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Beta diversity wrapper

Source: R/beta_div.r
beta_div.Rd

Beta diversity wrapper

Usage

beta_div(counts, metric, ...)

Arguments

counts

An OTU abundance matrix where each column is a sample, and each row is an OTU. Any object coercible with as.matrix() can be given here, as well as phyloseq, rbiom, SummarizedExperiment, and TreeSummarizedExperiment objects.

metric

The name of a beta diversity metric. Current options are c('bray_curtis', 'sorenson', 'canberra', 'euclidean', 'gower', 'jaccard', 'kulczynski', 'manhattan', 'unweighted_unifrac', 'weighted_unifrac', 'normalized_unifrac', 'generalized_unifrac', 'variance_adjusted_unifrac'). Supports flexible name matching - see details section below. Options are also available via names(metrics$beta).

...

Additional options to pass through to the called function. I.e. tree, weighted, pairs, alpha, or cpus.

Value

A numeric vector.

Details

Flexible name matching

Case insensitive and partial matching. Any runs of non-alpha characters are converted to underscores. E.g. metric = 'Bray Curtis selects Bray-Curtis.

UniFrac names can be shortened to the first letter plus "unifrac". E.g. uunifrac, w_unifrac, or V UniFrac. These also support partial matching, but the primary options take precedence. For instance metric = 'g' selects Gower, whereas metric = 'gu' selects Generalized UniFrac.

Finished code should always use the full primary option name to avoid ambiguity with future additions to the metrics list.

See also

Other alpha_diversity: alpha_div(), chao1(), faith(), inv_simpson(), observed(), shannon(), simpson()

Examples

    # Example counts matrix
    ex_counts
#>                   Saliva Gums Nose Stool
#> Streptococcus        162  793   22     1
#> Bacteroides            2    4    2   611
#> Corynebacterium        0    0  498     1
#> Haemophilus          180   87    2     1
#> Propionibacterium      1    1  251     0
#> Staphylococcus         0    1  236     1
    
    # Bray-Curtis distances
    beta_div(ex_counts, 'bray_curtis')
#>          Saliva      Gums      Nose
#> Gums  0.5905768                    
#> Nose  0.9601770 0.9704797          
#> Stool 0.9916667 0.9906729 0.9926199
    
    # Kulczynski distances
    beta_div(ex_counts, 'k')
#>          Saliva      Gums      Nose
#> Gums  0.4925704                    
#> Nose  0.9475164 0.9703510          
#> Stool 0.9909509 0.9903586 0.9921546
    
    # Generalized UniFrac distances
    beta_div(ex_counts, 'GUniFrac', tree = ex_tree)
#>          Saliva      Gums      Nose
#> Gums  0.4471644                    
#> Nose  0.8215129 0.7607876          
#> Stool 0.9727827 0.9784242 0.9730332