Plot abundance density

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,
  ...
)

Arguments

x

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")

layout

Character scalar. Selects the layout of the plot. There are three different options: jitter, density, and point plot. (default: layout = "jitter")

assay.type

Character scalar value defining which assay data to use. (Default: "relabundance")

assay_name

Deprecate. Use assay.type instead.

n

Integer scalar. Specifies the number of the most abundant taxa to show. (Default: min(nrow(x), 25L))

colour.by

Character scalar. Defines a column from colData, that is used to color plot. Must be a value of colData() function. (Default: NULL)

colour_by

Deprecated. Use colour.by instead.

shape.by

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)

shape_by

Deprecated. Use shape.by instead.

size.by

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)

size_by

Deprecated. Use size.by instead.

decreasing

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)

order_descending

Deprecated. Use order.descending instead.

Value

A ggplot2 object

Details

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.

Author

Leo Lahti and Tuomas Borman. Contact: microbiome.github.io

Examples

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()

Arguments

Value

Details

See also

Author

Examples