plotCCA.Rd
plotRDA
and plotCCA
create an RDA/CCA plot starting from the
output of CCA and RDA
functions, two common methods
for supervised ordination of microbiome data.
plotCCA(x, ...)
# S4 method for class 'SingleCellExperiment'
plotCCA(x, dimred, ...)
# S4 method for class 'matrix'
plotCCA(x, ...)
plotRDA(x, ...)
# S4 method for class 'SingleCellExperiment'
plotRDA(x, dimred, ...)
# S4 method for class 'matrix'
plotRDA(x, ...)
a
TreeSummarizedExperiment
or a matrix of weights. The latter is returned as output from
getRDA
.
additional parameters for plotting, inherited from
plotReducedDim
,
geom_label
and
geom_label_repel
.
add.ellipse
: One of
c(TRUE, FALSE, "fill", "colour")
, indicating whether
ellipses should be present, absent, filled or colored.
(default: ellipse.fill = TRUE
)
ellipse.alpha
: Numeric scalar
. Between 0 and 1.
Adjusts the opacity of ellipses. (Default: 0.2
)
ellipse.linewidth
: Numeric scalar
. Specifies the size
of ellipses. (Default: 0.1
)
ellipse.linetype
: Integer scalar
. Specifies the style
of ellipses. (Default: 1
)
confidence.level
: Numeric scalar
. Between 0 and 1.
Adjusts confidence level. (Default: 0.95
)
add.vectors
: Logical scalar
. Should vectors appear in
the plot. (Default: TRUE
)
vec.size
: Numeric scalar
. Specifies the size of
vectors. (Default: 0.5
)
vec.colour
: Character scalar
. Specifies the colour of
vectors. (Default: "black"
)
vec.linetype
: Integer scalar
. Specifies the style of
vector lines. (Default: 1
)
arrow.size
: Numeric scalar
. Specifies the size of
arrows. (Default: arrow.size = 0.25
)
label.size
: Numeric scalar
. Specifies the size of text
and labels. (Default: 4
)
label.colour
: Character scalar
. Specifies the colour of
text and labels. (Default: "black"
)
sep.group
: Character scalar
. Specifies the separator
used in the labels. (Default: "\U2014"
)
repl.underscore
: Character scalar
. Used to replace
underscores in the labels. (Default: " "
)
vec.text
: Logical scalar
. Should text instead of labels
be used to label vectors. (Default: TRUE
)
repel.labels
: Logical scalar
. Should labels be
repelled. (Default: TRUE
)
parse.labels
: Logical scalar
. Should labels be parsed.
(Default: TRUE
)
add.significance
: Logical scalar
. Should explained
variance and p-value appear in the labels. (Default: TRUE
)
add.expl.var
: Logical scalar
. Should explained
variance appear on the coordinate axes. (Default: TRUE
)
add.centroids
: Logical scalar
. Should centroids
of variables be added. (Default: FALSE
)
add.species
: Logical scalar
. Should species
scores be added. (Default: FALSE
)
Character scalar
or integer scalar
. Determines
the reduced dimension to
plot. This is the output of addRDA
and resides in
reducedDim(tse, dimred)
.
A ggplot2
object
plotRDA
and plotCCA
create an RDA/CCA plot starting from the
output of CCA and RDA
functions, two common methods
for supervised ordination of microbiome data. Either a
TreeSummarizedExperiment
or a matrix object is supported as input. When the input is a
TreeSummarizedExperiment, this should contain the output of addRDA
in the reducedDim slot and the argument dimred
needs to be defined.
When the input is a matrix, this should be returned as output from
getRDA. However, the first method is recommended because it provides
the option to adjust aesthetics to the colData variables through the
arguments inherited from plotReducedDim
.
# Load dataset
library(miaViz)
data("enterotype", package = "mia")
tse <- enterotype
# Run RDA and store results into TreeSE
tse <- addRDA(
tse,
formula = assay ~ ClinicalStatus + Gender + Age,
FUN = getDissimilarity,
distance = "bray",
na.action = na.exclude
)
# Create RDA plot coloured by variable
plotRDA(tse, "RDA", colour.by = "ClinicalStatus")
#> Warning: Removed 243 rows containing non-finite outside the scale range
#> (`stat_ellipse()`).
#> Too few points to calculate an ellipse
#> Too few points to calculate an ellipse
#> Warning: Removed 243 rows containing missing values or values outside the scale range
#> (`geom_point()`).
# Create RDA plot with empty ellipses
plotRDA(tse, "RDA", colour.by = "ClinicalStatus", add.ellipse = "colour")
#> Warning: Removed 243 rows containing non-finite outside the scale range
#> (`stat_ellipse()`).
#> Too few points to calculate an ellipse
#> Too few points to calculate an ellipse
#> Warning: Removed 243 rows containing missing values or values outside the scale range
#> (`geom_point()`).
# Create RDA plot with text encased in labels
plotRDA(tse, "RDA", colour.by = "ClinicalStatus", vec.text = FALSE)
#> Warning: Removed 243 rows containing non-finite outside the scale range
#> (`stat_ellipse()`).
#> Too few points to calculate an ellipse
#> Too few points to calculate an ellipse
#> Warning: Removed 243 rows containing missing values or values outside the scale range
#> (`geom_point()`).
# Create RDA plot without repelling text
plotRDA(tse, "RDA", colour.by = "ClinicalStatus", repel.labels = FALSE)
#> Warning: Removed 243 rows containing non-finite outside the scale range
#> (`stat_ellipse()`).
#> Too few points to calculate an ellipse
#> Too few points to calculate an ellipse
#> Warning: Removed 243 rows containing missing values or values outside the scale range
#> (`geom_point()`).
# Create RDA plot without vectors
plotRDA(tse, "RDA", colour.by = "ClinicalStatus", add.vectors = FALSE)
#> Warning: 'add.vectors' is FALSE, so other arguments for vectors and labels will be disregarded.
#> Warning: Removed 243 rows containing non-finite outside the scale range
#> (`stat_ellipse()`).
#> Too few points to calculate an ellipse
#> Too few points to calculate an ellipse
#> Warning: Removed 243 rows containing missing values or values outside the scale range
#> (`geom_point()`).
# Calculate RDA as a separate object
rda_mat <- getRDA(
tse,
formula = assay ~ ClinicalStatus + Gender + Age,
FUN = getDissimilarity,
distance = "bray",
na.action = na.exclude
)
# Create RDA plot from RDA matrix
plotRDA(rda_mat)
#> Warning: Removed 243 rows containing missing values or values outside the scale range
#> (`geom_point()`).