pairsplot: Draw multiple bi-plots.
In PCAtools: PCAtools: Everything Principal Components Analysis

Description Usage Arguments Details Value Author(s) Examples

Draw multiple bi-plots.

pairsplot(
  pcaobj,
  components = getComponents(pcaobj, seq_len(5)),
  triangle = TRUE,
  trianglelabSize = 18,
  plotaxes = TRUE,
  margingaps = unit(c(0.1, 0.1, 0.1, 0.1), "cm"),
  ncol = NULL,
  nrow = NULL,
  x = NULL,
  y = NULL,
  colby = NULL,
  colkey = NULL,
  singlecol = NULL,
  shape = NULL,
  shapekey = NULL,
  pointSize = 1,
  legendPosition = "none",
  legendLabSize = 6,
  legendIconSize = 1.5,
  xlim = NULL,
  ylim = NULL,
  lab = NULL,
  labSize = 1.5,
  labhjust = 1.5,
  labvjust = 0,
  selectLab = NULL,
  drawConnectors = FALSE,
  widthConnectors = 0.5,
  colConnectors = "grey50",
  xlab = NULL,
  xlabAngle = 0,
  xlabhjust = 0.5,
  xlabvjust = 0.5,
  ylab = NULL,
  ylabAngle = 0,
  ylabhjust = 0.5,
  ylabvjust = 0.5,
  axisLabSize = 10,
  title = NULL,
  titleLabSize = 32,
  hline = NULL,
  hlineType = "longdash",
  hlineCol = "black",
  hlineWidth = 0.4,
  vline = NULL,
  vlineType = "longdash",
  vlineCol = "black",
  vlineWidth = 0.4,
  gridlines.major = TRUE,
  gridlines.minor = TRUE,
  borderWidth = 0.8,
  borderColour = "black",
  returnPlot = TRUE
)

`pcaobj`	Object of class 'pca' created by pca().
`components`	The principal components to be included in the plot. These will be compared in a pairwise fashion via multiple calls to biplot().
`triangle`	Logical, indicating whether or not to draw the plots in the upper panel in a triangular arrangement? Principal component names will be labeled along the diagonal.
`trianglelabSize`	Size of p rincipal component label (when triangle = TRUE).
`plotaxes`	Logical, indicating whether or not to draw the axis tick, labels, and titles.
`margingaps`	The margins between plots in the plot space. Takes the form of a 'unit()' variable.
`ncol`	If triangle = FALSE, the number of columns in the final merged plot.
`nrow`	If triangle = FALSE, the number of rows in the final merged plot.
`x`	A principal component to plot on x-axis. All principal component names are stored in pcaobj$label.
`y`	A principal component to plot on y-axis. All principal component names are stored in pcaobj$label.
`colby`	If NULL, all points will be coloured differently. If not NULL, value is assumed to be a column name in pcaobj$metadata relating to some grouping/categorical variable.
`colkey`	Vector of name-value pairs relating to value passed to 'col', e.g., c(A='forestgreen', B='gold').
`singlecol`	If specified, all points will be shaded by this colour. Overrides 'col'.
`shape`	If NULL, all points will be have the same shape. If not NULL, value is assumed to be a column name in pcaobj$metadata relating to some grouping/categorical variable.
`shapekey`	Vector of name-value pairs relating to value passed to 'shape', e.g., c(A=10, B=21).
`pointSize`	Size of plotted points.
`legendPosition`	Position of legend ('top', 'bottom', 'left', 'right', 'none').
`legendLabSize`	Size of plot legend text.
`legendIconSize`	Size of plot legend icons / symbols.
`xlim`	Limits of the x-axis.
`ylim`	Limits of the y-axis.
`lab`	A vector containing labels to add to the plot.
`labSize`	Size of labels.
`labhjust`	Horizontal adjustment of label.
`labvjust`	Vertical adjustment of label.
`selectLab`	A vector containing a subset of lab to plot.
`drawConnectors`	Logical, indicating whether or not to connect plot labels to their corresponding points by line connectors.
`widthConnectors`	Line width of connectors.
`colConnectors`	Line colour of connectors.
`xlab`	Label for x-axis.
`xlabAngle`	Rotation angle of x-axis labels.
`xlabhjust`	Horizontal adjustment of x-axis labels.
`xlabvjust`	Vertical adjustment of x-axis labels.
`ylab`	Label for y-axis.
`ylabAngle`	Rotation angle of y-axis labels.
`ylabhjust`	Horizontal adjustment of y-axis labels.
`ylabvjust`	Vertical adjustment of y-axis labels.
`axisLabSize`	Size of x- and y-axis labels.
`title`	Plot title.
`titleLabSize`	Size of plot title.
`hline`	Draw one or more horizontal lines passing through this/these values on y-axis. For single values, only a single numerical value is necessary. For multiple lines, pass these as a vector, e.g., c(60,90).
`hlineType`	Line type for hline ('blank', 'solid', 'dashed', 'dotted', 'dotdash', 'longdash', 'twodash').
`hlineCol`	Colour of hline.
`hlineWidth`	Width of hline.
`vline`	Draw one or more vertical lines passing through this/these values on x-axis. For single values, only a single numerical value is necessary. For multiple lines, pass these as a vector, e.g., c(60,90).
`vlineType`	Line type for vline ('blank', 'solid', 'dashed', 'dotted', 'dotdash', 'longdash', 'twodash').
`vlineCol`	Colour of vline.
`vlineWidth`	Width of vline.
`gridlines.major`	Logical, indicating whether or not to draw major gridlines.
`gridlines.minor`	Logical, indicating whether or not to draw minor gridlines.
`borderWidth`	Width of the border on the x and y axes.
`borderColour`	Colour of the border on the x and y axes.
`returnPlot`	Logical, indicating whether or not to return the plot object.

Draw multiple bi-plots.

A cowplot object.

Kevin Blighe <kevin@clinicalbioinformatics.co.uk>

  options(scipen=10)
  options(digits=6)

  col <- 20
  row <- 20000
  mat1 <- matrix(
    rexp(col*row, rate = 0.1),
    ncol = col)
  rownames(mat1) <- paste0('gene', 1:nrow(mat1))
  colnames(mat1) <- paste0('sample', 1:ncol(mat1))

  mat2 <- matrix(
    rexp(col*row, rate = 0.1),
    ncol = col)
  rownames(mat2) <- paste0('gene', 1:nrow(mat2))
  colnames(mat2) <- paste0('sample', (ncol(mat1)+1):(ncol(mat1)+ncol(mat2)))

  mat <- cbind(mat1, mat2)

  metadata <- data.frame(row.names = colnames(mat))
  metadata$Group <- rep(NA, ncol(mat))
  metadata$Group[seq(1,40,2)] <- 'A'
  metadata$Group[seq(2,40,2)] <- 'B'
  metadata$CRP <- sample.int(100, size=ncol(mat), replace=TRUE)
  metadata$ESR <- sample.int(100, size=ncol(mat), replace=TRUE)

  p <- pca(mat, metadata = metadata, removeVar = 0.1)

  pairsplot(p, triangle = TRUE)