iCheck (version 1.2.0)

quantilePlot: Plot trajectories of quantiles across arrays

Description

Plot trajectories of quantiles across arrays.

Usage

quantilePlot( dat,  fileName,  probs = c(0, 0.05, 0.25, 0.5, 0.75, 0.95, 1),  plotOutPutFlag = FALSE,  requireLog2 = FALSE,  sortFlag = TRUE, cex = 1,  ylim = NULL,  xlab = "",  ylab = "intensity",  lwd = 3,  main = "Trajectory plot of quantiles",  mar = c(15, 4, 4, 2) + 0.1,  las = 2,  cex.axis = 1,  ...)

Arguments

dat

Expression data. Rows are gene probes; columns are arrays.

fileName

File name of output figure.

probs

quantiles (any real values between the interval $[0, 1]$).

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.

sortFlag

logical. sortFlag=TRUE indicates arrays will be sorted by the ascending order of MAD (median absolute deviation)

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

Charater string. 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

The quantile matrix with row quantiles and column array.

Examples

    # 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)


   png(file="qplot.png")
quantilePlot(
  dat = exprs(es.sim), 
  probs = c(0, 0.05, 0.25, 0.5, 0.75, 0.95, 1), 
  plotOutPutFlag = FALSE, 
  requireLog2 = FALSE, 
  sortFlag = TRUE)
dev.off()