Prevalence plot of all or agglomerated features in a
SummarizedExperiment
object. The panel implements plotPrevalence
to generate the plot.
The PrevalencePlot(...) constructor creates an instance of an
PrevalencePlot class, where any slot and its value can be passed to
... as a named argument.
The following slots control the thresholds used in the visualization:
detection Numeric scalar. Detection threshold between 0
and 1 for absence/presence. (Defualt: 0)
prevalence Numeric scalar. Prevalence threshold between 0
and 1. The required prevalence is strictly greater by default. To
include the limit, set include.lowest to TRUE. (Default:
0)
assay.type Character scalar. The name of the assay to
show. (Default: "relabundance")
rank Character scalar. The taxonomic rank to visualise.
(Default: NULL)
show.rank Logical scalar. Should options for the
taxonomic rank appear. (Default: FALSE)
include.lowest Logical scalar. Should features with
prevalence equal to prevalence be included. (Default: FALSE)
In addition, this class inherits all slots from its parent class
Panel.
# Import TreeSE
library(mia)
data("Tengeler2020", package = "mia")
tse <- Tengeler2020
tse <- transformAssay(tse,
assay.type = "counts",
method = "relabundance")
# Store panel into object
panel <- PrevalencePlot()
# View some adjustable parameters
head(slotNames(panel))
#> [1] "detection" "prevalence" "assay.type" "rank"
#> [5] "include.lowest" "show.rank"
# Launch iSEE with custom initial panel
if (interactive()) {
iSEE(tse, initial = c(panel))
}