iCheck (version 1.2.0)

pca2DPlot: Scatter plot of first 2 principal components

Description

Scatter plot of first 2 principal components.

Usage

pca2DPlot(pcaObj,  plot.dim = c(1,2), labelVariable = "subjID",  hybName = "Hybridization_Name", outFileName = "test_pca_raw.pdf",  title = "Scatter plot of pcas",  plotOutPutFlag = FALSE,  mar = c(5, 4, 4, 2) + 0.1,  lwd = 1.5,  equalRange = TRUE,  xlab = NULL,  ylab = NULL,  xlim = NULL,  ylim = NULL,  cex.legend = 1.5,  cex = 1.5,  cex.lab = 1.5,  cex.axis = 1.5,  legendPosition = "topright",  ...)

Arguments

pcaObj

An object returned by the function pca of the R package pcaMethods.

plot.dim

A vector of 2 positive-integer-value integer specifying which 2 pcas will be plot.

labelVariable

The name of a column of the phenotype data matrix. The elements of the column will replace the column names of the expression data matrix.

hybName

character string. indicating the phenotype variable Hybridization_Name.

outFileName

Name of the figure file to be created.

title

Title of the scatter plot.

plotOutPutFlag

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

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.

lwd

The line width, a _positive_ number, defaulting to '1'. see par.

equalRange

logical. Indicating if the x-axis and y-axis have the same range.

xlab

Label of x axis.

ylab

Label of y axis.

xlim

Range of x axis.

ylim

Range of y axis.

cex.legend

Font size for legend.

cex

numerical value giving the amount by which plotting text and symbols should be magnified relative to the default. see par.

cex.lab

The magnification to be used for x and y labels relative to the current setting of cex.

cex.axis

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

see par.

legendPosition

Position of legend. Possible values are “bottomright”, “bottom”, “bottomleft”, “left”, “topleft”, “top”, “topright”, “right” and “center”.

...

Arguments to be passed to plot.

Value

A matrix of PCA scores. Each column corresponds to a principal component.

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)

    pca.obj = getPCAFunc(es = es.sim, 
                     labelVariable = "subjID", 
                     hybName = "memSubj",
                     requireLog2 = FALSE,
                     corFlag = FALSE
)

pca2DPlot(pcaObj = pca.obj, 
          plot.dim = c(1,2),
          labelVariable = "subjID", 
          hybName = "memSubj",
          plotOutPutFlag = FALSE, 
          cex.legend = 0.5, 
          legendPosition = "topright")