R: Plotting abundance data

plotAbundance {miaViz}

R Documentation

Plotting abundance data

Description

plotAbundance plots the abundance on a selected taxonomic rank. Since this probably makes sense only for relative abundance data, the assay used by default is expected to be in the slot ‘relabundance’.

Usage

plotAbundance(x, ...)

## S4 method for signature 'SummarizedExperiment'
plotAbundance(
  x,
  rank = taxonomyRanks(x)[1],
  features = NULL,
  order_rank_by = c("name", "abund", "revabund"),
  order_sample_by = NULL,
  decreasing = TRUE,
  use_relative = TRUE,
  layout = c("bar", "point"),
  one_facet = TRUE,
  ncol = 2,
  scales = "fixed",
  abund_values = "counts",
  ...
)

Arguments

`x`	a `SummarizedExperiment` object.
`...`	additional parameters for plotting. See `mia-plot-args` for more details
`rank`	a single `character` value defining the taxonomic rank to use. Must be a value of `taxonomyRanks(x)`.
`features`	data `colData` to be plotted below the abundance plot. Continuous numeric values will be plotted as point, whereas factors and character will be plotted as colour-code bar. (default: `features = NULL`)
`order_rank_by`	How to order abundance value: By name (“name”), by abundance (“abund”) or by reverse abundance (“revabund”).
`order_sample_by`	A single character value from the chosen rank of abundance data data or from `colData` to select values to order the abundance plot by. If the value is not part of `features`, it will be added. (default: `order_sample_by = NULL`)
`decreasing`	TRUE or FALSE: If the `order_sample_by` is defined and the values are numeric, should the values used to order in decreasing or increasing fashion? (default: `decreasing = FALSE`)
`use_relative`	`TRUE` or `FALSE`: Should the relative values be calculated? (default: `use_relative = TRUE`)
`layout`	Either “bar” or “point”.
`one_facet`	Should the plot be returned in on facet or split into different facet, one facet per different value detect in `rank`. If `features` or `order_sample_by` is not `NULL`, this setting will be disregarded.
`ncol, scales`	if `one_facet = FALSE`, `ncol` defines many columns should be for plotting the different facets and `scales` is used to define the behavior of the scales of each facet. Both values are passed onto `facet_wrap`.
`abund_values`	a `character` value defining which assay data to use. (default: `abund_values = "relabundance"`)

Details

Subsetting to rows of interested and ordering of those is expected to be done outside of this functions, e.g. x[1:2,]. This will plot data of all features present.

Value

a ggplot object or list of ggplot objects, if features are added to the plot.

Examples

data(GlobalPatterns, package="mia")
se <- GlobalPatterns

#
plotAbundance(se, abund_values="counts")
#
plotAbundance(se, abund_values="counts", rank = "Phylum", add_legend = FALSE)

# If rank is set to NULL plotAbundance behaves like plotExpression
plotAbundance(se, abund_values="counts", rank = NULL,
              features = head(rownames(se)))
              
# Factors can also be plotted and ordered by
plotAbundance(se, abund_values="counts", rank = "Phylum",
              features = "SampleType",
              order_sample_by = "SampleType")

[Package miaViz version 1.0.1 Index]