quantilePlot: Plot trajectories of quantiles across arrays

In iCheck: QC Pipeline and Data Analysis Tools for High-Dimensional Illumina mRNA Expression Data

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.

Value

The quantile matrix with row quantiles and column array.

Author(s)

Weiliang Qiu <[e-mail]>, Brandon Guo <[e-mail]>, Christopher Anderson <[e-mail]>, Barbara Klanderman <[e-mail]>, Vincent Carey <[e-mail]>, Benjamin Raby <[e-mail]>

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()
  

iCheck documentation built on Nov. 8, 2020, 11:09 p.m.