plotAbundanceDensity.Rd
This function plots abundance of the most abundant taxa.
plotAbundanceDensity(x, ...)
# S4 method for class 'SummarizedExperiment'
plotAbundanceDensity(
x,
layout = c("jitter", "density", "point"),
assay.type = assay_name,
assay_name = "counts",
n = min(nrow(x), 25L),
colour.by = colour_by,
colour_by = NULL,
shape.by = shape_by,
shape_by = NULL,
size.by = size_by,
size_by = NULL,
decreasing = order_descending,
order_descending = TRUE,
...
)
a
SummarizedExperiment
object.
additional parameters for plotting.
xlab
Character scalar
. Selects the x-axis label.
(Default: assay.type
)
ylab
Character scalar
. Selects the y-axis label.
ylab
is disabled when layout = "density"
.
(Default: "Taxa"
)
point.alpha
Numeric scalar
. From range 0 to 1. Selects the transparency of
colour in jitter
and point
plot. (Default: 0.6
)
point.shape
Positive integer scalar
. Value selecting the shape of point in
jitter
and point
plot. (Default: 21
)
point.size
Positive integer scalar
. Selects the size of point in
jitter
and point
plot. (Default: 2
)
add_legend
Logical scalar
. Determines if legend is added.
(Default: TRUE
)
flipped
: Logical scalar
. Determines if the orientation of plot is changed
so that x-axis and y-axis are swapped. (Default: FALSE
)
add_x_text
Logical scalar
. Determines if text that represents values is included
in x-axis. (Default: TRUE
)
See mia-plot-args
for more details i.e. call help("mia-plot-args")
Character scalar
. Selects the layout of the plot.
There are three different options: jitter
, density
, and
point
plot. (default: layout = "jitter"
)
Character scalar
value defining which assay data to
use. (Default: "relabundance"
)
Deprecate. Use assay.type
instead.
Integer scalar
. Specifies the number of the most abundant taxa
to show. (Default: min(nrow(x), 25L)
)
Character scalar
. Defines a column from
colData
, that is used to color plot. Must be a value of
colData()
function. (Default: NULL
)
Deprecated. Use colour.by
instead.
Character scalar
. Defines a column from
colData
, that is used to group observations to different point shape
groups. Must be a value of colData()
function. shape.by
is
disabled when layout = "density"
. (Default: NULL
)
Deprecated. Use shape.by
instead.
Character scalar
. Defines a column from
colData
, that is used to group observations to different point size
groups. Must be a value of colData()
function. size.by
is
disabled when layout = "density"
. (Default: NULL
)
Deprecated. Use size.by
instead.
Logical scalar
. Indicates whether the results should be ordered
in a descending order or not. If NA
is given the order
as found in x
for the n
most abundant taxa is used.
(Default: TRUE
)
Deprecated. Use order.descending
instead.
A ggplot2
object
This function plots abundance of the most abundant taxa. Abundance can be plotted as a jitter plot, a density plot, or a point plot. By default, x-axis represents abundance and y-axis taxa. In a jitter and point plot, each point represents abundance of individual taxa in individual sample. Most common abundances are shown as a higher density.
A density plot can be seen as a smoothened bar plot. It visualized distribution of abundances where peaks represent most common abundances.
data("peerj13075", package = "mia")
tse <- peerj13075
# Plots the abundances of 25 most abundant taxa. Jitter plot is the default option.
plotAbundanceDensity(tse, assay.type = "counts")
# Counts relative abundances
tse <- transformAssay(tse, method = "relabundance")
# Plots the relative abundance of 10 most abundant taxa.
# "nationality" information is used to color the points. X-axis is log-scaled.
plotAbundanceDensity(
tse, layout = "jitter", assay.type = "relabundance", n = 10,
colour.by = "Geographical_location") +
scale_x_log10()
#> Warning: log-10 transformation introduced infinite values.
# Plots the relative abundance of 10 most abundant taxa as a density plot.
# X-axis is log-scaled
plotAbundanceDensity(
tse, layout = "density", assay.type = "relabundance", n = 10 ) +
scale_x_log10()
#> Warning: log-10 transformation introduced infinite values.
#> Warning: Removed 134 rows containing non-finite outside the scale range
#> (`stat_density()`).
# Plots the relative abundance of 10 most abundant taxa as a point plot.
# Point shape is changed from default (21) to 41.
plotAbundanceDensity(
tse, layout = "point", assay.type = "relabundance", n = 10,
point.shape = 41)
# Plots the relative abundance of 10 most abundant taxa as a point plot.
# In addition to colour, groups can be visualized by size and shape in point plots,
# and adjusted for point size
plotAbundanceDensity(
tse, layout = "point", assay.type = "relabundance", n = 10,
shape.by = "Geographical_location", size.by = "Age", point.size=1)
#> Warning: Using size for a discrete variable is not advised.
# Ordering via decreasing
plotAbundanceDensity(
tse, assay.type = "relabundance", decreasing = FALSE)
# for custom ordering set decreasing = NA and order the input object
# to your wishes
plotAbundanceDensity(
tse, assay.type = "relabundance", decreasing = NA)
# Box plots and violin plots are supported by scater::plotExpression.
# Plots the relative abundance of 5 most abundant taxa as a violin plot.
library(scater)
top <- getTop(tse, top = 5)
plotExpression(tse, features = top, assay.type = "relabundance") + ggplot2::coord_flip()
# Plots the relative abundance of 5 most abundant taxa as a box plot.
plotExpression(tse, features = top, assay.type = "relabundance",
show_violin = FALSE, show_box = TRUE) + ggplot2::coord_flip()