plotgg_rankabun2: Make rank abundance plot with Poisson confidence intervals.

In surh/AMOR: Abundance Matrix Operations in R

Make rank abundance plot with Poisson confidence intervals.

Description

Make a rank abundance plot with Poisson confidence intervals from a Dataset object. IMPORTANT: There is no guarantee that Poisson confidence intervals are representative of the data. This should be viewed only as descriptive statistic and not for inference.

Usage

plotgg_rankabun2(...)

## Default S3 method:
plotgg_rankabun2(
  Tab,
  Map,
  groupby,
  sortby,
  alpha = 0.2,
  theme = theme_blackbox(),
  variable.name = "Taxon",
  value.name = "Abundance",
  sample.id.name = "SAMPLEID"
)

## S3 method for class 'Dataset'
plotgg_rankabun2(
  Dat,
  groupby,
  sortby,
  alpha = 0.2,
  theme = theme_blackbox(),
  variable.name = "Taxon",
  value.name = "Abundance",
  sample.id.name = "SAMPLEID"
)

Arguments

Tab	A matrix object with samples as columns and taxa as rows.
Map	A data frame with metadata forTab. Each row must be a sample with row names matching column names in Tab and in the same order as in Tab.
groupby	Variable name to be used for grouping samples before plotting th rank abundance.
sortby	Variable value to be used as reference for sorting the taxa in the rank abundance plot.
alpha	Transparency parameter for ggplot2
theme	ggplot2 theme to be used for plotting.
variable.name	x-axis label in the plot.
value.name	y-axis label in the plot.
sample.id.name	name to store sample IDs in Map. Used for internal handling only.
Dat	A Dataset object.

Value

A ggplot2 plot.

Author(s)

Sur Herrera Paredes

See Also

plotgg_rankabun

Examples

data(Rhizo)
data(Rhizo.map)
data(Rhizo.tax)
Dat <- create_dataset(Rhizo, Rhizo.map, Rhizo.tax)

plotgg_rankabun2(Tab = Dat$Tab,Map = Dat$Map,
                 groupby = "fraction",sortby = "E")
plotgg_rankabun2(Dat, groupby = "fraction", sortby = "E")

surh/AMOR documentation built on Feb. 21, 2023, 6:31 a.m.