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new species groups, updated clinical breakpoints
This commit is contained in:
@ -51,7 +51,7 @@ Useful links:
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}
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\author{
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\strong{Maintainer}: Matthijs S. Berends \email{m.berends@certe.nl} (\href{https://orcid.org/0000-0001-7620-1800}{ORCID})
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\strong{Maintainer}: Matthijs S. Berends \email{m.s.berends@umcg.nl} (\href{https://orcid.org/0000-0001-7620-1800}{ORCID})
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Authors:
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\itemize{
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@ -147,7 +147,7 @@ where:
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\item \eqn{l_n} is the length of \eqn{n};
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\item \eqn{lev} is the \href{https://en.wikipedia.org/wiki/Levenshtein_distance}{Levenshtein distance function} (counting any insertion as 1, and any deletion or substitution as 2) that is needed to change \eqn{x} into \eqn{n};
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\item \eqn{p_n} is the human pathogenic prevalence group of \eqn{n}, as described below;
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\item \eqn{k_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
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\item \eqn{k_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 1.25, Protozoa = 1.5, Archaea = 2, others = 3.
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}
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The grouping into human pathogenic prevalence \eqn{p} is based on recent work from Bartlett \emph{et al.} (2022, \doi{10.1099/mic.0.001269}) who extensively studied medical-scientific literature to categorise all bacterial species into these groups:
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@ -161,13 +161,13 @@ Furthermore,
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\item Any genus present in the \strong{established} list also has \code{prevalence = 1.0} in the \link{microorganisms} data set;
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\item Any other genus present in the \strong{putative} list has \code{prevalence = 1.25} in the \link{microorganisms} data set;
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\item Any other species or subspecies of which the genus is present in the two aforementioned groups, has \code{prevalence = 1.5} in the \link{microorganisms} data set;
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\item Any \emph{non-bacterial} genus, species or subspecies of which the genus is present in the following list, has \code{prevalence = 1.5} in the \link{microorganisms} data set: \emph{Absidia}, \emph{Acanthamoeba}, \emph{Acremonium}, \emph{Aedes}, \emph{Alternaria}, \emph{Amoeba}, \emph{Ancylostoma}, \emph{Angiostrongylus}, \emph{Anisakis}, \emph{Anopheles}, \emph{Apophysomyces}, \emph{Aspergillus}, \emph{Aureobasidium}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Blastomyces}, \emph{Candida}, \emph{Capillaria}, \emph{Chaetomium}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Contracaecum}, \emph{Cordylobia}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Demodex}, \emph{Dermatobia}, \emph{Dientamoeba}, \emph{Diphyllobothrium}, \emph{Dirofilaria}, \emph{Echinostoma}, \emph{Entamoeba}, \emph{Enterobius}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Fasciola}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Giardia}, \emph{Haloarcula}, \emph{Halobacterium}, \emph{Halococcus}, \emph{Hendersonula}, \emph{Heterophyes}, \emph{Histomonas}, \emph{Histoplasma}, \emph{Hymenolepis}, \emph{Hypomyces}, \emph{Hysterothylacium}, \emph{Leishmania}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Metagonimus}, \emph{Meyerozyma}, \emph{Microsporidium}, \emph{Microsporum}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Necator}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oesophagostomum}, \emph{Oidiodendron}, \emph{Opisthorchis}, \emph{Pediculus}, \emph{Penicillium}, \emph{Phlebotomus}, \emph{Phoma}, \emph{Pichia}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Pneumocystis}, \emph{Pseudallescheria}, \emph{Pseudoterranova}, \emph{Pulex}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Saccharomyces}, \emph{Sarcoptes}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium}, \emph{Spirometra}, \emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Strongyloides}, \emph{Syngamus}, \emph{Taenia}, \emph{Talaromyces}, \emph{Toxocara}, \emph{Trichinella}, \emph{Trichobilharzia}, \emph{Trichoderma}, \emph{Trichomonas}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Trichostrongylus}, \emph{Trichuris}, \emph{Tritirachium}, \emph{Trombicula}, \emph{Trypanosoma}, \emph{Tunga}, or \emph{Wuchereria};
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\item Any \emph{non-bacterial} genus, species or subspecies of which the genus is present in the following list, has \code{prevalence = 1.25} in the \link{microorganisms} data set: \emph{Absidia}, \emph{Acanthamoeba}, \emph{Acremonium}, \emph{Aedes}, \emph{Alternaria}, \emph{Amoeba}, \emph{Ancylostoma}, \emph{Angiostrongylus}, \emph{Anisakis}, \emph{Anopheles}, \emph{Apophysomyces}, \emph{Aspergillus}, \emph{Aureobasidium}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Blastomyces}, \emph{Candida}, \emph{Capillaria}, \emph{Chaetomium}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Contracaecum}, \emph{Cordylobia}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Demodex}, \emph{Dermatobia}, \emph{Dientamoeba}, \emph{Diphyllobothrium}, \emph{Dirofilaria}, \emph{Echinostoma}, \emph{Entamoeba}, \emph{Enterobius}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Fasciola}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Giardia}, \emph{Haloarcula}, \emph{Halobacterium}, \emph{Halococcus}, \emph{Hendersonula}, \emph{Heterophyes}, \emph{Histomonas}, \emph{Histoplasma}, \emph{Hymenolepis}, \emph{Hypomyces}, \emph{Hysterothylacium}, \emph{Leishmania}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Metagonimus}, \emph{Meyerozyma}, \emph{Microsporidium}, \emph{Microsporum}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Necator}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oesophagostomum}, \emph{Oidiodendron}, \emph{Opisthorchis}, \emph{Pediculus}, \emph{Penicillium}, \emph{Phlebotomus}, \emph{Phoma}, \emph{Pichia}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Pneumocystis}, \emph{Pseudallescheria}, \emph{Pseudoterranova}, \emph{Pulex}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Saccharomyces}, \emph{Sarcoptes}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium}, \emph{Spirometra}, \emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Strongyloides}, \emph{Syngamus}, \emph{Taenia}, \emph{Talaromyces}, \emph{Toxocara}, \emph{Trichinella}, \emph{Trichobilharzia}, \emph{Trichoderma}, \emph{Trichomonas}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Trichostrongylus}, \emph{Trichuris}, \emph{Tritirachium}, \emph{Trombicula}, \emph{Trypanosoma}, \emph{Tunga}, or \emph{Wuchereria};
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\item All other records have \code{prevalence = 2.0} in the \link{microorganisms} data set.
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}
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When calculating the matching score, all characters in \eqn{x} and \eqn{n} are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.
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All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.688}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.159}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
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All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.688}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.381}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
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}
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\section{Reference Data Publicly Available}{
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@ -43,7 +43,7 @@ is_sir_eligible(x, threshold = 0.05)
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reference_data = AMR::clinical_breakpoints,
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include_screening = getOption("AMR_include_screening", FALSE),
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include_PKPD = getOption("AMR_include_PKPD", TRUE),
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breakpoint_type = getOption("AMR_breakpoint_type", FALSE),
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breakpoint_type = getOption("AMR_breakpoint_type", "human"),
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...
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)
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@ -57,7 +57,7 @@ is_sir_eligible(x, threshold = 0.05)
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reference_data = AMR::clinical_breakpoints,
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include_screening = getOption("AMR_include_screening", FALSE),
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include_PKPD = getOption("AMR_include_PKPD", TRUE),
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breakpoint_type = getOption("AMR_breakpoint_type", FALSE),
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breakpoint_type = getOption("AMR_breakpoint_type", "human"),
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...
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)
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@ -72,7 +72,7 @@ is_sir_eligible(x, threshold = 0.05)
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reference_data = AMR::clinical_breakpoints,
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include_screening = getOption("AMR_include_screening", FALSE),
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include_PKPD = getOption("AMR_include_PKPD", TRUE),
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breakpoint_type = getOption("AMR_breakpoint_type", FALSE)
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breakpoint_type = getOption("AMR_breakpoint_type", "human")
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)
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sir_interpretation_history(clean = FALSE)
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@ -102,7 +102,7 @@ sir_interpretation_history(clean = FALSE)
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\item{include_PKPD}{a \link{logical} to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is \code{TRUE}. Can also be set with the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_include_PKPD}}.}
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\item{breakpoint_type}{the type of breakpoints to use, either "". ECOFF stands for Epidemiological Cut-Off values. The default is \code{"human"}, which can also be set with the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_breakpoint_type}}.}
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\item{breakpoint_type}{the type of breakpoints to use, either "ECOFF", "animal", or "human". ECOFF stands for Epidemiological Cut-Off values. The default is \code{"human"}, which can also be set with the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_breakpoint_type}}.}
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\item{col_mo}{column name of the names or codes of the microorganisms (see \code{\link[=as.mo]{as.mo()}}) - the default is the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.}
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@ -114,11 +114,12 @@ Ordered \link{factor} with new class \code{sir}
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\description{
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Interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI, or clean up existing SIR values. This transforms the input to a new class \code{\link{sir}}, which is an ordered \link{factor} with levels \verb{S < I < R}.
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Currently available \strong{breakpoint guidelines} are EUCAST 2011-2023 and CLSI 2011-2023, and available \strong{breakpoint types} are "".
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Currently available \strong{breakpoint guidelines} are EUCAST 2011-2023 and CLSI 2011-2023, and available \strong{breakpoint types} are "ECOFF", "animal", and "human".
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All breakpoints used for interpretation are publicly available in the \link{clinical_breakpoints} data set.
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}
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\details{
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\emph{Note: The clinical breakpoints in this package were validated through and imported from \href{https://whonet.org}{WHONET} and the public use of this \code{AMR} package has been endorsed by CLSI and EUCAST, please see \link{clinical_breakpoints} for more information.}
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\subsection{How it Works}{
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The \code{\link[=as.sir]{as.sir()}} function works in four ways:
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@ -170,7 +171,7 @@ After using \code{\link[=as.sir]{as.sir()}}, you can use the \code{\link[=eucast
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\subsection{Machine-Readable Clinical Breakpoints}{
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The repository of this package \href{https://github.com/msberends/AMR/blob/main/data-raw/clinical_breakpoints.txt}{contains a machine-readable version} of all guidelines. This is a CSV file consisting of 42 599 rows and 12 columns. This file is machine-readable, since it contains one row for every unique combination of the test method (MIC or disk diffusion), the antimicrobial drug and the microorganism. \strong{This allows for easy implementation of these rules in laboratory information systems (LIS)}. Note that it only contains interpretation guidelines for humans - interpretation guidelines from CLSI for animals were removed.
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The repository of this package \href{https://github.com/msberends/AMR/blob/main/data-raw/clinical_breakpoints.txt}{contains a machine-readable version} of all guidelines. This is a CSV file consisting of 28 454 rows and 12 columns. This file is machine-readable, since it contains one row for every unique combination of the test method (MIC or disk diffusion), the antimicrobial drug and the microorganism. \strong{This allows for easy implementation of these rules in laboratory information systems (LIS)}. Note that it only contains interpretation guidelines for humans - interpretation guidelines from CLSI for animals were removed.
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}
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\subsection{Other}{
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@ -5,19 +5,19 @@
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\alias{clinical_breakpoints}
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\title{Data Set with Clinical Breakpoints for SIR Interpretation}
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\format{
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A \link[tibble:tibble]{tibble} with 42 599 observations and 12 variables:
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A \link[tibble:tibble]{tibble} with 28 454 observations and 12 variables:
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\itemize{
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\item \code{guideline}\cr Name of the guideline
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\item \code{method}\cr Either "DISK" or "MIC"
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\item \code{site}\cr Body site, e.g. "Oral" or "Respiratory"
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\item \code{type}\cr Breakpoint type, either "ECOFF", "animal", or "human"
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\item \code{method}\cr Testing method, either "DISK" or "MIC"
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\item \code{site}\cr Body site for which the breakpoint must be applied, e.g. "Oral" or "Respiratory"
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\item \code{mo}\cr Microbial ID, see \code{\link[=as.mo]{as.mo()}}
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\item \code{rank_index}\cr Taxonomic rank index of \code{mo} from 1 (subspecies/infraspecies) to 5 (unknown microorganism)
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\item \code{ab}\cr Antibiotic ID, see \code{\link[=as.ab]{as.ab()}}
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\item \code{ab}\cr Antibiotic code as used by this package, EARS-Net and WHONET, see \code{\link[=as.ab]{as.ab()}}
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\item \code{ref_tbl}\cr Info about where the guideline rule can be found
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\item \code{disk_dose}\cr Dose of the used disk diffusion method
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\item \code{breakpoint_S}\cr Lowest MIC value or highest number of millimetres that leads to "S"
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\item \code{breakpoint_R}\cr Highest MIC value or lowest number of millimetres that leads to "R"
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\item \code{ecoff}\cr Epidemiological cut-off (ECOFF) value, used in antimicrobial susceptibility testing to differentiate between wild-type and non-wild-type strains of bacteria or fungi (use \code{\link[=as.sir]{as.sir(..., ecoff = TRUE)}} to interpret raw data using ECOFF values)
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\item \code{uti}\cr A \link{logical} value (\code{TRUE}/\code{FALSE}) to indicate whether the rule applies to a urinary tract infection (UTI)
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}
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}
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@ -28,11 +28,29 @@ clinical_breakpoints
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Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. Currently implemented guidelines are EUCAST (2011-2023) and CLSI (2011-2023). Use \code{\link[=as.sir]{as.sir()}} to transform MICs or disks measurements to SIR values.
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}
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\details{
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Clinical breakpoints are validated through \href{https://whonet.org}{WHONET}, a free desktop Windows application developed and supported by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance. More can be read on \href{https://whonet.org}{their website}.
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\subsection{Different types of breakpoints}{
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Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit \href{https://msberends.github.io/AMR/articles/datasets.html}{our website for the download links}. The actual files are of course available on \href{https://github.com/msberends/AMR/tree/main/data-raw}{our GitHub repository}.
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Supported types of breakpoints are ECOFF, animal, and human. ECOFF (Epidemiological cut-off) values are used in antimicrobial susceptibility testing to differentiate between wild-type and non-wild-type strains of bacteria or fungi.
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They \strong{allow for machine reading EUCAST and CLSI guidelines}, which is almost impossible with the MS Excel and PDF files distributed by EUCAST and CLSI.
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The default is \code{"human"}, which can also be set with the \link[=AMR-options]{package option} \code{\link[=AMR-options]{AMR_breakpoint_type}}. Use \code{\link[=as.sir]{as.sir(..., breakpoint_type = ...)}} to interpret raw data using a specific breakpoint type, e.g. \code{as.sir(..., breakpoint_type = "ECOFF")} to use ECOFFs.
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}
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\subsection{Imported from WHONET}{
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Clinical breakpoints in this package were validated through and imported from \href{https://whonet.org}{WHONET}, a free desktop Windows application developed and supported by the WHO Collaborating Centre for Surveillance of Antimicrobial Resistance. More can be read on \href{https://whonet.org}{their website}. The developers of WHONET and this \code{AMR} package have been in contact about sharing their work. We highly appreciate their development on the WHONET software.
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}
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\subsection{Response from CLSI and EUCAST}{
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The CEO of CLSI and the chairman of EUCAST have endorsed the work and public use of this \code{AMR} package in June 2023, when future development of distributing clinical breakpoints was discussed in a meeting between CLSI, EUCAST, the WHO, and developers of WHONET and the \code{AMR} package.
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}
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\subsection{Download}{
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Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit \href{https://msberends.github.io/AMR/articles/datasets.html}{our website for the download links}. The actual files are of course available on \href{https://github.com/msberends/AMR/tree/main/data-raw}{our GitHub repository}. They allow for machine reading EUCAST and CLSI guidelines, which is almost impossible with the MS Excel and PDF files distributed by EUCAST and CLSI, though initiatives have started to overcome these burdens.
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\strong{NOTE:} this \code{AMR} package (and the WHONET software as well) contains internal methods to apply the guidelines, which is rather complex. For example, some breakpoints must be applied on certain species groups (which are in case of this package available through the \link{microorganisms.groups} data set). It is important that this is considered when using the breakpoints for own use.
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}
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}
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\examples{
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clinical_breakpoints
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@ -27,14 +27,13 @@ eucast_rules(
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verbose = FALSE,
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version_breakpoints = 12,
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version_expertrules = 3.3,
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version_resistant_phenotypes = 1.2,
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ampc_cephalosporin_resistance = NA,
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only_sir_columns = FALSE,
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custom_rules = NULL,
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...
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)
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eucast_dosage(ab, administration = "iv", version_breakpoints = 13)
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eucast_dosage(ab, administration = "iv", version_breakpoints = 12)
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}
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\arguments{
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\item{x}{a data set with antibiotic columns, such as \code{amox}, \code{AMX} and \code{AMC}}
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@ -47,12 +46,10 @@ eucast_dosage(ab, administration = "iv", version_breakpoints = 13)
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\item{verbose}{a \link{logical} to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way. Using Verbose mode takes a lot more time.}
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\item{version_breakpoints}{the version number to use for the EUCAST Clinical Breakpoints guideline. Can be "13.0", "12.0", "11.0", or "10.0".}
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\item{version_breakpoints}{the version number to use for the EUCAST Clinical Breakpoints guideline. Can be "12.0", "11.0", or "10.0".}
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\item{version_expertrules}{the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be "3.3", "3.2", or "3.1".}
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\item{version_resistant_phenotypes}{the version number to use for the EUCAST Expected Resistant Phenotypes. Can be "1.2".}
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\item{ampc_cephalosporin_resistance}{a \link{character} value that should be applied to cefotaxime, ceftriaxone and ceftazidime for AmpC de-repressed cephalosporin-resistant mutants - the default is \code{NA}. Currently only works when \code{version_expertrules} is \code{3.2} and higher; these version of '\emph{EUCAST Expert Rules on Enterobacterales}' state that results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these three drugs. A value of \code{NA} (the default) for this argument will remove results for these three drugs, while e.g. a value of \code{"R"} will make the results for these drugs resistant. Use \code{NULL} or \code{FALSE} to not alter results for these three drugs of AmpC de-repressed cephalosporin-resistant mutants. Using \code{TRUE} is equal to using \code{"R"}. \cr For \emph{EUCAST Expert Rules} v3.2, this rule applies to: \emph{Citrobacter braakii}, \emph{Citrobacter freundii}, \emph{Citrobacter gillenii}, \emph{Citrobacter murliniae}, \emph{Citrobacter rodenticum}, \emph{Citrobacter sedlakii}, \emph{Citrobacter werkmanii}, \emph{Citrobacter youngae}, \emph{Enterobacter}, \emph{Hafnia alvei}, \emph{Klebsiella aerogenes}, \emph{Morganella morganii}, \emph{Providencia}, and \emph{Serratia}.}
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\item{only_sir_columns}{a \link{logical} to indicate whether only antibiotic columns must be detected that were transformed to class \code{sir} (see \code{\link[=as.sir]{as.sir()}}) on beforehand (default is \code{FALSE})}
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@ -3,9 +3,9 @@
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\docType{data}
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\name{microorganisms}
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\alias{microorganisms}
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\title{Data Set with 52 158 Microorganisms}
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\title{Data Set with 52 169 Microorganisms}
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\format{
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||||
A \link[tibble:tibble]{tibble} with 52 158 observations and 23 variables:
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A \link[tibble:tibble]{tibble} with 52 169 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.
|
||||
@ -64,8 +64,7 @@ Included taxonomic data are:
|
||||
For convenience, some entries were added manually:
|
||||
\itemize{
|
||||
\item ~1 500 entries of \emph{Salmonella}, such as the city-like serovars and groups A to H
|
||||
\item 15 entries of \emph{Streptococcus}, such as the beta-haemolytic groups A to K, viridans, and milleri
|
||||
\item 2 entries of \emph{Staphylococcus} (coagulase-negative (CoNS) and coagulase-positive (CoPS))
|
||||
\item 34 species groups (such as the beta-haemolytic \emph{Streptococcus} groups A to K, coagulase-negative \emph{Staphylococcus} (CoNS), \emph{Mycobacterium tuberculosis} complex, etc.), of which the group compositions are stored in the \link{microorganisms.groups} data set
|
||||
\item 1 entry of \emph{Blastocystis} (\emph{B. hominis}), although it officially does not exist (Noel \emph{et al.} 2005, PMID 15634993)
|
||||
\item 1 entry of \emph{Moraxella} (\emph{M. catarrhalis}), which was formally named \emph{Branhamella catarrhalis} (Catlin, 1970) though this change was never accepted within the field of clinical microbiology
|
||||
\item 8 other 'undefined' entries (unknown, unknown Gram-negatives, unknown Gram-positives, unknown yeast, unknown fungus, and unknown anaerobic Gram-pos/Gram-neg bacteria)
|
||||
@ -91,6 +90,6 @@ The List of Prokaryotic names with Standing in Nomenclature (LPSN) provides comp
|
||||
microorganisms
|
||||
}
|
||||
\seealso{
|
||||
\code{\link[=as.mo]{as.mo()}}, \code{\link[=mo_property]{mo_property()}}, \link{microorganisms.codes}, \link{intrinsic_resistant}
|
||||
\code{\link[=as.mo]{as.mo()}}, \code{\link[=mo_property]{mo_property()}}, \link{microorganisms.groups}, \link{microorganisms.codes}, \link{intrinsic_resistant}
|
||||
}
|
||||
\keyword{datasets}
|
||||
|
||||
@ -3,9 +3,9 @@
|
||||
\docType{data}
|
||||
\name{microorganisms.codes}
|
||||
\alias{microorganisms.codes}
|
||||
\title{Data Set with 4 946 Common Microorganism Codes}
|
||||
\title{Data Set with 4 957 Common Microorganism Codes}
|
||||
\format{
|
||||
A \link[tibble:tibble]{tibble} with 4 946 observations and 2 variables:
|
||||
A \link[tibble:tibble]{tibble} with 4 957 observations and 2 variables:
|
||||
\itemize{
|
||||
\item \code{code}\cr Commonly used code of a microorganism
|
||||
\item \code{mo}\cr ID of the microorganism in the \link{microorganisms} data set
|
||||
@ -15,7 +15,7 @@ A \link[tibble:tibble]{tibble} with 4 946 observations and 2 variables:
|
||||
microorganisms.codes
|
||||
}
|
||||
\description{
|
||||
A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with \code{\link[=set_mo_source]{set_mo_source()}}. They will all be searched when using \code{\link[=as.mo]{as.mo()}} and consequently all the \code{\link[=mo_property]{mo_*}} functions.
|
||||
A data set containing commonly used codes for microorganisms, from laboratory systems and \href{https://whonet.org}{WHONET}. Define your own with \code{\link[=set_mo_source]{set_mo_source()}}. They will all be searched when using \code{\link[=as.mo]{as.mo()}} and consequently all the \code{\link[=mo_property]{mo_*}} functions.
|
||||
}
|
||||
\details{
|
||||
Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit \href{https://msberends.github.io/AMR/articles/datasets.html}{our website for the download links}. The actual files are of course available on \href{https://github.com/msberends/AMR/tree/main/data-raw}{our GitHub repository}.
|
||||
|
||||
34
man/microorganisms.groups.Rd
Normal file
34
man/microorganisms.groups.Rd
Normal file
@ -0,0 +1,34 @@
|
||||
% Generated by roxygen2: do not edit by hand
|
||||
% Please edit documentation in R/data.R
|
||||
\docType{data}
|
||||
\name{microorganisms.groups}
|
||||
\alias{microorganisms.groups}
|
||||
\title{Data Set with 444 Microorganisms In Species Groups}
|
||||
\format{
|
||||
A \link[tibble:tibble]{tibble} with 444 observations and 4 variables:
|
||||
\itemize{
|
||||
\item \code{mo_group}\cr ID of the species group / microbiological complex
|
||||
\item \code{mo}\cr ID of the microorganism belonging in the species group / microbiological complex
|
||||
\item \code{mo_group_name}\cr Name of the species group / microbiological complex, as retrieved with \code{\link[=mo_name]{mo_name()}}
|
||||
\item \code{mo_name}\cr Name of the microorganism belonging in the species group / microbiological complex, as retrieved with \code{\link[=mo_name]{mo_name()}}
|
||||
}
|
||||
}
|
||||
\usage{
|
||||
microorganisms.groups
|
||||
}
|
||||
\description{
|
||||
A data set containing species groups and microbiological complexes, which are used in \link[=clinial_breakpoints]{the clinical breakpoints table}.
|
||||
}
|
||||
\details{
|
||||
Like all data sets in this package, this data set is publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit \href{https://msberends.github.io/AMR/articles/datasets.html}{our website for the download links}. The actual files are of course available on \href{https://github.com/msberends/AMR/tree/main/data-raw}{our GitHub repository}.
|
||||
}
|
||||
\examples{
|
||||
microorganisms.groups
|
||||
|
||||
# these are all species in the Bacteroides fragilis group, as per WHONET:
|
||||
microorganisms.groups[microorganisms.groups$mo_group == "B_BCTRD_FRGL-C", ]
|
||||
}
|
||||
\seealso{
|
||||
\code{\link[=as.mo]{as.mo()}} \link{microorganisms}
|
||||
}
|
||||
\keyword{datasets}
|
||||
@ -34,7 +34,7 @@ where:
|
||||
\item \eqn{l_n} is the length of \eqn{n};
|
||||
\item \eqn{lev} is the \href{https://en.wikipedia.org/wiki/Levenshtein_distance}{Levenshtein distance function} (counting any insertion as 1, and any deletion or substitution as 2) that is needed to change \eqn{x} into \eqn{n};
|
||||
\item \eqn{p_n} is the human pathogenic prevalence group of \eqn{n}, as described below;
|
||||
\item \eqn{k_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
|
||||
\item \eqn{k_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 1.25, Protozoa = 1.5, Archaea = 2, others = 3.
|
||||
}
|
||||
|
||||
The grouping into human pathogenic prevalence \eqn{p} is based on recent work from Bartlett \emph{et al.} (2022, \doi{10.1099/mic.0.001269}) who extensively studied medical-scientific literature to categorise all bacterial species into these groups:
|
||||
@ -48,13 +48,13 @@ Furthermore,
|
||||
\item Any genus present in the \strong{established} list also has \code{prevalence = 1.0} in the \link{microorganisms} data set;
|
||||
\item Any other genus present in the \strong{putative} list has \code{prevalence = 1.25} in the \link{microorganisms} data set;
|
||||
\item Any other species or subspecies of which the genus is present in the two aforementioned groups, has \code{prevalence = 1.5} in the \link{microorganisms} data set;
|
||||
\item Any \emph{non-bacterial} genus, species or subspecies of which the genus is present in the following list, has \code{prevalence = 1.5} in the \link{microorganisms} data set: \emph{Absidia}, \emph{Acanthamoeba}, \emph{Acremonium}, \emph{Aedes}, \emph{Alternaria}, \emph{Amoeba}, \emph{Ancylostoma}, \emph{Angiostrongylus}, \emph{Anisakis}, \emph{Anopheles}, \emph{Apophysomyces}, \emph{Aspergillus}, \emph{Aureobasidium}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Blastomyces}, \emph{Candida}, \emph{Capillaria}, \emph{Chaetomium}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Contracaecum}, \emph{Cordylobia}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Demodex}, \emph{Dermatobia}, \emph{Dientamoeba}, \emph{Diphyllobothrium}, \emph{Dirofilaria}, \emph{Echinostoma}, \emph{Entamoeba}, \emph{Enterobius}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Fasciola}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Giardia}, \emph{Haloarcula}, \emph{Halobacterium}, \emph{Halococcus}, \emph{Hendersonula}, \emph{Heterophyes}, \emph{Histomonas}, \emph{Histoplasma}, \emph{Hymenolepis}, \emph{Hypomyces}, \emph{Hysterothylacium}, \emph{Leishmania}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Metagonimus}, \emph{Meyerozyma}, \emph{Microsporidium}, \emph{Microsporum}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Necator}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oesophagostomum}, \emph{Oidiodendron}, \emph{Opisthorchis}, \emph{Pediculus}, \emph{Penicillium}, \emph{Phlebotomus}, \emph{Phoma}, \emph{Pichia}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Pneumocystis}, \emph{Pseudallescheria}, \emph{Pseudoterranova}, \emph{Pulex}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Saccharomyces}, \emph{Sarcoptes}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium}, \emph{Spirometra}, \emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Strongyloides}, \emph{Syngamus}, \emph{Taenia}, \emph{Talaromyces}, \emph{Toxocara}, \emph{Trichinella}, \emph{Trichobilharzia}, \emph{Trichoderma}, \emph{Trichomonas}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Trichostrongylus}, \emph{Trichuris}, \emph{Tritirachium}, \emph{Trombicula}, \emph{Trypanosoma}, \emph{Tunga}, or \emph{Wuchereria};
|
||||
\item Any \emph{non-bacterial} genus, species or subspecies of which the genus is present in the following list, has \code{prevalence = 1.25} in the \link{microorganisms} data set: \emph{Absidia}, \emph{Acanthamoeba}, \emph{Acremonium}, \emph{Aedes}, \emph{Alternaria}, \emph{Amoeba}, \emph{Ancylostoma}, \emph{Angiostrongylus}, \emph{Anisakis}, \emph{Anopheles}, \emph{Apophysomyces}, \emph{Aspergillus}, \emph{Aureobasidium}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Blastomyces}, \emph{Candida}, \emph{Capillaria}, \emph{Chaetomium}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Contracaecum}, \emph{Cordylobia}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Demodex}, \emph{Dermatobia}, \emph{Dientamoeba}, \emph{Diphyllobothrium}, \emph{Dirofilaria}, \emph{Echinostoma}, \emph{Entamoeba}, \emph{Enterobius}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Fasciola}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Giardia}, \emph{Haloarcula}, \emph{Halobacterium}, \emph{Halococcus}, \emph{Hendersonula}, \emph{Heterophyes}, \emph{Histomonas}, \emph{Histoplasma}, \emph{Hymenolepis}, \emph{Hypomyces}, \emph{Hysterothylacium}, \emph{Leishmania}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Metagonimus}, \emph{Meyerozyma}, \emph{Microsporidium}, \emph{Microsporum}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Necator}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oesophagostomum}, \emph{Oidiodendron}, \emph{Opisthorchis}, \emph{Pediculus}, \emph{Penicillium}, \emph{Phlebotomus}, \emph{Phoma}, \emph{Pichia}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Pneumocystis}, \emph{Pseudallescheria}, \emph{Pseudoterranova}, \emph{Pulex}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Saccharomyces}, \emph{Sarcoptes}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium}, \emph{Spirometra}, \emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Strongyloides}, \emph{Syngamus}, \emph{Taenia}, \emph{Talaromyces}, \emph{Toxocara}, \emph{Trichinella}, \emph{Trichobilharzia}, \emph{Trichoderma}, \emph{Trichomonas}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Trichostrongylus}, \emph{Trichuris}, \emph{Tritirachium}, \emph{Trombicula}, \emph{Trypanosoma}, \emph{Tunga}, or \emph{Wuchereria};
|
||||
\item All other records have \code{prevalence = 2.0} in the \link{microorganisms} data set.
|
||||
}
|
||||
|
||||
When calculating the matching score, all characters in \eqn{x} and \eqn{n} are ignored that are other than A-Z, a-z, 0-9, spaces and parentheses.
|
||||
|
||||
All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.688}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.159}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
|
||||
All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., \code{"E. coli"} will return the microbial ID of \emph{Escherichia coli} (\eqn{m = 0.688}, a highly prevalent microorganism found in humans) and not \emph{Entamoeba coli} (\eqn{m = 0.381}, a less prevalent microorganism in humans), although the latter would alphabetically come first.
|
||||
}
|
||||
|
||||
\section{Reference Data Publicly Available}{
|
||||
|
||||
Reference in New Issue
Block a user