rbiom (version 3.1.0)

biom_inflate: Inflate Relative Abundances to Integer Counts

Description

Scaling a matrix of proportions (or counts) to a new target depth, rounding to integers while preserving the original total abundance sum exactly.

Usage

biom_inflate(biom, depth = NULL, clone = TRUE)

Value

An rbiom object.

Arguments

biom

An rbiom object, or any value accepted by as_rbiom().

depth

The target library size (sum) for each sample. Must be an integer greater than 0. If NULL (the default), the depth is estimated per-sample using the "Singleton Peak Heuristic". See suggest_inflate_depths() for algorithm details.

clone

Create a copy of biom before modifying. If FALSE, biom is modified in place as a side-effect. See speed ups for use cases. Default: TRUE

Rounding (Largest Remainder Method)

To ensure the sum of the resulting counts equals the target depth exactly (avoiding drift caused by simple rounding), this function uses the Largest Remainder Method (also known as the Hare-Niemeyer method).

It assigns the integer part of the scaled value to each feature, and then distributes the remaining counts to the features with the largest fractional parts.

See Also

suggest_inflate_depths() for details on how target depths are estimated when depth = NULL.

Other transformations: biom_relativize(), biom_rescale(), modify_metadata, rarefy(), slice_metadata, subset(), with()

Examples

    library(rbiom)
    
    biom <- hmp50[1:5]
    sample_sums(biom)
    
    biom <- biom_relativize(biom)
    sample_sums(biom)
    
    biom <- biom_inflate(biom)
    sample_sums(biom)