Sample PCA plot for transformed data

Plots the results of PCA on a 2-dimensional space

pcaplot(
  x,
  intgroup = NULL,
  ntop = 500,
  returnData = FALSE,
  title = NULL,
  pcX = 1,
  pcY = 2,
  text_labels = TRUE,
  point_size = 3,
  ellipse = TRUE,
  ellipse.prob = 0.95
)

Arguments

x

A DESeqTransform() object, with data in assay(x), produced for example by either rlog() or varianceStabilizingTransformation()/vst()

intgroup

Interesting groups: a character vector of names in colData(x) to use for grouping. Defaults to NULL, which would then select the first column of the colData slot

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)

Value

An object created by ggplot, which can be assigned and further customized.

Examples

dds <- makeExampleDESeqDataSet_multifac(betaSD_condition = 3, betaSD_tissue = 1)
rlt <- DESeq2::rlogTransformation(dds)
pcaplot(rlt, ntop = 200)
#> Defaulting to 'condition' as the `intgroup` parameter...