Data set with ~60,000 microorganisms

A data set containing the microbial taxonomy of six kingdoms from the Catalogue of Life. MO codes can be looked up using as.mo.

microorganisms

Format

A data.frame with 57,158 observations and 14 variables:

mo

ID of microorganism as used by this package

col_id

Catalogue of Life ID

fullname

Full name, like "Echerichia coli"

kingdom

Taxonomic kingdom of the microorganism

phylum

Taxonomic phylum of the microorganism

class

Taxonomic class of the microorganism

order

Taxonomic order of the microorganism

family

Taxonomic family of the microorganism

genus

Taxonomic genus of the microorganism

species

Taxonomic species of the microorganism

subspecies

Taxonomic subspecies of the microorganism

rank

Taxonomic rank of the microorganism, like "species" or "genus"

ref

Author(s) and year of concerning scientific publication

species_id

ID of the species as used by the Catalogue of Life

Source

Catalogue of Life: Annual Checklist (public online database), www.catalogueoflife.org.

Details

Manually added were:

  • 9 species of Streptococcus (beta haemolytic groups A, B, C, D, F, G, H, K and unspecified)

  • 2 species of Staphylococcus (coagulase-negative [CoNS] and coagulase-positive [CoPS])

  • 2 other undefined (unknown Gram negatives and unknown Gram positives)

Catalogue of Life


This package contains the complete taxonomic tree of almost all microorganisms (~60,000 species) from the authoritative and comprehensive Catalogue of Life (http://www.catalogueoflife.org). The Catalogue of Life is the most comprehensive and authoritative global index of species currently available.

Click here for more information about the included taxa. The Catalogue of Life releases updates annually; check which version was included in this package with catalogue_of_life_version().

Read more on our website!

On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.

See also

as.mo, mo_property, microorganisms.codes