Update transformAssay with pseudocount TRUE/FALSE option

[RiboRings]

Hi!

This PR is meant to simplify pseudocount selection for transformations that need a pseudocount, as discussed in this OMA issue.

The option TRUE of transformAssay sets pseudocount to smallest positive value of assay, whereas FALSE sets it to 0.

[RiboRings]

Examples:

When negative values are present but pseudocount = TRUE, error arises because pseudocount should be set manually.

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

assay(tse, "neg_counts") <- assay(tse, "counts") - 2

tse <- transformAssay(tse,
                      method = "relabundance",
                      assay.type = "neg_counts",
                      pseudocount = TRUE)

# Error: The assay contains some negative values. 'pseudocount' must be specified manually.

tse <- transformAssay(tse,
                      method = "relabundance",
                      assay.type = "neg_counts",
                      pseudocount = 4)

# Warning message:
# The assay contains some negative values. Applying a pseudocount may produce meaningless data.

When pseudocount = TRUE, applied value is returned as message

tse <- transformAssay(tse,
                      method = "relabundance",
                      pseudocount = TRUE)

# A pseudocount of 1 was applied.

Warning when only positive values but pseudocount = TRUE or positive number

tse <- transformAssay(tse,
                      method = "clr",
                      assay.type = "relabundance",
                      pseudocount = TRUE)

# Warning message:
# The assay contains only positive values. Applying a pseudocount is not necessary.

When negative values present but pseudocount = 0, FALSE or TRUE

tse <- transformAssay(tse,
                      method = "log10",
                      assay.type = "clr",
                      pseudocount = FALSE)

# Error: The assay contains negative values and log10 transformation is being applied without
# pseudocount.`pseudocount` must be specified manually.

[TuomasBorman]

Nice