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Otsuka-Ochiai dissimilarity

Source: R/beta_div.r
ochiai.Rd

Also known as the cosine similarity for binary data.

Usage

ochiai(counts, margin = 1L, pairs = NULL, cpus = n_cpus())

Arguments

counts

A numeric matrix of count data (samples \(\times\) features). Typically contains absolute abundances (integer counts), though proportions are also accepted.

margin

The margin containing samples. 1 if samples are rows, 2 if samples are columns. Ignored when counts is a special object class (e.g. phyloseq). Default: 1

pairs

Which combinations of samples should distances be calculated for? The default value (NULL) calculates all-vs-all. Provide a numeric or logical vector specifying positions in the distance matrix to calculate. See examples.

cpus

How many parallel processing threads should be used. The default, n_cpus(), will use all logical CPU cores.

Details

The Otsuka-Ochiai dissimilarity is defined as: $$1 - \frac{J}{\sqrt{AB}}$$

Where:

  • \(A\), \(B\) : Number of features in each sample.

  • \(J\) : Number of features in common (intersection).

Base R Equivalent:

x <- ex_counts[1,]
y <- ex_counts[2,]
1 - sum(x & y) / sqrt(sum(x>0) * sum(y>0))

Input Types

The counts parameter is designed to accept a simple numeric matrix, but seamlessly supports objects from the following biological data packages:

  • phyloseq

  • rbiom

  • SummarizedExperiment

  • TreeSummarizedExperiment

For large datasets, standard matrix operations may be slow. See vignette('performance') for details on using optimized formats (e.g. sparse matrices) and parallel processing.

References

Ochiai, A. (1957). Zoogeographic studies on the soleoid fishes found in Japan and its neighbouring regions. Bulletin of the Japanese Society of Scientific Fisheries, 22, 526-530.

See also

beta_div(), vignette('bdiv'), vignette('bdiv_guide')

Other Presence/Absence metrics: hamming(), jaccard(), sorensen()

Examples

    ochiai(ex_counts)
#>           Saliva       Gums       Nose
#> Gums  0.10557281                      
#> Nose  0.18350342 0.08712907           
#> Stool 0.32917961 0.20000000 0.08712907