plotCurves: Plot trajectories of probe profiles across arrays

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

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.

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)
    
  # 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) 

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