Plots the results of PCA on a 3-dimensional space, interactively
pcaplot3d(
  x,
  intgroup = "condition",
  ntop = 500,
  returnData = FALSE,
  title = NULL,
  pcX = 1,
  pcY = 2,
  pcZ = 3,
  text_labels = TRUE,
  point_size = 3
)A DESeq2::DESeqTransform() object, with data in assay(x),
produced for example by either DESeq2::rlog() or
DESeq2::varianceStabilizingTransformation()
Interesting groups: a character vector of
names in colData(x) to use for grouping
Number of top genes to use for principal components, selected by highest row variance
logical, if TRUE returns a data.frame for further use, containing the selected principal components and intgroup covariates for custom plotting
The plot title
The principal component to display on the x axis
The principal component to display on the y axis
The principal component to display on the z axis
Logical, whether to display the labels with the sample identifiers
Integer, the size of the points for the samples
A html-based visualization of the 3d PCA plot
dds <- makeExampleDESeqDataSet_multifac(betaSD_condition = 3, betaSD_tissue = 1)
rlt <- DESeq2::rlogTransformation(dds)
pcaplot3d(rlt, ntop = 200)