Usage
plotPCASCESet(object, ntop = 500, ncomponents = 2, exprs_values = "exprs", colour_by = NULL, shape_by = NULL, size_by = NULL, feature_set = NULL, return_SCESet = FALSE, scale_features = TRUE, draw_plot = TRUE, pca_data_input = "exprs", selected_variables = NULL, detect_outliers = FALSE, theme_size = 10, legend = "auto")
"plotPCA"(object, ntop = 500, ncomponents = 2, exprs_values = "exprs", colour_by = NULL, shape_by = NULL, size_by = NULL, feature_set = NULL, return_SCESet = FALSE, scale_features = TRUE, draw_plot = TRUE, pca_data_input = "exprs", selected_variables = NULL, detect_outliers = FALSE, theme_size = 10, legend = "auto")
Arguments
ntop
numeric scalar indicating the number of most variable features to
use for the PCA. Default is 500, but any ntop argument is
overrided if the feature_set argument is non-NULL.
ncomponents
numeric scalar indicating the number of principal
components to plot, starting from the first principal component. Default is
2. If ncomponents is 2, then a scatterplot of PC2 vs PC1 is produced.
If ncomponents is greater than 2, a pairs plots for the top components
is produced.
exprs_values
character string indicating which values should be used
as the expression values for this plot. Valid arguments are "tpm"
(default; transcripts per million), "norm_tpm" (normalised TPM
values), "fpkm" (FPKM values), "norm_fpkm" (normalised FPKM
values), "counts" (counts for each feature), "norm_counts",
"cpm" (counts-per-million), "norm_cpm" (normalised
counts-per-million), "exprs" (whatever is in the 'exprs' slot
of the SCESet object; default), "norm_exprs" (normalised
expression values) or "stand_exprs" (standardised expression values)
or any other named element of the assayData slot of the SCESet
object that can be accessed with the get_exprs function.
colour_by
character string defining the column of pData(object) to
be used as a factor by which to colour the points in the plot.
shape_by
character string defining the column of pData(object) to
be used as a factor by which to define the shape of the points in the plot.
size_by
character string defining the column of pData(object) to
be used as a factor by which to define the size of points in the plot.
feature_set
character, numeric or logical vector indicating a set of
features to use for the PCA. If character, entries must all be in
featureNames(object). If numeric, values are taken to be indices for
features. If logical, vector is used to index features and should have length
equal to nrow(object).
return_SCESet
logical, should the function return an SCESet
object with principal component values for cells in the
reducedDimension slot. Default is FALSE, in which case a
ggplot object is returned.
scale_features
logical, should the expression values be standardised
so that each feature has unit variance? Default is TRUE.
draw_plot
logical, should the plot be drawn on the current graphics
device? Only used if return_SCESet is TRUE, otherwise the plot
is always produced.
pca_data_input
character argument defining which data should be used
as input for the PCA. Possible options are "exprs" (default), which
uses expression data to produce a PCA at the cell level; "pdata" which
uses numeric variables from pData(object) to do PCA at the cell level;
and "fdata" which uses numeric variables from fData(object) to
do PCA at the feature level.
selected_variables
character vector indicating which variables in
pData(object) to use for the phenotype-data based PCA. Ignored if
the argument pca_data_input is anything other than "pdata".
detect_outliers
logical, should outliers be detected in the PC plot?
Only an option when pca_data_input argument is "pdata". Default
is FALSE.
theme_size
numeric scalar giving default font size for plotting theme
(default is 10).
legend
character, specifying how the legend(s) be shown? Default is
"auto", which hides legends that have only one level and shows others.
Alternatives are "all" (show all legends) or "none" (hide all legends).