rbiom (version 3.1.0)

matrix_ops: Deprecated matrix transformations

Description

A collection of transformations that operate directly on matrices.

Usage

mtx_rarefy(
  mtx,
  margin = 2L,
  depth = 0.1,
  n = NULL,
  seed = 0L,
  upsample = NULL,
  cpus = NULL
)
mtx_percent(mtx, margin = 2L)
mtx_rescale(mtx, margin = 2L, range = c(0, 1))
rarefy_cols(mtx, depth = 0.1, n = NULL, seed = 0L, cpus = NULL)
rescale_rows(mtx)
rescale_cols(mtx)

Value

A A numeric matrix or sparse matrix, depending on the input type, with the same dimensions as mtx.

Arguments

mtx

A numeric matrix or sparse matrix of counts.

margin

Apply the transformation to the matrix's rows (margin=1L) or columns (margin=2L). Instead of 1L and 2L, you may also use 'rows' and 'cols'. Default: 2L (column-wise, aka sample-wise for otu tables)

depth

How many observations to keep per sample.

n

Deprecated. The number of samples to keep. This argument is ignored in the current version.

seed

An integer seed for randomizing which observations to keep or drop.

upsample

If the count data is in percentages, provide an integer value here to scale each sample's observations to integers that sum to this value. Maps to inflate in the new syntax.

cpus

The number of CPUs to use. Set to NULL to use all available, or to 1 to disable parallel processing. Default: NULL

range

When rescaling, what should the minimum and maximum values be? Default: c(0, 1)

Examples

    mtx <- matrix(1:12, ncol = 3, dimnames = list(paste0("OTU", 1:4), paste0("Sample", 1:3)))
    
    mtx
    
    suppressWarnings({
    
      mtx_rarefy(mtx)
      
      rarefy_cols(mtx)
      
      mtx_percent(mtx)
      
      mtx_rescale(mtx)
      
      rescale_rows(mtx)
      
      rescale_cols(mtx)
      
    })