main = "Trajectory plot", mar = c(10, 4, 4, 2) + 0.1, las = 2, cex.axis=1, ...)

Arguments

dat
Numeric data matrix. Rows are probes; columns are arrays.
curveNames
Probe names.
fileName
file name of output figure.
plotOutPutFlag
logical. plotOutPutFlag=TRUE indicates the plots will be output to pdf format files. Otherwise, the plots will not be output to external files.
requireLog2
logical. requiredLog2=TRUE indicates probe expression levels will be log2 transformed. Otherwise, no transformation will be performed.
cex
numerical value giving the amount by which plotting text and symbols should be magnified relative to the default. see par.
ylim
Range of y axis.
xlab
Label of x axis.
ylab
Label of y axis.
lwd
The line width, a _positive_ number, defaulting to '1'. see par.
main
Main title of the plot.
mar
A numerical vector of the form 'c(bottom, left, top, right)' which gives the number of lines of margin to be specified on the four sides of the plot. The default is 'c(5, 4, 4, 2) + 0.1'. see par.
las
'las' numeric in 0,1,2,3; the style of axis labels. 0 - always parallel to the axis, 1 - always horizontal, 2 - always perpendicular to the axis, or 3 - always vertical.

see par.

cex.axis
The magnification to be used for axis annotation relative to the current setting of cex.

see par.

...
Arguments to be passed to plot.

Value

no return value.

Examples

Run this code
    # generate simulated data set from conditional normal distribution
    set.seed(1234567)
    es.sim = genSimData.BayesNormal(nCpGs = 100, 
      nCases = 20, nControls = 20,
      mu.n = -2, mu.c = 2,
      d0 = 20, s02 = 0.64, s02.c = 1.5, testPara = "var",
      outlierFlag = FALSE, 
      eps = 1.0e-3, applier = lapply) 
    print(es.sim)
    
  # plot trajectories of the first 5 genes
  plotCurves(
  dat = exprs(es.sim)[1:5,], 
  curveNames = featureNames(es.sim)[1:5], 
  plotOutPutFlag=FALSE,
  cex = 0.5,
  requireLog2 = FALSE) 

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