iCheck (version 1.2.0)

plotQCCurves: Plot trajectories of specific QC probes (e.g., biotin, cy3_hyb, housekeeping gene probes, low stringency probes, etc.) across arrays

Description

Plot trajectories of specific QC probes (e.g., biotin, cy3_hyb, housekeeping gene probes, low stringency probes, etc.) across arrays

Usage

plotQCCurves( esQC,  probes = c("biotin", "cy3_hyb", "housekeeping",  "low_stringency_hyb", "signal", "p95p05"),  labelVariable = "subjID", hybName = "Hybridization_Name", reporterGroupName = "Reporter_Group_Name", requireLog2 = TRUE,  projectName = "test",  plotOutPutFlag = FALSE,  cex = 1,  ylim = NULL,  xlab = "",  ylab = "intensity",  lwd = 3,  mar = c(10, 4, 4, 2) + 0.1, las = 2, cex.axis = 1, sortFlag = TRUE, varSort = c("Batch_Run_Date", "Chip_Barcode", "Chip_Address"),  timeFormat = c("%m/%d/%Y", NA, NA), ...)

Arguments

esQC

ExpressionSet object of QC probe profiles. fData(esQC) should contains the variable Reporter_Group_Name.

probes

A character vectors of QC probe names. By default, it includes the following probe names “biotin”, “cy3_hyb”, “housekeeping”, “low_stringency_hyb”, “signal”, “p95p05”. For “signal”, trajectories of 5th, 25th, 50th, 75th, and 95th percentiles of the expression levels of all QC probes will be ploted. For “p95p05”, the trajectory of the ratio of 95th percentile to 5th percentile of the expression levels of all QC probes will be ploted.

labelVariable

A character string. The name of a phenotype data variable use to label the arrays in the boxplots. By default, labelVariable = "subjID" which is equivalent to labelVariable = "Hybridization_Name".

hybName

character string. indicating the phenotype variable Hybridization_Name.

reporterGroupName

character string. indicating feature variable Reporter_Group_Name (QC probe's name).

requireLog2

logical. requiredLog2=TRUE indicates probe expression levels will be log2 transformed. Otherwise, no transformation will be performed.

projectName

A character string. Name of the project. The plots will be saved as pdf format files, the names of which have the format projectName_probeName_traj_plot.pdf.

plotOutPutFlag

logical. plotOutPutFlag=TRUE indicates the plots will be output to pdf format files. Otherwise, the plots will not be output to external files.

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.

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.

sortFlag

logical. Indicates if arrays need to be sorted according to Batch_Run_Date, Chip_Barcode, and Chip_Address.

varSort

A vector of phenotype variable names to be used to sort the samples of es.

timeFormat

A vector of time format for the possible time variables in varSort. The length of timeFormat should be the same as that of varSort. For non-time variable, the corresponding time format should be set to be equal to NA.

...

Arguments to be passed to plot.

Value

no return value.

Examples

    # generate simulated data set from conditional normal distribution
    set.seed(1234567)
    esQC.sim = genSimData.BayesNormal(nCpGs = 10, 
      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(esQC.sim)

    fDat = fData(esQC.sim)
    esQC.sim$Hybridization_Name = sampleNames(esQC.sim)
    fDat$Reporter_Group_Name = c( rep("biotin", 5),
      rep("housekeeping", 5))
    fData(esQC.sim)=fDat

    # plot trajectories of the QC probes
    plotQCCurves(
      esQC = esQC.sim, 
      probes = c("biotin", "housekeeping"), 
      labelVariable = "subjID",
      hybName = "Hybridization_Name",
      reporterGroupName = "Reporter_Group_Name",
      requireLog2 = FALSE, 
      plotOutPutFlag = FALSE, 
      sortFlag = FALSE)