| eigencorplot {PCAtools} | R Documentation |
Correlate principal components to continuous variable metadata and test significancies of these.
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',
corMultipleTestCorrection = 'none',
signifSymbols = c('***', '**', '*', ''),
signifCutpoints = c(0, 0.001, 0.01, 0.05, 1),
colFrame = 'white',
plotRsquared = FALSE,
returnPlot = TRUE)
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. |
corMultipleTestCorrection |
Multiple testing p-value adjustment method. Any method from stats::p.adjust() can be used. Activating this function means that signifSymbols and signifCutpoints then relate to adjusted (not nominal) p-values. DEFAULT = 'none'. |
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. |
A lattice 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)
eigencorplot(p, components = getComponents(p, 1:10),
metavars = c('ESR', 'CRP'))