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taxize (version 0.9.4)

tax_agg: Aggregate species data to given taxonomic rank

Description

Aggregate species data to given taxonomic rank

Usage

tax_agg(x, rank, db = "ncbi", verbose = FALSE, ...)

# S3 method for tax_agg print(x, ...)

Arguments

x

Community data matrix. Taxa in columns, samples in rows.

rank

character; Taxonomic rank to aggregate by.

db

character; taxonomic API to use, 'ncbi, 'itis' or both, see tax_name. Note that each taxonomic data source has their own identifiers, so that if you provide the wrong db value for the identifier you could get a result, but it will likely be wrong (not what you were expecting).

verbose

(logical) If FALSE (Default) suppress messages

...

Other arguments passed to get_tsn or get_uid.

Value

A list of class tax_agg with the following items:

x

Community data matrix with aggregated data.

by

A lookup-table showing which taxa were aggregated.

n_pre

Number of taxa before aggregation.

rank

Rank at which taxa have been aggregated.

Details

tax_agg aggregates (sum) taxa to a specific taxonomic level. If a taxon is not found in the database (ITIS or NCBI) or the supplied taxon is on higher taxonomic level this taxon is not aggregated.

See Also

tax_name

Examples

Run this code
# NOT RUN {
if (requireNamespace("vegan", quietly = TRUE)) {
  # use dune dataset
  library("vegan")
  data(dune, package='vegan')
  species <- c("Bellis perennis", "Empetrum nigrum", "Juncus bufonius",
  "Juncus articulatus",
  "Aira praecox", "Eleocharis parvula", "Rumex acetosa", "Vicia lathyroides",
  "Brachythecium rutabulum", "Ranunculus flammula", "Cirsium arvense",
  "Hypochaeris radicata", "Leontodon autumnalis", "Potentilla palustris",
  "Poa pratensis", "Calliergonella cuspidata", "Trifolium pratense",
  "Trifolium repens", "Anthoxanthum odoratum", "Salix repens", "Achillea
  millefolium",
  "Poa trivialis", "Chenopodium album", "Elymus repens", "Sagina procumbens",
  "Plantago lanceolata", "Agrostis stolonifera", "Lolium perenne", "Alopecurus
  geniculatus", "Bromus hordeaceus")
  colnames(dune) <- species

  # aggregate sample to families
  (agg <- tax_agg(dune, rank = 'family', db = 'ncbi'))

  # extract aggregated community data matrix for further usage
  agg$x
  # check which taxa have been aggregated
  agg$by
}

# A use case where there are different taxonomic levels in the same dataset
spnames <- c('Puma','Ursus americanus','Ursidae')
df <- data.frame(c(1,2,3), c(11,12,13), c(1,4,50))
names(df) <- spnames
out <- tax_agg(df, rank = 'family', db='itis')
out$x

# You can input a matrix too
mat <- matrix(c(1,2,3, 11,12,13), nrow = 2, ncol = 3,
 dimnames=list(NULL, c('Puma concolor','Ursus americanus','Ailuropoda melanoleuca')))
tax_agg(mat, rank = 'family', db='itis')
# }

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