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add oxygen tolerance
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R/data.R
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R/data.R
@ -93,6 +93,7 @@
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#' - `rank`\cr Text of the taxonomic rank of the microorganism, such as `"species"` or `"genus"`
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#' - `ref`\cr Author(s) and year of related scientific publication. This contains only the *first surname* and year of the *latest* authors, e.g. "Wallis *et al.* 2006 *emend.* Smith and Jones 2018" becomes "Smith *et al.*, 2018". This field is directly retrieved from the source specified in the column `source`. Moreover, accents were removed to comply with CRAN that only allows ASCII characters, e.g. "V`r "\u00e1\u0148ov\u00e1"`" becomes "Vanova".
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#' - `lpsn`\cr Identifier ('Record number') of the List of Prokaryotic names with Standing in Nomenclature (LPSN). This will be the first/highest LPSN identifier to keep one identifier per row. For example, *Acetobacter ascendens* has LPSN Record number 7864 and 11011. Only the first is available in the `microorganisms` data set.
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#' - `oxygen_tolerance` \cr Oxygen tolerance, either `r vector_or(microorganisms$oxygen_tolerance)`. These data were retrieved from BacDive (see *Source*). Items that contain "likely" are missing from BacDive and were extrapolated from other species within the same genus to guess the oxygen tolerance. Currently `r round(length(microorganisms$oxygen_tolerance[which(!is.na(microorganisms$oxygen_tolerance))]) / nrow(microorganisms[which(microorganisms$kingdom == "Bacteria"), ]) * 100, 1)`% of all `r format_included_data_number(nrow(microorganisms[which(microorganisms$kingdom == "Bacteria"), ]))` bacteria in the data set contain an oxygen tolerance.
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#' - `lpsn_parent`\cr LPSN identifier of the parent taxon
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#' - `lpsn_renamed_to`\cr LPSN identifier of the currently valid taxon
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#' - `gbif`\cr Identifier ('taxonID') of the Global Biodiversity Information Facility (GBIF)
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#' * Grimont *et al.* (2007). Antigenic Formulae of the Salmonella Serovars, 9th Edition. WHO Collaborating Centre for Reference and Research on *Salmonella* (WHOCC-SALM).
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#'
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#' * Bartlett *et al.* (2022). **A comprehensive list of bacterial pathogens infecting humans** *Microbiology* 168:001269; \doi{10.1099/mic.0.001269}
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#'
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#' * Reimer *et al.* (2022). ***BacDive* in 2022: the knowledge base for standardized bacterial and archaeal data.** *Nucleic Acids Res.* 2022 Jan 7;50(D1):D741-D746; \doi{10.1093/nar/gkab961}
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#' @seealso [as.mo()], [mo_property()], [microorganisms.codes], [intrinsic_resistant]
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#' @examples
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#' microorganisms
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