plotloadings: Plot the component loadings for selected principal components...
In PCAtools: PCAtools: Everything Principal Components Analysis

Description Usage Arguments Details Value Author(s) Examples

Plot the component loadings for selected principal components / eigenvectors and label variables driving variation along these.

plotloadings(
  pcaobj,
  components = getComponents(pcaobj, seq_len(5)),
  rangeRetain = 0.05,
  absolute = FALSE,
  col = c("gold", "white", "royalblue"),
  colMidpoint = 0,
  shape = 21,
  shapeSizeRange = c(10, 10),
  legendPosition = "top",
  legendLabSize = 10,
  legendIconSize = 3,
  xlim = NULL,
  ylim = NULL,
  labSize = 2,
  labhjust = 1.5,
  labvjust = 0,
  drawConnectors = TRUE,
  positionConnectors = "right",
  widthConnectors = 0.5,
  typeConnectors = "closed",
  endsConnectors = "first",
  lengthConnectors = unit(0.01, "npc"),
  colConnectors = "grey50",
  xlab = "Principal component",
  xlabAngle = 0,
  xlabhjust = 0.5,
  xlabvjust = 0.5,
  ylab = "Component loading",
  ylabAngle = 0,
  ylabhjust = 0.5,
  ylabvjust = 0.5,
  axisLabSize = 16,
  title = "",
  subtitle = "",
  caption = "",
  titleLabSize = 16,
  subtitleLabSize = 12,
  captionLabSize = 12,
  hline = c(0),
  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.
`rangeRetain`	Cut-off value for retaining variables. The function will look across each specified principal component and retain the variables that fall within this top/bottom fraction of the loadings range.
`absolute`	Logical, indicating whether or not to plot absolute loadings.
`col`	Colours used for generation of fill gradient according to loadings values. Can be 2 or 3 colours.
`colMidpoint`	Mid-point (loading) for the colour range.
`shape`	Shape of the plotted points.
`shapeSizeRange`	Size range for the plotted points (min, max).
`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.
`labSize`	Size of labels.
`labhjust`	Horizontal adjustment of label.
`labvjust`	Vertical adjustment of label.
`drawConnectors`	Logical, indicating whether or not to connect plot labels to their corresponding points by line connectors.
`positionConnectors`	Position of the connectors and their labels with respect to the plotted points ('left', 'right').
`widthConnectors`	Line width of connectors.
`typeConnectors`	Have the arrow head open or filled ('closed')? ('open', 'closed').
`endsConnectors`	Which end of connectors to draw arrow head? ('last', 'first', 'both').
`lengthConnectors`	Length of the 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.
`subtitle`	Plot subtitle.
`caption`	Plot caption.
`titleLabSize`	Size of plot title.
`subtitleLabSize`	Size of plot subtitle.
`captionLabSize`	Size of plot caption.
`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.

Plot the component loadings for selected principal components / eigenvectors and label variables driving variation along these.

A ggplot2 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)

  plotloadings(p, drawConnectors = TRUE)