PCAtools (version 1.3.6)

eigencorplot: eigencorplot

Description

Correlate principal components to continuous variable metadata and test significancies of these.

Usage

eigencorplot(pcaobj,
  components = getComponents(pcaobj, seq_len(10)),
  metavars,
  titleX = '',
  cexTitleX = 1.0,
  rotTitleX = 0,
  colTitleX = 'black',
  fontTitleX = 2,
  titleY = '',
  cexTitleY = 1.0,
  rotTitleY = 0,
  colTitleY = 'black',
  fontTitleY = 2,
  cexLabX = 1.0,
  rotLabX = 0,
  colLabX = 'black',
  fontLabX = 2,
  cexLabY = 1.0,
  rotLabY = 0,
  colLabY = 'black',
  fontLabY = 2,
  posLab = 'bottomleft',
  col = c('blue4', 'blue3', 'blue2', 'blue1', 'white',
    'red1', 'red2', 'red3', 'red4'),
  posColKey = 'right',
  cexLabColKey = 1.0,
  cexCorval = 1.0,
  colCorval = 'black',
  fontCorval = 1,
  scale = TRUE,
  main = '',
  cexMain = 2,
  rotMain = 0,
  colMain = 'black',
  fontMain = 2,
  corFUN = 'pearson',
  corUSE = 'pairwise.complete.obs',
  signifSymbols = c('***', '**', '*', ''),
  signifCutpoints = c(0, 0.001, 0.01, 0.05, 1),
  colFrame = 'white',
  plotRsquared = FALSE,
  returnPlot = TRUE)

Arguments

pcaobj

Object of class 'pca' created by pca(). REQUIRED.

components

The principal components to be included in the plot. DEFAULT = getComponents(pcaobj, seq_len(10)). OPTIONAL.

metavars

A vector of column names in metadata representing continuos variables. REQUIRED.

titleX

X-axis title. DEFAULT = ''. OPTIONAL.

cexTitleX

X-axis title cex. DEFAULT = 1.0. OPTIONAL.

rotTitleX

X-axis title rotation in degrees. DEFAULT = 0. OPTIONAL.

colTitleX

X-axis title colour. DEFAULT = 'black'. OPTIONAL.

fontTitleX

X-axis title font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 2. OPTIONAL.

titleY

Y-axis title. DEFAULT = ''. OPTIONAL.

cexTitleY

Y-axis title cex. DEFAULT = 1.0. OPTIONAL.

rotTitleY

Y-axis title rotation in degrees. DEFAULT = 0. OPTIONAL.

colTitleY

Y-axis title colour. DEFAULT = 'black'. OPTIONAL.

fontTitleY

Y-axis title font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 2. OPTIONAL.

cexLabX

X-axis labels cex. DEFAULT = 1.0. OPTIONAL.

rotLabX

X-axis labels rotation in degrees. DEFAULT = 0. OPTIONAL.

colLabX

X-axis labels colour. DEFAULT = 'black'. OPTIONAL.

fontLabX

X-axis labels font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 2. OPTIONAL.

cexLabY

Y-axis labels cex. DEFAULT = 1.0. OPTIONAL.

rotLabY

Y-axis labels rotation in degrees. DEFAULT = 0. OPTIONAL.

colLabY

Y-axis labels colour. DEFAULT = 'black'. OPTIONAL.

fontLabY

Y-axis labels font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 2. OPTIONAL.

posLab

Positioning of the X- and Y-axis labels. 'bottomleft', bottom and left; 'topright', top and right; 'all', bottom / top and left /right; 'none', no labels. DEFAULT = 'bottomleft'. OPTIONAL.

col

Colour shade gradient for RColorBrewer. DEFAULT = c('blue4', 'blue3', 'blue2', 'blue1', 'white', 'red1', 'red2', 'red3', 'red4'). OPTIONAL.

posColKey

Position of colour key. 'bottom', 'left', 'top', 'right'. DEFAULT = 'right'. OPTIONAL.

cexLabColKey

Colour key labels cex. DEFAULT = 1.0. OPTIONAL.

cexCorval

Correlation values cex. DEFAULT = 1.0. OPTIONAL.

colCorval

Correlation values colour. DEFAULT = 'black'. OPTIONAL.

fontCorval

Correlation values font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 1. OPTIONAL.

scale

Logical, indicating whether or not to scale the colour range to max and min cor values. DEFAULT = TRUE. OPTIONAL.

main

Plot title. DEFAULT = ''. OPTIONAL.

cexMain

Plot title cex. DEFAULT = 2. OPTIONAL.

rotMain

Plot title rotation in degrees. DEFAULT = 0. OPTIONAL.

colMain

Plot title colour. DEFAULT = 'black'. OPTIONAL.

fontMain

Plot title font style. 1, plain; 2, bold; 3, italic; 4, bold-italic. DEFAULT = 2. OPTIONAL.

corFUN

Correlation method: 'pearson', 'spearman', or 'kendall'. DEFAULT = 'pearson'. OPTIONAL.

corUSE

Method for handling missing values (see documentation for cor function via ?cor). 'everything', 'all.obs', 'complete.obs', 'na.or.complete', or 'pairwise.complete.obs'. DEFAULT = 'pairwise.complete.obs'. OPTIONAL.

signifSymbols

Statistical significance symbols to display beside correlation values. DEFAULT = c('***', '**', '*', ''). OPTIONAL.

signifCutpoints

Cut-points for statistical significance. DEFAULT = c(0, 0.001, 0.01, 0.05, 1). OPTIONAL.

colFrame

Frame colour. DEFAULT = 'white'. OPTIONAL.

plotRsquared

Logical, indicating whether or not to plot R-squared values. DEFAULT = FALSE. OPTIONAL.

returnPlot

Logical, indicating whether or not to return the plot object. DEFAULT = TRUE. OPTIONAL.

Value

A lattice object.

Examples

# NOT RUN {
  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)

  eigencorplot(p, components = getComponents(p, 1:10),
    metavars = c('ESR', 'CRP'))
# }