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add oxygen tolerance

This commit is contained in:
2023-05-11 21:56:27 +02:00
parent bf08d136a0
commit 91fa73dedf
28 changed files with 52310 additions and 52203 deletions

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@ -47,7 +47,7 @@ antibiogram(
\item{antibiotics}{vector of any antibiotic name or code (will be evaluated with \code{\link[=as.ab]{as.ab()}}, column name of \code{x}, or (any combinations of) \link[=antibiotic_class_selectors]{antibiotic selectors} such as \code{\link[=aminoglycosides]{aminoglycosides()}} or \code{\link[=carbapenems]{carbapenems()}}. For combination antibiograms, this can also be set to values separated with \code{"+"}, such as "TZP+TOB" or "cipro + genta", given that columns resembling such antibiotics exist in \code{x}. See \emph{Examples}.}
\item{mo_transform}{a character to transform microorganism input - must be "name", "shortname", "gramstain", or one of the column names of the \link{microorganisms} data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed". Can also be \code{NULL} to not transform the input.}
\item{mo_transform}{a character to transform microorganism input - must be "name", "shortname", "gramstain", or one of the column names of the \link{microorganisms} data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed". Can also be \code{NULL} to not transform the input.}
\item{ab_transform}{a character to transform antibiotic input - must be one of the column names of the \link{antibiotics} data set: "ab", "cid", "name", "group", "atc", "atc_group1", "atc_group2", "abbreviations", "synonyms", "oral_ddd", "oral_units", "iv_ddd", "iv_units", or "loinc". Can also be \code{NULL} to not transform the input.}

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@ -121,13 +121,14 @@ The coercion rules consider the prevalence of microorganisms in humans, which is
\item Berends MS \emph{et al.} (2022). \strong{AMR: An R Package for Working with Antimicrobial Resistance Data}. \emph{Journal of Statistical Software}, 104(3), 1-31; \doi{10.18637/jss.v104.i03}
\item Becker K \emph{et al.} (2014). \strong{Coagulase-Negative Staphylococci.} \emph{Clin Microbiol Rev.} 27(4): 870-926; \doi{10.1128/CMR.00109-13}
\item Becker K \emph{et al.} (2019). \strong{Implications of identifying the recently defined members of the \emph{S. aureus} complex, \emph{S. argenteus} and \emph{S. schweitzeri}: A position paper of members of the ESCMID Study Group for staphylococci and Staphylococcal Diseases (ESGS).} \emph{Clin Microbiol Infect}; \doi{10.1016/j.cmi.2019.02.028}
\item Becker K \emph{et al.} (2020). \strong{Emergence of coagulase-negative staphylococci} \emph{Expert Rev Anti Infect Ther.} 18(4):349-366; \doi{10.1080/14787210.2020.1730813}
\item Lancefield RC (1933). \strong{A serological differentiation of human and other groups of hemolytic streptococci}. \emph{J Exp Med.} 57(4): 571-95; \doi{10.1084/jem.57.4.571}
\item Berends MS \emph{et al.} (2022). \strong{Trends in Occurrence and Phenotypic Resistance of Coagulase-Negative Staphylococci (CoNS) Found in Human Blood in the Northern Netherlands between 2013 and 2019} \emph{Microorganisms} 10(9), 1801; \doi{10.3390/microorganisms10091801}
\item Becker K \emph{et al.} (2020). \strong{Emergence of coagulase-negative staphylococci.} \emph{Expert Rev Anti Infect Ther.} 18(4):349-366; \doi{10.1080/14787210.2020.1730813}
\item Lancefield RC (1933). \strong{A serological differentiation of human and other groups of hemolytic streptococci.} \emph{J Exp Med.} 57(4): 571-95; \doi{10.1084/jem.57.4.571}
\item Berends MS \emph{et al.} (2022). \strong{Trends in Occurrence and Phenotypic Resistance of Coagulase-Negative Staphylococci (CoNS) Found in Human Blood in the Northern Netherlands between 2013 and 2019/} \emph{Micro.rganisms} 10(9), 1801; \doi{10.3390/microorganisms10091801}
\item Parte, AC \emph{et al.} (2020). \strong{List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ.} International Journal of Systematic and Evolutionary Microbiology, 70, 5607-5612; \doi{10.1099/ijsem.0.004332}. Accessed from \url{https://lpsn.dsmz.de} on 11 December, 2022.
\item GBIF Secretariat (2022). GBIF Backbone Taxonomy. Checklist dataset \doi{10.15468/39omei}. Accessed from \url{https://www.gbif.org} on 11 December, 2022.
\item Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS). US Edition of SNOMED CT from 1 September 2020. Value Set Name 'Microoganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: \url{https://phinvads.cdc.gov}
\item Bartlett A \emph{et al.} (2022). \strong{A comprehensive list of bacterial pathogens infecting humans} \emph{Microbiology} 168:001269; \doi{10.1099/mic.0.001269}
\item Reimer \emph{et al.} (2022). \strong{\emph{BacDive} in 2022: the knowledge base for standardized bacterial and archaeal data.} \emph{Nucleic Acids Res.} 2022 Jan 7;50(D1):D741-D746; \doi{10.1093/nar/gkab961}
}
}

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@ -60,7 +60,7 @@ eucast_rules(df, rules = "custom", custom_rules = x, info = FALSE)
\subsection{Using taxonomic properties in rules}{
There is one exception in columns used for the rules: all column names of the \link{microorganisms} data set can also be used, but do not have to exist in the data set. These column names are: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", and "snomed". Thus, this next example will work as well, despite the fact that the \code{df} data set does not contain a column \code{genus}:
There is one exception in columns used for the rules: all column names of the \link{microorganisms} data set can also be used, but do not have to exist in the data set. These column names are: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", and "snomed". Thus, this next example will work as well, despite the fact that the \code{df} data set does not contain a column \code{genus}:
\if{html}{\out{<div class="sourceCode r">}}\preformatted{y <- custom_eucast_rules(TZP == "S" & genus == "Klebsiella" ~ aminopenicillins == "S",
TZP == "R" & genus == "Klebsiella" ~ aminopenicillins == "R")

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@ -5,7 +5,7 @@
\alias{microorganisms}
\title{Data Set with 52 151 Microorganisms}
\format{
A \link[tibble:tibble]{tibble} with 52 151 observations and 22 variables:
A \link[tibble:tibble]{tibble} with 52 151 observations and 23 variables:
\itemize{
\item \code{mo}\cr ID of microorganism as used by this package
\item \code{fullname}\cr Full name, like \code{"Escherichia coli"}. For the taxonomic ranks genus, species and subspecies, this is the 'pasted' text of genus, species, and subspecies. For all taxonomic ranks higher than genus, this is the name of the taxon.
@ -14,6 +14,7 @@ A \link[tibble:tibble]{tibble} with 52 151 observations and 22 variables:
\item \code{rank}\cr Text of the taxonomic rank of the microorganism, such as \code{"species"} or \code{"genus"}
\item \code{ref}\cr Author(s) and year of related scientific publication. This contains only the \emph{first surname} and year of the \emph{latest} authors, e.g. "Wallis \emph{et al.} 2006 \emph{emend.} Smith and Jones 2018" becomes "Smith \emph{et al.}, 2018". This field is directly retrieved from the source specified in the column \code{source}. Moreover, accents were removed to comply with CRAN that only allows ASCII characters, e.g. "Váňová" becomes "Vanova".
\item \code{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, \emph{Acetobacter ascendens} has LPSN Record number 7864 and 11011. Only the first is available in the \code{microorganisms} data set.
\item \code{oxygen_tolerance} \cr Oxygen tolerance, either "aerobe", "anaerobe", "anaerobe/microaerophile", "facultative anaerobe", "likely facultative anaerobe", or "microaerophile". These data were retrieved from BacDive (see \emph{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 73.4\% of all ~36 000 bacteria in the data set contain an oxygen tolerance.
\item \code{lpsn_parent}\cr LPSN identifier of the parent taxon
\item \code{lpsn_renamed_to}\cr LPSN identifier of the currently valid taxon
\item \code{gbif}\cr Identifier ('taxonID') of the Global Biodiversity Information Facility (GBIF)
@ -31,6 +32,7 @@ A \link[tibble:tibble]{tibble} with 52 151 observations and 22 variables:
\item Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS). US Edition of SNOMED CT from 1 September 2020. Value Set Name 'Microoganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: \url{https://phinvads.cdc.gov}
\item Grimont \emph{et al.} (2007). Antigenic Formulae of the Salmonella Serovars, 9th Edition. WHO Collaborating Centre for Reference and Research on \emph{Salmonella} (WHOCC-SALM).
\item Bartlett \emph{et al.} (2022). \strong{A comprehensive list of bacterial pathogens infecting humans} \emph{Microbiology} 168:001269; \doi{10.1099/mic.0.001269}
\item Reimer \emph{et al.} (2022). \strong{\emph{BacDive} in 2022: the knowledge base for standardized bacterial and archaeal data.} \emph{Nucleic Acids Res.} 2022 Jan 7;50(D1):D741-D746; \doi{10.1093/nar/gkab961}
}
}
\usage{

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@ -22,6 +22,8 @@
\alias{mo_is_gram_positive}
\alias{mo_is_yeast}
\alias{mo_is_intrinsic_resistant}
\alias{mo_oxygen_tolerance}
\alias{mo_is_anaerobic}
\alias{mo_snomed}
\alias{mo_ref}
\alias{mo_authors}
@ -177,6 +179,20 @@ mo_is_intrinsic_resistant(
...
)
mo_oxygen_tolerance(
x,
language = get_AMR_locale(),
keep_synonyms = getOption("AMR_keep_synonyms", FALSE),
...
)
mo_is_anaerobic(
x,
language = get_AMR_locale(),
keep_synonyms = getOption("AMR_keep_synonyms", FALSE),
...
)
mo_snomed(
x,
language = get_AMR_locale(),
@ -278,7 +294,7 @@ mo_property(
\item{open}{browse the URL using \code{\link[utils:browseURL]{browseURL()}}}
\item{property}{one of the column names of the \link{microorganisms} data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed", or must be \code{"shortname"}}
\item{property}{one of the column names of the \link{microorganisms} data set: "mo", "fullname", "status", "kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies", "rank", "ref", "oxygen_tolerance", "source", "lpsn", "lpsn_parent", "lpsn_renamed_to", "gbif", "gbif_parent", "gbif_renamed_to", "prevalence", or "snomed", or must be \code{"shortname"}}
}
\value{
\itemize{
@ -313,6 +329,8 @@ Determination of yeasts (\code{\link[=mo_is_yeast]{mo_is_yeast()}}) will be base
Determination of intrinsic resistance (\code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}}) will be based on the \link{intrinsic_resistant} data set, which is based on \href{https://www.eucast.org/expert_rules_and_expected_phenotypes/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.3} (2021). The \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} function can be vectorised over both argument \code{x} (input for microorganisms) and \code{ab} (input for antibiotics).
Determination of bacterial oxygen tolerance (\code{\link[=mo_oxygen_tolerance]{mo_oxygen_tolerance()}}) will be based on BacDive, see \emph{Source}. The function \code{\link[=mo_is_anaerobic]{mo_is_anaerobic()}} only returns \code{TRUE} if the oxygen tolerance is \code{"anaerobe"}, indicting an obligate anaerobic species or genus. It always returns \code{FALSE} for species outside the taxonomic kingdom of Bacteria.
The function \code{\link[=mo_url]{mo_url()}} will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.
SNOMED codes (\code{\link[=mo_snomed]{mo_snomed()}}) are from the version of 1 July, 2021. See \emph{Source} and the \link{microorganisms} data set for more info.
@ -332,13 +350,14 @@ This function uses \code{\link[=as.mo]{as.mo()}} internally, which uses an advan
\item Berends MS \emph{et al.} (2022). \strong{AMR: An R Package for Working with Antimicrobial Resistance Data}. \emph{Journal of Statistical Software}, 104(3), 1-31; \doi{10.18637/jss.v104.i03}
\item Becker K \emph{et al.} (2014). \strong{Coagulase-Negative Staphylococci.} \emph{Clin Microbiol Rev.} 27(4): 870-926; \doi{10.1128/CMR.00109-13}
\item Becker K \emph{et al.} (2019). \strong{Implications of identifying the recently defined members of the \emph{S. aureus} complex, \emph{S. argenteus} and \emph{S. schweitzeri}: A position paper of members of the ESCMID Study Group for staphylococci and Staphylococcal Diseases (ESGS).} \emph{Clin Microbiol Infect}; \doi{10.1016/j.cmi.2019.02.028}
\item Becker K \emph{et al.} (2020). \strong{Emergence of coagulase-negative staphylococci} \emph{Expert Rev Anti Infect Ther.} 18(4):349-366; \doi{10.1080/14787210.2020.1730813}
\item Lancefield RC (1933). \strong{A serological differentiation of human and other groups of hemolytic streptococci}. \emph{J Exp Med.} 57(4): 571-95; \doi{10.1084/jem.57.4.571}
\item Berends MS \emph{et al.} (2022). \strong{Trends in Occurrence and Phenotypic Resistance of Coagulase-Negative Staphylococci (CoNS) Found in Human Blood in the Northern Netherlands between 2013 and 2019} \emph{Microorganisms} 10(9), 1801; \doi{10.3390/microorganisms10091801}
\item Becker K \emph{et al.} (2020). \strong{Emergence of coagulase-negative staphylococci.} \emph{Expert Rev Anti Infect Ther.} 18(4):349-366; \doi{10.1080/14787210.2020.1730813}
\item Lancefield RC (1933). \strong{A serological differentiation of human and other groups of hemolytic streptococci.} \emph{J Exp Med.} 57(4): 571-95; \doi{10.1084/jem.57.4.571}
\item Berends MS \emph{et al.} (2022). \strong{Trends in Occurrence and Phenotypic Resistance of Coagulase-Negative Staphylococci (CoNS) Found in Human Blood in the Northern Netherlands between 2013 and 2019/} \emph{Micro.rganisms} 10(9), 1801; \doi{10.3390/microorganisms10091801}
\item Parte, AC \emph{et al.} (2020). \strong{List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ.} International Journal of Systematic and Evolutionary Microbiology, 70, 5607-5612; \doi{10.1099/ijsem.0.004332}. Accessed from \url{https://lpsn.dsmz.de} on 11 December, 2022.
\item GBIF Secretariat (2022). GBIF Backbone Taxonomy. Checklist dataset \doi{10.15468/39omei}. Accessed from \url{https://www.gbif.org} on 11 December, 2022.
\item Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS). US Edition of SNOMED CT from 1 September 2020. Value Set Name 'Microoganism', OID 2.16.840.1.114222.4.11.1009 (v12). URL: \url{https://phinvads.cdc.gov}
\item Bartlett A \emph{et al.} (2022). \strong{A comprehensive list of bacterial pathogens infecting humans} \emph{Microbiology} 168:001269; \doi{10.1099/mic.0.001269}
\item Reimer \emph{et al.} (2022). \strong{\emph{BacDive} in 2022: the knowledge base for standardized bacterial and archaeal data.} \emph{Nucleic Acids Res.} 2022 Jan 7;50(D1):D741-D746; \doi{10.1093/nar/gkab961}
}
}