pcaplot {pcaExplorer} | R Documentation |
Plots the results of PCA on a 2-dimensional space
pcaplot( x, intgroup = "condition", ntop = 500, returnData = FALSE, title = NULL, pcX = 1, pcY = 2, text_labels = TRUE, point_size = 3, ellipse = TRUE, ellipse.prob = 0.95 )
x |
A |
intgroup |
Interesting groups: a character vector of
names in |
ntop |
Number of top genes to use for principal components, selected by highest row variance |
returnData |
logical, if TRUE returns a data.frame for further use, containing the selected principal components and intgroup covariates for custom plotting |
title |
The plot title |
pcX |
The principal component to display on the x axis |
pcY |
The principal component to display on the y axis |
text_labels |
Logical, whether to display the labels with the sample identifiers |
point_size |
Integer, the size of the points for the samples |
ellipse |
Logical, whether to display the confidence ellipse for the selected groups |
ellipse.prob |
Numeric, a value in the interval [0;1) |
An object created by ggplot
, which can be assigned and further customized.
dds <- makeExampleDESeqDataSet_multifac(betaSD_condition = 3, betaSD_tissue = 1) rlt <- DESeq2::rlogTransformation(dds) pcaplot(rlt, ntop = 200)