plotPrevalence: Plot prevalence information
In microbiome/miaViz: Microbiome Analysis Plotting and Visualization

plotPrevalence

R Documentation

Plot prevalence information

Description

plotPrevalence and plotRowPrevalence visualize prevalence information.

Usage

plotPrevalence(x, ...)

## S4 method for signature 'SummarizedExperiment'
plotPrevalence(
  x,
  detection = detections,
  detections = c(0.01, 0.1, 1, 2, 5, 10, 20),
  prevalence = prevalences,
  prevalences = seq(0.1, 1, 0.1),
  assay.type = assay_name,
  assay_name = "counts",
  rank = NULL,
  BPPARAM = BiocParallel::SerialParam(),
  ...
)

plotPrevalentAbundance(x, ...)

## S4 method for signature 'SummarizedExperiment'
plotPrevalentAbundance(
  x,
  rank = NULL,
  assay.type = assay_name,
  assay_name = "counts",
  colour.by = colour_by,
  colour_by = NULL,
  size.by = size_by,
  size_by = NULL,
  shape.by = shape_by,
  shape_by = NULL,
  show.label = label,
  label = NULL,
  facet.by = facet_by,
  facet_by = NULL,
  ...
)

plotRowPrevalence(x, ...)

## S4 method for signature 'SummarizedExperiment'
plotRowPrevalence(
  x,
  rank = NULL,
  assay.type = assay_name,
  assay_name = "counts",
  detection = detections,
  detections = c(0.01, 0.1, 1, 2, 5, 10, 20),
  min.prevalence = min_prevalence,
  min_prevalence = 0,
  BPPARAM = BiocParallel::SerialParam(),
  ...
)

plotTaxaPrevalence(x, ...)

## S4 method for signature 'ANY'
plotTaxaPrevalence(x, ...)

plotFeaturePrevalence(x, ...)

## S4 method for signature 'ANY'
plotFeaturePrevalence(x, ...)

Arguments

`x`	a `SummarizedExperiment` object.
`detection`	`Numeric scalar`. Detection thresholds for absence/presence. Either an absolutes value compared directly to the values of `x` or a relative value between 0 and 1, if `TRUE`.
`detections`	Deprecated. Use `detection` instead.
`prevalence`	`Numeric scalar`. Prevalence thresholds (in 0 to 1). The required prevalence is strictly greater by default. To include the limit, set `include.lowest` to `TRUE`.
`prevalences`	Deprecated. Use `prevalence` instead.
`assay.type`	`Character scalar`. Defines which assay data to use. (Default: `"relabundance"`)
`assay_name`	Deprecated. Use `assay.type` instead.
`rank`, `...`	additional arguments as.relative `Logical scalar`. Should the relative values be calculated? (Default: `FALSE`) ndetection `Integer scalar`. Determines the number of breaks calculated detection thresholds when `detection=NULL`. When `TRUE`, `as_relative` is then also regarded as `TRUE`. (Default: `20`) If `!is.null(rank)` matching arguments are passed on to `agglomerateByRank`. See `?agglomerateByRank` for more details. additional arguments for plotting. See `mia-plot-args` for more details i.e. call `help("mia-plot-args")`
`BPPARAM`	A `BiocParallelParam` object specifying whether the UniFrac calculation should be parallelized.
`colour.by`	`Character scalar`. Specification of a feature to colour points by, see the `by` argument in `?retrieveFeatureInfo` for possible values. Only used with `layout = "point"`. (Default: `NULL`)
`colour_by`	Deprecated. Use `colour.by` instead.
`size.by`	`Character scalar`. Specification of a feature to size points by, see the `by` argument in `?retrieveFeatureInfo` for possible values. Only used with `layout = "point"`. (Default: `NULL`)
`size_by`	Deprecated. Use `size.by` instead.
`shape.by`	`Character scalar`. Specification of a feature to shape points by, see the `by` argument in `?retrieveFeatureInfo` for possible values. Only used with `layout = "point"`. (Default: `NULL`)
`shape_by`	Deprecated. Use `shape.by` instead.
`show.label`	`Logical scalar`, `character scalar` or `integer vector` for selecting labels from the rownames of `x`. If `rank` is not `NULL` the rownames might change. (Default: `NULL`)
`label`	Deprecated. Use `show.label` instead.
`facet.by`	`Character scalar`. Taxonomic rank to facet the plot by. Value must be of `taxonomyRanks(x)` Argument can only be used in function plotPrevalentAbundance.
`facet_by`	Deprecated. Use `facet.by` instead.
`min.prevalence`	`Numeric scalar`. Applied as a threshold for plotting. The threshold is applied per row and column. (Default: `0`)
`min_prevalence`	Deprecated. Use `min.prevalence` instead.

Details

Whereas plotPrevalence produces a line plot, plotRowPrevalence returns a heatmap.

Agglomeration on different taxonomic levels is available through the rank argument.

To exclude certain taxa, preprocess x to your liking, for example with subsetting via getPrevalent or agglomerateByPrevalence.

Value

A ggplot2 object or plotly object, if more than one prevalence was defined.

Examples

data(GlobalPatterns, package = "mia")

# Apply relative transformation
GlobalPatterns <- transformAssay(GlobalPatterns, method = "relabundance")

# plotting N of prevalence exceeding taxa on the Phylum level
plotPrevalence(GlobalPatterns, rank = "Phylum")
plotPrevalence(GlobalPatterns, rank = "Phylum") + scale_x_log10()

# plotting prevalence per taxa for different detection thresholds as heatmap
plotRowPrevalence(GlobalPatterns, rank = "Phylum")

# by default a continuous scale is used for different detection levels, 
# but this can be adjusted
plotRowPrevalence(
    GlobalPatterns, rank = "Phylum", assay.type = "relabundance",
    detection = c(0, 0.001, 0.01, 0.1, 0.2))
                   
# point layout for plotRowPrevalence can be used to visualize by additional
# information
plotPrevalentAbundance(
    GlobalPatterns, rank = "Family", colour.by = "Phylum") +
    scale_x_log10()

# When using function plotPrevalentAbundace, it is possible to create facets
# with 'facet.by'.
plotPrevalentAbundance(
    GlobalPatterns, rank = "Family",
    colour.by = "Phylum", facet.by = "Kingdom") +
    scale_x_log10()

microbiome/miaViz documentation built on Dec. 9, 2024, 2:18 a.m.