getPrevalent / getPrevalence

[antagomir]

In some applications we like to calculate prevalences per group, and possibly then pick features that are sufficiently prevalent in at least one group. Currently this can be done e.g. with:

library(mia)
data(peerj13075)
tse <- peerj13075

# Split the tse data object by milk stage
tses <- splitOn(tse, group = "Geographical_location")

# Calculate prevalences per group (features x groups table)
prev <- sapply(tses, function (tse) getPrevalence(tse, assay.type="counts"))

mia could possibly simplify this and provide a wrapper like just:

prev <- getPrevalenceByGroup(tse, assay.type="counts", group="Geographical_location")

But perhaps it is simple enough already without? At least we could add an example of this on the manpage of getPrevalence?