documentation

.github/prehooks/pre-commit

@@ -35,8 +35,8 @@ echo "Running pre-commit hook..."
 if command -v Rscript > /dev/null; then
   if [ "$(Rscript -e 'cat(all(c('"'pkgload'"', '"'devtools'"', '"'dplyr'"') %in% rownames(installed.packages())))')" = "TRUE" ]; then
     Rscript -e "source('data-raw/_pre_commit_hook.R')"
-    currentpkg=`Rscript -e "cat(pkgload::pkg_name())"`
+    currentpkg=$(Rscript -e "cat(pkgload::pkg_name())")
-    echo "-> Adding all files in 'data-raw' to this commit"
+    echo "-> Adding files in 'data-raw' and 'man' to this commit"
     git add data-raw/*
     git add man/*
     git add R/sysdata.rda
@@ -57,18 +57,18 @@ echo "Updating semantic versioning and date..."
 
 # get tags from remote, and remove tags not on remote:
 git fetch origin --prune --prune-tags --quiet
-currenttagfull=`git describe --tags --abbrev=0`
+currenttagfull=$(git describe --tags --abbrev=0)
-currenttag=`git describe --tags --abbrev=0 | sed 's/v//'`
+currenttag=$(git describe --tags --abbrev=0 | sed 's/v//')
 # assume main branch to be 'main' or 'master', pick the right name:
-defaultbranch=`git branch | cut -c 3- | grep -E '^master$|^main$'`
+defaultbranch=$(git branch | cut -c 3- | grep -E '^master$|^main$')
 if [ "$currenttag" = "" ]; then
   # there is no tag, so set tag to 0.0.1 and commit index to current count
   currenttag="0.0.1"
-  currentcommit=`git rev-list --count ${defaultbranch}`
+  currentcommit=$(git rev-list --count ${defaultbranch})
   echo "- no git tags found, create one in format 'v(x).(y).(z)' - curently ${currentcommit} previous commits in ${defaultbranch}"
 else
   # there is a tag, so base version number on that
-  currentcommit=`git rev-list --count ${currenttagfull}..${defaultbranch}`
+  currentcommit=$(git rev-list --count ${currenttagfull}..${defaultbranch})
   if (( "$currentcommit" == 0 )); then
     # tag is new, so this must become the version number
     currentversion="$currenttag"

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: AMR
-Version: 1.8.2.9085
+Version: 1.8.2.9086
 Date: 2023-01-06
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 1.8.2.9085
+# AMR 1.8.2.9086
 
 *(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*
 

R/aa_helper_functions.R

@@ -229,7 +229,7 @@ search_type_in_df <- function(x, type, info = TRUE) {
       # take first 'mo' column
       found <- colnames(x)[vapply(FUN.VALUE = logical(1), x, is.mo)]
     } else if ("mo" %in% colnames_formatted &&
-      suppressWarnings(all(x$mo %in% c(NA, AMR::microorganisms$mo)))) {
+      suppressWarnings(all(x$mo %in% c(NA, AMR_env$MO_lookup$mo)))) {
       found <- "mo"
     } else if (any(colnames_formatted %like_case% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$")) {
       found <- sort(colnames(x)[colnames_formatted %like_case% "^(mo|microorganism|organism|bacteria|ba[ck]terie)s?$"])

R/eucast_rules.R

@@ -1116,7 +1116,7 @@ edit_rsi <- function(x,
       error = function(e) {
         txt_error()
         stop(paste0(
-          "In row(s) ", paste(rows[1:min(length(rows), 10)], collapse = ","),
+          "In row(s) ", paste(rows[seq_len(min(length(rows), 10))], collapse = ","),
           ifelse(length(rows) > 10, "...", ""),
           " while writing value '", to,
           "' to column(s) `", paste(cols, collapse = "`, `"),

R/join_microorganisms.R

@@ -165,10 +165,11 @@ join_microorganisms <- function(type, x, by, suffix, ...) {
     # otherwise use poorman, see R/aa_helper_pm_functions.R
     join_fn <- get(paste0("pm_", type), envir = asNamespace("AMR"))
   }
+  MO_df <- AMR_env$MO_lookup[, colnames(AMR::microorganisms), drop = FALSE]
   if (type %like% "full|left|right|inner") {
-    joined <- join_fn(x = x, y = AMR::microorganisms, by = by, suffix = suffix, ...)
+    joined <- join_fn(x = x, y = MO_df, by = by, suffix = suffix, ...)
   } else {
-    joined <- join_fn(x = x, y = AMR::microorganisms, by = by, ...)
+    joined <- join_fn(x = x, y = MO_df, by = by, ...)
   }
 
   if ("join.mo" %in% colnames(joined)) {

R/mo_matching_score.R

@@ -30,7 +30,7 @@
 #' Calculate the Matching Score for Microorganisms
 #'
 #' This algorithm is used by [as.mo()] and all the [`mo_*`][mo_property()] functions to determine the most probable match of taxonomic records based on user input.
-#' @author Dr. Matthijs Berends
+#' @author Dr. Matthijs Berends, 2018
 #' @param x Any user input value(s)
 #' @param n A full taxonomic name, that exists in [`microorganisms$fullname`][microorganisms]
 #' @note This algorithm was originally described in: Berends MS *et al.* (2022). **AMR: An R Package for Working with Antimicrobial Resistance Data**. *Journal of Statistical Software*, 104(3), 1-31; \doi{10.18637/jss.v104.i03}.
@@ -43,7 +43,7 @@
 #'
 #' where:
 #'
-#' * \ifelse{html}{\out{<i>x</i> is the user input;}}{\eqn{x} is the user input;}
+#' * \eqn{x} is the user input;
 #' * \ifelse{html}{\out{<i>n</i> is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
 #' * \ifelse{html}{\out{<i>l<sub>n</sub></i> is the length of <i>n</i>;}}{l_n is the length of \eqn{n};}
 #' * \ifelse{html}{\out{<i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a> (counting any insertion as 1, and any deletion or substitution as 2) that is needed to change <i>x</i> into <i>n</i>;}}{lev is the 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};}

R/mo_property.R

@@ -36,12 +36,13 @@
 #' @param ... other arguments passed on to [as.mo()], such as 'minimum_matching_score', 'ignore_pattern', and 'remove_from_input'
 #' @param ab any (vector of) text that can be coerced to a valid antibiotic drug code with [as.ab()]
 #' @param open browse the URL using [`browseURL()`][utils::browseURL()]
-#' @details All functions will, at default, keep old taxonomic properties. Please refer to this example, knowing that *Escherichia blattae* was renamed to *Shimwellia blattae* in 2010:
+#' @details All functions will, at default, **not** keep old taxonomic properties, as synonyms are automatically replaced with the current taxonomy. Take for example *Escherichia blattae*, which was renamed to *Shimwellia blattae* in 2010:
-#' - `mo_name("Escherichia blattae")` will return `"Shimwellia blattae"` (with a note about the renaming)
+#' - `mo_genus("Escherichia blattae")` will return `"Shemwellia"` (with a note about the renaming)
-#' - `mo_ref("Escherichia blattae", keep_synonyms = TRUE)` will return `"Burgess et al., 1973"` (without a note)
+#' - `mo_genus("Escherichia blattae", keep_synonyms = TRUE)` will return `"Escherichia"` (with a warning that the name is outdated)
-#' - `mo_ref("Shimwellia blattae", keep_synonyms = FALSE)` will return `"Priest et al., 2010"` (without a note)
+#' - `mo_ref("Escherichia blattae")` will return `"Priest et al., 2010"` (with a note)
+#' - `mo_ref("Escherichia blattae", keep_synonyms = TRUE)` will return `"Burgess et al., 1973"` (with a warning)
 #'
-#' The short name - [mo_shortname()] - almost always returns the first character of the genus and the full species, like `"E. coli"`. Exceptions are abbreviations of staphylococci (such as *"CoNS"*, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as *"GBS"*, Group B Streptococci). Please bear in mind that e.g. *E. coli* could mean *Escherichia coli* (kingdom of Bacteria) as well as *Entamoeba coli* (kingdom of Protozoa). Returning to the full name will be done using [as.mo()] internally, giving priority to bacteria and human pathogens, i.e. `"E. coli"` will be considered *Escherichia coli*. In other words, `mo_fullname(mo_shortname("Entamoeba coli"))` returns `"Escherichia coli"`.
+#' The short name ([mo_shortname()]) returns the first character of the genus and the full species, such as `"E. coli"`, for species and subspecies. Exceptions are abbreviations of staphylococci (such as *"CoNS"*, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as *"GBS"*, Group B Streptococci). Please bear in mind that e.g. *E. coli* could mean *Escherichia coli* (kingdom of Bacteria) as well as *Entamoeba coli* (kingdom of Protozoa). Returning to the full name will be done using [as.mo()] internally, giving priority to bacteria and human pathogens, i.e. `"E. coli"` will be considered *Escherichia coli*. In other words, `mo_fullname(mo_shortname("Entamoeba coli"))` returns `"Escherichia coli"`.
 #'
 #' Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions [mo_kingdom()] and [mo_domain()] return the exact same results.
 #'
@@ -60,7 +61,8 @@
 #' SNOMED codes ([mo_snomed()]) are from the version of `r documentation_date(TAXONOMY_VERSION$SNOMED$accessed_date)`. See *Source* and the [microorganisms] data set for more info.
 #'
 #' Old taxonomic names (so-called 'synonyms') can be retrieved with [mo_synonyms()], the current taxonomic name can be retrieved with [mo_current()]. Both functions return full names.
-#' @inheritSection mo_matching_score Matching Score for Microorganisms
+#' @section Matching Score for Microorganisms:
+#' This function uses [as.mo()] internally, which uses an advanced algorithm to translate arbitrary user input to valid taxonomy using a so-called matching score. You can read about this public algorithm on the [MO matching score page][mo_matching_score()].
 #' @inheritSection as.mo Source
 #' @rdname mo_property
 #' @name mo_property

R/mo_source.R

@@ -288,9 +288,9 @@ check_validity_mo_source <- function(x, refer_to_name = "`reference_df`", stop_o
       return(FALSE)
     }
   }
-  if (!all(x$mo %in% c("", AMR::microorganisms$mo, AMR::microorganisms$fullname), na.rm = TRUE)) {
+  if (!all(x$mo %in% c("", AMR_env$MO_lookup$mo, AMR_env$MO_lookup$fullname), na.rm = TRUE)) {
     if (stop_on_error == TRUE) {
-      invalid <- x[which(!x$mo %in% c("", AMR::microorganisms$mo, AMR::microorganisms$fullname)), , drop = FALSE]
+      invalid <- x[which(!x$mo %in% c("", AMR_env$MO_lookup$mo, AMR_env$MO_lookup$fullname)), , drop = FALSE]
       if (nrow(invalid) > 1) {
         plural <- "s"
       } else {

man/as.mo.Rd

@@ -135,7 +135,7 @@ With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\li
 
 where:
 \itemize{
-\item \ifelse{html}{\out{<i>x</i> is the user input;}}{\eqn{x} is the user input;}
+\item \eqn{x} is the user input;
 \item \ifelse{html}{\out{<i>n</i> is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
 \item \ifelse{html}{\out{<i>l<sub>n</sub></i> is the length of <i>n</i>;}}{l_n is the length of \eqn{n};}
 \item \ifelse{html}{\out{<i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a> (counting any insertion as 1, and any deletion or substitution as 2) that is needed to change <i>x</i> into <i>n</i>;}}{lev is the 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};}

man/mo_matching_score.Rd

@@ -27,7 +27,7 @@ With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\li
 
 where:
 \itemize{
-\item \ifelse{html}{\out{<i>x</i> is the user input;}}{\eqn{x} is the user input;}
+\item \eqn{x} is the user input;
 \item \ifelse{html}{\out{<i>n</i> is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
 \item \ifelse{html}{\out{<i>l<sub>n</sub></i> is the length of <i>n</i>;}}{l_n is the length of \eqn{n};}
 \item \ifelse{html}{\out{<i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a> (counting any insertion as 1, and any deletion or substitution as 2) that is needed to change <i>x</i> into <i>n</i>;}}{lev is the 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};}
@@ -70,5 +70,5 @@ mo_matching_score(
 )
 }
 \author{
-Dr. Matthijs Berends
+Dr. Matthijs Berends, 2018
 }

man/mo_property.Rd

@@ -294,14 +294,15 @@ mo_property(
 Use these functions to return a specific property of a microorganism based on the latest accepted taxonomy. All input values will be evaluated internally with \code{\link[=as.mo]{as.mo()}}, which makes it possible to use microbial abbreviations, codes and names as input. See \emph{Examples}.
 }
 \details{
-All functions will, at default, keep old taxonomic properties. Please refer to this example, knowing that \emph{Escherichia blattae} was renamed to \emph{Shimwellia blattae} in 2010:
+All functions will, at default, \strong{not} keep old taxonomic properties, as synonyms are automatically replaced with the current taxonomy. Take for example \emph{Escherichia blattae}, which was renamed to \emph{Shimwellia blattae} in 2010:
 \itemize{
-\item \code{mo_name("Escherichia blattae")} will return \code{"Shimwellia blattae"} (with a note about the renaming)
+\item \code{mo_genus("Escherichia blattae")} will return \code{"Shemwellia"} (with a note about the renaming)
-\item \code{mo_ref("Escherichia blattae", keep_synonyms = TRUE)} will return \code{"Burgess et al., 1973"} (without a note)
+\item \code{mo_genus("Escherichia blattae", keep_synonyms = TRUE)} will return \code{"Escherichia"} (with a warning that the name is outdated)
-\item \code{mo_ref("Shimwellia blattae", keep_synonyms = FALSE)} will return \code{"Priest et al., 2010"} (without a note)
+\item \code{mo_ref("Escherichia blattae")} will return \code{"Priest et al., 2010"} (with a note)
+\item \code{mo_ref("Escherichia blattae", keep_synonyms = TRUE)} will return \code{"Burgess et al., 1973"} (with a warning)
 }
 
-The short name - \code{\link[=mo_shortname]{mo_shortname()}} - almost always returns the first character of the genus and the full species, like \code{"E. coli"}. Exceptions are abbreviations of staphylococci (such as \emph{"CoNS"}, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as \emph{"GBS"}, Group B Streptococci). Please bear in mind that e.g. \emph{E. coli} could mean \emph{Escherichia coli} (kingdom of Bacteria) as well as \emph{Entamoeba coli} (kingdom of Protozoa). Returning to the full name will be done using \code{\link[=as.mo]{as.mo()}} internally, giving priority to bacteria and human pathogens, i.e. \code{"E. coli"} will be considered \emph{Escherichia coli}. In other words, \code{mo_fullname(mo_shortname("Entamoeba coli"))} returns \code{"Escherichia coli"}.
+The short name (\code{\link[=mo_shortname]{mo_shortname()}}) returns the first character of the genus and the full species, such as \code{"E. coli"}, for species and subspecies. Exceptions are abbreviations of staphylococci (such as \emph{"CoNS"}, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as \emph{"GBS"}, Group B Streptococci). Please bear in mind that e.g. \emph{E. coli} could mean \emph{Escherichia coli} (kingdom of Bacteria) as well as \emph{Entamoeba coli} (kingdom of Protozoa). Returning to the full name will be done using \code{\link[=as.mo]{as.mo()}} internally, giving priority to bacteria and human pathogens, i.e. \code{"E. coli"} will be considered \emph{Escherichia coli}. In other words, \code{mo_fullname(mo_shortname("Entamoeba coli"))} returns \code{"Escherichia coli"}.
 
 Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions \code{\link[=mo_kingdom]{mo_kingdom()}} and \code{\link[=mo_domain]{mo_domain()}} return the exact same results.
 
@@ -323,38 +324,7 @@ Old taxonomic names (so-called 'synonyms') can be retrieved with \code{\link[=mo
 }
 \section{Matching Score for Microorganisms}{
 
-With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
+This function uses \code{\link[=as.mo]{as.mo()}} internally, which uses an advanced algorithm to translate arbitrary user input to valid taxonomy using a so-called matching score. You can read about this public algorithm on the \link[=mo_matching_score]{MO matching score page}.
-
-\ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}}
-
-where:
-\itemize{
-\item \ifelse{html}{\out{<i>x</i> is the user input;}}{\eqn{x} is the user input;}
-\item \ifelse{html}{\out{<i>n</i> is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
-\item \ifelse{html}{\out{<i>l<sub>n</sub></i> is the length of <i>n</i>;}}{l_n is the length of \eqn{n};}
-\item \ifelse{html}{\out{<i>lev</i> is the <a href="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance function</a> (counting any insertion as 1, and any deletion or substitution as 2) that is needed to change <i>x</i> into <i>n</i>;}}{lev is the 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 \ifelse{html}{\out{<i>p<sub>n</sub></i> is the human pathogenic prevalence group of <i>n</i>, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
-\item \ifelse{html}{\out{<i>k<sub>n</sub></i> is the taxonomic kingdom of <i>n</i>, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
-}
-
-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:
-\itemize{
-\item \strong{Established}, if a taxonomic species has infected at least three persons in three or more references. These records have \code{prevalence = 1.0} in the \link{microorganisms} data set;
-\item \strong{Putative}, if a taxonomic species has fewer than three known cases. These records have \code{prevalence = 1.25} in the \link{microorganisms} data set.
-}
-
-Furthermore,
-\itemize{
-\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{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{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.
 }
 
 \section{Source}{