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
)
A DESeq2::DESeqTransform()
object, with data in assay(x)
,
produced for example by either DESeq2::rlog()
or
DESeq2::varianceStabilizingTransformation()
/DESeq2::vst()
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
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
Logical, whether to display the labels with the sample identifiers
Integer, the size of the points for the samples
Logical, whether to display the confidence ellipse for the selected groups
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)
#> Defaulting to 'condition' as the `intgroup` parameter...