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(v0.7.1.9081) bug_drug fixes

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dr. M.S. (Matthijs) Berends 2019-09-23 13:53:50 +02:00
parent 66d405ff57
commit 64d9829030
26 changed files with 622 additions and 505 deletions
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4
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR
Version: 0.7.1.9080
Date: 2019-09-22
Version: 0.7.1.9081
Date: 2019-09-23
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

33
NEWS.md
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@ -1,5 +1,5 @@
# AMR 0.7.1.9080
<small>Last updated: 22-Sep-2019</small>
# AMR 0.7.1.9081
<small>Last updated: 23-Sep-2019</small>
### Breaking
* Determination of first isolates now **excludes** all 'unknown' microorganisms at default, i.e. microbial code `"UNKNOWN"`. They can be included with the new parameter `include_unknown`:
@ -25,17 +25,27 @@
* Function `freq()` has moved to a new package, [`clean`](https://github.com/msberends/clean) ([CRAN link](https://cran.r-project.org/package=clean)), since creating frequency tables actually does not fit the scope of this package. The `freq()` function still works, since it is re-exported from the `clean` package (which will be installed automatically upon updating this `AMR` package).
### New
* Function `bug_drug_combinations()` to quickly get a `data.frame` with the antimicrobial resistance of any bug-drug combination in a data set:
* Function `bug_drug_combinations()` to quickly get a `data.frame` with the antimicrobial resistance of any bug-drug combination in a data set. The columns with microorganism codes is guessed automatically and its input is transformed with `mo_shortname()` at default:
```r
x <- bug_drug_combinations(example_isolates)
x
# NOTE: Using column `mo` as input for `col_mo`.
#> ab mo S I R total
#> 1 AMC B_ESCHR_COLI 332 74 61 467
#> 2 AMC B_KLBSL_PNMN 49 3 6 58
#> 3 AMC B_PROTS_MRBL 28 7 1 36
#> 4 AMC B_PSDMN_AERG 0 0 30 30
#> 5 AMC B_STPHY_AURS 234 0 1 235
x[1:5, ]
#> ab mo S I R total
#> 1 AMC CoNS 178 0 132 310
#> 2 AMC E. coli 332 74 61 467
#> 3 AMC K. pneumoniae 49 3 6 58
#> 4 AMC P. aeruginosa 0 0 30 30
#> 5 AMC P. mirabilis 28 7 1 36
# change the transformation with the FUN argument to anything you like:
x <- bug_drug_combinations(example_isolates, FUN = mo_gramstain)
# NOTE: Using column `mo` as input for `col_mo`.
x[1:4, ]
#> ab mo S I R total
#> 1 AMC Gram-negative 469 89 174 732
#> 2 AMC Gram-positive 873 2 272 1147
#> 3 AMK Gram-negative 251 0 2 253
#> 4 AMK Gram-positive 0 0 100 100
```
You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R `format()` function:
```r
@ -82,7 +92,8 @@
* Added support for *Blastocystis*
* Added support for 5,000 new fungi
* Added support for unknown yeasts and fungi
* Changed most microorganism IDs to improve readability. **IMPORTANT:** Because of these changes, the microorganism IDs have been changed to a slightly different format. Old microorganism IDs are still supported, but support will be dropped in a future version. Use `as.mo()` on your old codes to transform them to the new format.
* Changed most microorganism IDs to improve readability. For example, the old code `B_ENTRC_FAE` could have been both *E. faecalis* and *E. faecium*. Its new code is `B_ENTRC_FCLS` and *E. faecium* has become `B_ENTRC_FACM`. Also, the Latin character æ (ae) is now preserved at the start of each genus and species abbreviation. For example, the old code for *Aerococcus urinae* was `B_ARCCC_NAE`. This is now `B_AERCC_URIN`.
**IMPORTANT:** Old microorganism IDs are still supported, but support will be dropped in a future version. Use `as.mo()` on your old codes to transform them to the new format. Using functions from the `mo_*` family (like `mo_name()` and `mo_gramstain()`) on old codes, will throw a warning.
* Renamed data set `septic_patients` to `example_isolates`
* Function `eucast_rules()`:
* Fixed a bug for *Yersinia pseudotuberculosis*

49
R/bug_drug_combinations.R
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@ -25,12 +25,16 @@
#' @inheritParams eucast_rules
#' @param combine_IR logical to indicate whether values R and I should be summed
#' @param add_ab_group logical to indicate where the group of the antimicrobials must be included as a first column
#' @param ... argumments passed on to \code{\link{mo_name}}
#' @param FUN the function to call on the \code{mo} column to transform the microorganism IDs, defaults to \code{\link{mo_shortname}}
#' @param ... argumments passed on to \code{FUN}
#' @inheritParams rsi_df
#' @inheritParams base::formatC
#' @importFrom dplyr rename
#' @importFrom tidyr spread
#' @importFrom clean freq
#' @details The function \code{format} calculates the resistance per bug-drug combination. Use \code{combine_IR = FALSE} (default) to test R vs. S+I and \code{combine_IR = TRUE} to test R+I vs. S.
#'
#' The language of the output can be overwritten with \code{options(AMR_locale)}, please see \link{translate}.
#' @export
#' @rdname bug_drug_combinations
#' @source \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
@ -40,8 +44,21 @@
#' x <- bug_drug_combinations(example_isolates)
#' x
#' format(x)
#'
#' # Use FUN to change to transformation of microorganism codes
#' x <- bug_drug_combinations(example_isolates,
#' FUN = mo_gramstain)
#'
#' x <- bug_drug_combinations(example_isolates,
#' FUN = function(x) ifelse(x == "B_ESCHR_COLI",
#' "E. coli",
#' "Others"))
#' }
bug_drug_combinations <- function(x, col_mo = NULL, minimum = 30) {
bug_drug_combinations <- function(x,
col_mo = NULL,
minimum = 30,
FUN = mo_shortname,
...) {
if (!is.data.frame(x)) {
stop("`x` must be a data frame.", call. = FALSE)
}
@ -56,7 +73,7 @@ bug_drug_combinations <- function(x, col_mo = NULL, minimum = 30) {
}
x <- x %>%
mutate(col_mo = x %>% pull(col_mo)) %>%
mutate(mo = x %>% pull(col_mo) %>% FUN(...)) %>%
filter(mo %in% (clean::freq(mo) %>%
filter(count >= minimum) %>%
pull(item))) %>%
@ -76,31 +93,37 @@ bug_drug_combinations <- function(x, col_mo = NULL, minimum = 30) {
#' @exportMethod format.bug_drug_combinations
#' @export
#' @rdname bug_drug_combinations
format.bug_drug_combinations <- function(x, combine_IR = FALSE, add_ab_group = TRUE, ...) {
format.bug_drug_combinations <- function(x,
combine_IR = FALSE,
add_ab_group = TRUE,
decimal.mark = getOption("OutDec"),
big.mark = ifelse(decimal.mark == ",", ".", ",")) {
if (combine_IR == FALSE) {
x$isolates <- x$R
} else {
x$isolates <- x$R + x$I
}
y <- x %>%
mutate(mo = mo_name(mo, ...),
txt = paste0(percent(isolates / total, force_zero = TRUE),
" (", trimws(format(isolates, big.mark = ",")), "/",
trimws(format(total, big.mark = ",")), ")")) %>%
mutate(txt = paste0(percent(isolates / total, force_zero = TRUE, decimal.mark = decimal.mark, big.mark = big.mark),
" (", trimws(format(isolates, big.mark = big.mark)), "/",
trimws(format(total, big.mark = big.mark)), ")")) %>%
select(ab, mo, txt) %>%
spread(mo, txt) %>%
mutate_all(~ifelse(is.na(.), "", .)) %>%
mutate(ab = paste0(ab_name(ab), " (", as.ab(ab), ", ", ab_atc(ab), ")"),
ab_group = ab_group(ab)) %>%
mutate(ab_group = ab_group(ab),
ab = paste0(ab_name(ab), " (", as.ab(ab), ", ", ab_atc(ab), ")")) %>%
select(ab_group, ab, everything()) %>%
arrange(ab_group, ab) %>%
mutate(ab_group = ifelse(ab_group != lag(ab_group) | is.na(lag(ab_group)), ab_group, ""))
if (add_ab_group == FALSE) {
y <- y %>% select(-ab_group)
y <- y %>% select(-ab_group) %>% rename("Antibiotic" = ab)
colnames(y)[1] <- translate_AMR(colnames(y)[1], language = get_locale(), only_unknown = FALSE)
} else {
y <- y %>% rename("Group" = ab_group,
"Antibiotic" = ab)
colnames(y)[1:2] <- translate_AMR(colnames(y)[1:2], language = get_locale(), only_unknown = FALSE)
}
y <- y %>% rename("Group" = ab_group,
"Antibiotic" = ab)
y
}

4
R/freq.R
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@ -42,8 +42,8 @@ freq.mo <- function(x, ...) {
decimal.mark = "."),
" (", percent(sum(grams == "Gram-positive", na.rm = TRUE) / length(grams), force_zero = TRUE, round = 2),
")"),
`Unique genera` = n_distinct(mo_genus(x_noNA, language = NULL)),
`Unique species` = n_distinct(paste(mo_genus(x_noNA, language = NULL),
`Nr of genera` = n_distinct(mo_genus(x_noNA, language = NULL)),
`Nr of species` = n_distinct(paste(mo_genus(x_noNA, language = NULL),
mo_species(x_noNA, language = NULL)))))
}

77
R/mo.R
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@ -65,59 +65,48 @@
#' Usually, any guess after the first try runs 80-95\% faster than the first try.
#'
# \emph{For now, learning only works per session. If R is closed or terminated, the algorithms reset. This might be resolved in a future version.}
#'
#' This resets with every update of this \code{AMR} package since results are saved to your local package library folder.
#'
#' \strong{Intelligent rules} \cr
#' This function uses intelligent rules to help getting fast and logical results. It tries to find matches in this order:
#' The \code{as.mo()} function uses several coercion rules for fast and logical results. It assesses the input matching criteria in the following order:
#' \itemize{
#' \item{Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations}
#' \item{Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones (see \emph{Microbial prevalence of pathogens in humans} below)}
#' \item{Taxonomic kingdom: it first searches in Bacteria, then Fungi, then Protozoa, then Archaea, then others}
#' \item{Breakdown of input values: from here it starts to breakdown input values to find possible matches}
#' \item{Human pathogenic prevalence: the function starts with more prevalent microorganisms, followed by less prevalent ones;}
#' \item{Taxonomic kingdom: the function starts with determining Bacteria, then Fungi, then Protozoa, then others;}
#' \item{Breakdown of input values to identify possible matches.}
#' }
#'
#' This will lead to the effect that e.g. \code{"E. coli"} (a highly prevalent microorganism found in humans) will return the microbial ID of \emph{Escherichia coli} and not \emph{Entamoeba coli} (a less prevalent microorganism in humans), although the latter would alphabetically come first. In addition, the \code{as.mo()} function can differentiate four levels of uncertainty to guess valid results:
#'
#' \itemize{
#' \item{Uncertainty level 0: no additional rules are applied;}
#' \item{Uncertainty level 1: allow previously accepted (but now invalid) taxonomic names and minor spelling errors;}
#' \item{Uncertainty level 2: allow all of level 1, strip values between brackets, inverse the words of the input, strip off text elements from the end keeping at least two elements;}
#' \item{Uncertainty level 3: allow all of level 1 and 2, strip off text elements from the end, allow any part of a taxonomic name.}
#' }
#'
#'
#' A couple of effects because of these rules:
#' \itemize{
#' \item{\code{"E. coli"} will return the ID of \emph{Escherichia coli} and not \emph{Entamoeba coli}, although the latter would alphabetically come first}
#' \item{\code{"H. influenzae"} will return the ID of \emph{Haemophilus influenzae} and not \emph{Haematobacter influenzae} for the same reason}
#' \item{Something like \code{"stau"} or \code{"S aur"} will return the ID of \emph{Staphylococcus aureus} and not \emph{Staphylococcus auricularis}}
#' }
#' This means that looking up human pathogenic microorganisms takes less time than looking up human non-pathogenic microorganisms.
#'
#' \strong{Uncertain results} \cr
#' The algorithm can additionally use three different levels of uncertainty to guess valid results. The default is \code{allow_uncertain = TRUE}, which is equal to uncertainty level 2. Using \code{allow_uncertain = FALSE} will skip all of these additional rules:
#' \itemize{
#' \item{(uncertainty level 1): It tries to look for only matching genera, previously accepted (but now invalid) taxonomic names and misspelled input}
#' \item{(uncertainty level 2): It removed parts between brackets, strips off words from the end one by one and re-evaluates the input with all previous rules}
#' \item{(uncertainty level 3): It strips off words from the start one by one and tries any part of the name}
#' }
#'
#' You can also use e.g. \code{as.mo(..., allow_uncertain = 1)} to only allow up to level 1 uncertainty.
#'
#' Examples:
#' This leads to e.g.:
#'
#' \itemize{
#' \item{\code{"Streptococcus group B (known as S. agalactiae)"}. The text between brackets will be removed and a warning will be thrown that the result \emph{Streptococcus group B} (\code{B_STRPT_GRPB}) needs review.}
#' \item{\code{"S. aureus - please mind: MRSA"}. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result \emph{Staphylococcus aureus} (\code{B_STPHY_AUR}) needs review.}
#' \item{\code{"Fluoroquinolone-resistant Neisseria gonorrhoeae"}. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result \emph{Neisseria gonorrhoeae} (\code{B_NESSR_GON}) needs review.}
#' \item{\code{"S. aureus - please mind: MRSA"}. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result \emph{Staphylococcus aureus} (\code{B_STPHY_AURS}) needs review.}
#' \item{\code{"Fluoroquinolone-resistant Neisseria gonorrhoeae"}. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result \emph{Neisseria gonorrhoeae} (\code{B_NESSR_GNRR}) needs review.}
#' }
#'
#' Use \code{mo_failures()} to get a vector with all values that could not be coerced to a valid value.
#'
#' Use \code{mo_uncertainties()} to get a data.frame with all values that were coerced to a valid value, but with uncertainty.
#'
#' Use \code{mo_renamed()} to get a data.frame with all values that could be coerced based on an old, previously accepted taxonomic name.
#' The level of uncertainty can be set using the argument \code{allow_uncertain}. The default is \code{allow_uncertain = TRUE}, which is equal to uncertainty level 2. Using \code{allow_uncertain = FALSE} is equal to uncertainty level 0 and will skip all rules. You can also use e.g. \code{as.mo(..., allow_uncertain = 1)} to only allow up to level 1 uncertainty.
#'
#' Use \code{mo_failures()} to get a vector with all values that could not be coerced to a valid value. \cr
#' Use \code{mo_uncertainties()} to get a \code{data.frame} with all values that were coerced to a valid value, but with uncertainty. \cr
#' Use \code{mo_renamed()} to get a \code{data.frame} with all values that could be coerced based on an old, previously accepted taxonomic name.
#'
#' \strong{Microbial prevalence of pathogens in humans} \cr
#' The intelligent rules take into account microbial prevalence of pathogens in humans. It uses three groups and all (sub)species are in only one group. These groups are:
#' \itemize{
#' \item{1 (most prevalent): class is Gammaproteobacteria \strong{or} genus is one of: \emph{Enterococcus}, \emph{Staphylococcus}, \emph{Streptococcus}.}
#' \item{2: phylum is one of: Proteobacteria, Firmicutes, Actinobacteria, Sarcomastigophora \strong{or} genus is one of: \emph{Aspergillus}, \emph{Bacteroides}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Chryseobacterium}, \emph{Cryptococcus}, \emph{Elisabethkingia}, \emph{Flavobacterium}, \emph{Fusobacterium}, \emph{Giardia}, \emph{Leptotrichia}, \emph{Mycoplasma}, \emph{Prevotella}, \emph{Rhodotorula}, \emph{Treponema}, \emph{Trichophyton}, \emph{Ureaplasma}.}
#' \item{3 (least prevalent): all others.}
#' }
#'
#' Group 1 contains all common Gram positives and Gram negatives, like all Enterobacteriaceae and e.g. \emph{Pseudomonas} and \emph{Legionella}.
#'
#' Group 2 contains probably less pathogenic microorganisms; all other members of phyla that were found in humans in the Northern Netherlands between 2001 and 2018.
#' The intelligent rules consider the prevalence of microorganisms in humans grouped into three groups, which is available as the \code{prevalence} columns in the \code{\link{microorganisms}} and \code{\link{microorganisms.old}} data sets. The grouping into prevalence groups is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence.
#'
#' Group 1 (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacteriales.
#'
#' Group 2 consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Aspergillus}, \emph{Bacteroides}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Chryseobacterium}, \emph{Cryptococcus}, \emph{Elisabethkingia}, \emph{Flavobacterium}, \emph{Fusobacterium}, \emph{Giardia}, \emph{Leptotrichia}, \emph{Mycoplasma}, \emph{Prevotella}, \emph{Rhodotorula}, \emph{Treponema}, \emph{Trichophyton} or \emph{Ureaplasma}.
#'
#' Group 3 (least prevalent microorganisms) consists of all other microorganisms.
#' @inheritSection catalogue_of_life Catalogue of Life
# (source as a section here, so it can be inherited by other man pages:)
#' @section Source:
@ -1722,7 +1711,7 @@ exec_as.mo <- function(x,
}
if (old_mo_warning == TRUE & property != "mo") {
warning("The input contained old microorganism IDs from previous versions of this package. Please use as.mo() on these old codes.\nSUPPORT FOR THIS WILL BE DROPPED IN A FUTURE VERSION.", call. = FALSE)
warning("The input contained old microorganism IDs from previous versions of this package.\nPlease use `as.mo()` on these old IDs to transform them to the new format.\nSUPPORT FOR THIS WILL BE DROPPED IN A FUTURE VERSION.", call. = FALSE)
}
x

BIN
R/sysdata.rda
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Binary file not shown.

2
data-raw/translations.tsv
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@ -52,6 +52,8 @@ nl biogroup biogroep FALSE FALSE
nl vegetative vegetatief FALSE FALSE
nl ([([ ]*?)group \\1groep FALSE FALSE
nl ([([ ]*?)Group \\1Groep FALSE FALSE
nl antibiotic antibioticum FALSE FALSE
nl Antibiotic Antibioticum FALSE FALSE
es Coagulase-negative Staphylococcus Staphylococcus coagulasa negativo FALSE FALSE
es Coagulase-positive Staphylococcus Staphylococcus coagulasa positivo FALSE FALSE
es Beta-haemolytic Streptococcus Streptococcus Beta-hemolítico FALSE FALSE

1 lang pattern replacement fixed ignore.case
52 nl vegetative vegetatief FALSE FALSE
53 nl ([([ ]*?)group \\1groep FALSE FALSE
54 nl ([([ ]*?)Group \\1Groep FALSE FALSE
55 nl antibiotic antibioticum FALSE FALSE
56 nl Antibiotic Antibioticum FALSE FALSE
57 es Coagulase-negative Staphylococcus Staphylococcus coagulasa negativo FALSE FALSE
58 es Coagulase-positive Staphylococcus Staphylococcus coagulasa positivo FALSE FALSE
59 es Beta-haemolytic Streptococcus Streptococcus Beta-hemolítico FALSE FALSE

2
docs/LICENSE-text.html
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@ -78,7 +78,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9080</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9081</span>
</span>
</div>

375
docs/articles/benchmarks.html
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@ -1,35 +1,75 @@
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<h1>Benchmarks</h1>
<h4 class="author">Matthijs S. Berends</h4>
<h4 class="date">22 September 2019</h4>
<h4 class="date">23 September 2019</h4>
<div class="hidden name"><code>benchmarks.Rmd</code></div>
@ -195,45 +237,45 @@
<p><small>Source: <a href="https://gitlab.com/msberends/AMR/blob/master/vignettes/benchmarks.Rmd" class="uri">https://gitlab.com/msberends/AMR/blob/master/vignettes/benchmarks.Rmd</a></small></p>
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://catalogueoflife.org">Catalogue of Life</a>. We created a function <code><a href="../reference/as.mo.html">as.mo()</a></code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the taxonomic tree of Catalogue of Life.</p>
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark()</a></code> runs different input expressions independently of each other and measures their time-to-result.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(microbenchmark)</a>
<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(AMR)</a></code></pre></div>
<p>One of the most important features of this package is the complete microbial taxonomic database, supplied by the <a href="http://catalogueoflife.org">Catalogue of Life</a>. We created a function <code>as.mo()</code> that transforms any user input value to a valid microbial ID by using intelligent rules combined with the taxonomic tree of Catalogue of Life.</p>
<p>Using the <code>microbenchmark</code> package, we can review the calculation performance of this function. Its function <code>microbenchmark()</code> runs different input expressions independently of each other and measures their time-to-result.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw">library</span>(microbenchmark)</a>
<a class="sourceLine" id="cb1-2" data-line-number="2"><span class="kw">library</span>(AMR)</a></code></pre></div>
<p>In the next test, we try to ‘coerce’ different input values for <em>Staphylococcus aureus</em>. The actual result is the same every time: it returns its microorganism code <code>B_STPHY_AURS</code> (<em>B</em> stands for <em>Bacteria</em>, the taxonomic kingdom).</p>
<p>But the calculation time differs a lot:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1">S.aureus &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(</a>
<a class="sourceLine" id="cb2-2" data-line-number="2"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"sau"</span>), <span class="co"># WHONET code</span></a>
<a class="sourceLine" id="cb2-3" data-line-number="3"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"stau"</span>),</a>
<a class="sourceLine" id="cb2-4" data-line-number="4"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"STAU"</span>),</a>
<a class="sourceLine" id="cb2-5" data-line-number="5"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"staaur"</span>),</a>
<a class="sourceLine" id="cb2-6" data-line-number="6"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"STAAUR"</span>),</a>
<a class="sourceLine" id="cb2-7" data-line-number="7"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. aureus"</span>),</a>
<a class="sourceLine" id="cb2-8" data-line-number="8"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S aureus"</span>),</a>
<a class="sourceLine" id="cb2-9" data-line-number="9"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Staphylococcus aureus"</span>), <span class="co"># official taxonomic name</span></a>
<a class="sourceLine" id="cb2-10" data-line-number="10"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Staphylococcus aureus (MRSA)"</span>), <span class="co"># additional text</span></a>
<a class="sourceLine" id="cb2-11" data-line-number="11"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Sthafilokkockus aaureuz"</span>), <span class="co"># incorrect spelling</span></a>
<a class="sourceLine" id="cb2-12" data-line-number="12"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"MRSA"</span>), <span class="co"># Methicillin Resistant S. aureus</span></a>
<a class="sourceLine" id="cb2-13" data-line-number="13"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"VISA"</span>), <span class="co"># Vancomycin Intermediate S. aureus</span></a>
<a class="sourceLine" id="cb2-14" data-line-number="14"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"VRSA"</span>), <span class="co"># Vancomycin Resistant S. aureus</span></a>
<a class="sourceLine" id="cb2-15" data-line-number="15"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="dv">22242419</span>), <span class="co"># Catalogue of Life ID</span></a>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1">S.aureus &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(</a>
<a class="sourceLine" id="cb2-2" data-line-number="2"> <span class="kw">as.mo</span>(<span class="st">&quot;sau&quot;</span>), <span class="co"># WHONET code</span></a>
<a class="sourceLine" id="cb2-3" data-line-number="3"> <span class="kw">as.mo</span>(<span class="st">&quot;stau&quot;</span>),</a>
<a class="sourceLine" id="cb2-4" data-line-number="4"> <span class="kw">as.mo</span>(<span class="st">&quot;STAU&quot;</span>),</a>
<a class="sourceLine" id="cb2-5" data-line-number="5"> <span class="kw">as.mo</span>(<span class="st">&quot;staaur&quot;</span>),</a>
<a class="sourceLine" id="cb2-6" data-line-number="6"> <span class="kw">as.mo</span>(<span class="st">&quot;STAAUR&quot;</span>),</a>
<a class="sourceLine" id="cb2-7" data-line-number="7"> <span class="kw">as.mo</span>(<span class="st">&quot;S. aureus&quot;</span>),</a>
<a class="sourceLine" id="cb2-8" data-line-number="8"> <span class="kw">as.mo</span>(<span class="st">&quot;S aureus&quot;</span>),</a>
<a class="sourceLine" id="cb2-9" data-line-number="9"> <span class="kw">as.mo</span>(<span class="st">&quot;Staphylococcus aureus&quot;</span>), <span class="co"># official taxonomic name</span></a>
<a class="sourceLine" id="cb2-10" data-line-number="10"> <span class="kw">as.mo</span>(<span class="st">&quot;Staphylococcus aureus (MRSA)&quot;</span>), <span class="co"># additional text</span></a>
<a class="sourceLine" id="cb2-11" data-line-number="11"> <span class="kw">as.mo</span>(<span class="st">&quot;Sthafilokkockus aaureuz&quot;</span>), <span class="co"># incorrect spelling</span></a>
<a class="sourceLine" id="cb2-12" data-line-number="12"> <span class="kw">as.mo</span>(<span class="st">&quot;MRSA&quot;</span>), <span class="co"># Methicillin Resistant S. aureus</span></a>
<a class="sourceLine" id="cb2-13" data-line-number="13"> <span class="kw">as.mo</span>(<span class="st">&quot;VISA&quot;</span>), <span class="co"># Vancomycin Intermediate S. aureus</span></a>
<a class="sourceLine" id="cb2-14" data-line-number="14"> <span class="kw">as.mo</span>(<span class="st">&quot;VRSA&quot;</span>), <span class="co"># Vancomycin Resistant S. aureus</span></a>
<a class="sourceLine" id="cb2-15" data-line-number="15"> <span class="kw">as.mo</span>(<span class="dv">22242419</span>), <span class="co"># Catalogue of Life ID</span></a>
<a class="sourceLine" id="cb2-16" data-line-number="16"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(S.aureus, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb2-17" data-line-number="17"><span class="kw">print</span>(S.aureus, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb2-18" data-line-number="18"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq max</span></a>
<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo("sau") 8.5 8.6 11 8.7 9.1 34</span></a>
<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo("stau") 31.0 31.0 39 31.0 56.0 58</span></a>
<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo("STAU") 31.0 34.0 39 34.0 35.0 60</span></a>
<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo("staaur") 8.5 8.7 15 8.9 9.6 67</span></a>
<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo("STAAUR") 8.6 8.7 14 9.0 9.9 36</span></a>
<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo("S. aureus") 23.0 23.0 40 25.0 26.0 180</span></a>
<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo("S aureus") 23.0 24.0 30 26.0 30.0 51</span></a>
<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo("Staphylococcus aureus") 28.0 28.0 31 29.0 29.0 51</span></a>
<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo("Staphylococcus aureus (MRSA)") 570.0 600.0 620 620.0 640.0 710</span></a>
<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo("Sthafilokkockus aaureuz") 280.0 310.0 320 320.0 330.0 340</span></a>
<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo("MRSA") 8.4 8.6 11 8.8 9.5 35</span></a>
<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo("VISA") 19.0 19.0 21 20.0 22.0 24</span></a>
<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo("VRSA") 19.0 19.0 27 23.0 41.0 46</span></a>
<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 18.0 18.0 22 21.0 22.0 43</span></a>
<a class="sourceLine" id="cb2-19" data-line-number="19"><span class="co"># expr min lq mean median uq max</span></a>
<a class="sourceLine" id="cb2-20" data-line-number="20"><span class="co"># as.mo(&quot;sau&quot;) 9.1 9.1 12.0 9.5 10.0 35</span></a>
<a class="sourceLine" id="cb2-21" data-line-number="21"><span class="co"># as.mo(&quot;stau&quot;) 31.0 32.0 37.0 33.0 34.0 58</span></a>
<a class="sourceLine" id="cb2-22" data-line-number="22"><span class="co"># as.mo(&quot;STAU&quot;) 31.0 32.0 34.0 34.0 35.0 37</span></a>
<a class="sourceLine" id="cb2-23" data-line-number="23"><span class="co"># as.mo(&quot;staaur&quot;) 8.6 9.1 9.7 9.8 10.0 11</span></a>
<a class="sourceLine" id="cb2-24" data-line-number="24"><span class="co"># as.mo(&quot;STAAUR&quot;) 8.7 8.9 17.0 9.4 12.0 57</span></a>
<a class="sourceLine" id="cb2-25" data-line-number="25"><span class="co"># as.mo(&quot;S. aureus&quot;) 23.0 24.0 34.0 26.0 46.0 54</span></a>
<a class="sourceLine" id="cb2-26" data-line-number="26"><span class="co"># as.mo(&quot;S aureus&quot;) 23.0 24.0 28.0 25.0 28.0 53</span></a>
<a class="sourceLine" id="cb2-27" data-line-number="27"><span class="co"># as.mo(&quot;Staphylococcus aureus&quot;) 29.0 29.0 31.0 30.0 32.0 34</span></a>
<a class="sourceLine" id="cb2-28" data-line-number="28"><span class="co"># as.mo(&quot;Staphylococcus aureus (MRSA)&quot;) 570.0 590.0 620.0 620.0 650.0 690</span></a>
<a class="sourceLine" id="cb2-29" data-line-number="29"><span class="co"># as.mo(&quot;Sthafilokkockus aaureuz&quot;) 310.0 320.0 350.0 330.0 340.0 480</span></a>
<a class="sourceLine" id="cb2-30" data-line-number="30"><span class="co"># as.mo(&quot;MRSA&quot;) 8.7 9.0 12.0 9.5 9.7 32</span></a>
<a class="sourceLine" id="cb2-31" data-line-number="31"><span class="co"># as.mo(&quot;VISA&quot;) 19.0 20.0 22.0 22.0 24.0 26</span></a>
<a class="sourceLine" id="cb2-32" data-line-number="32"><span class="co"># as.mo(&quot;VRSA&quot;) 19.0 20.0 28.0 22.0 43.0 48</span></a>
<a class="sourceLine" id="cb2-33" data-line-number="33"><span class="co"># as.mo(22242419) 18.0 19.0 25.0 22.0 23.0 41</span></a>
<a class="sourceLine" id="cb2-34" data-line-number="34"><span class="co"># neval</span></a>
<a class="sourceLine" id="cb2-35" data-line-number="35"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-36" data-line-number="36"><span class="co"># 10</span></a>
@ -249,137 +291,134 @@
<a class="sourceLine" id="cb2-46" data-line-number="46"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-47" data-line-number="47"><span class="co"># 10</span></a>
<a class="sourceLine" id="cb2-48" data-line-number="48"><span class="co"># 10</span></a></code></pre></div>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-5-1.png" width="562.5"></p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-5-1.png" width="562.5" /></p>
<p>In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second. The second input is the only one that has to be looked up thoroughly. All the others are known codes (the first one is a WHONET code) or common laboratory codes, or common full organism names like the last one. Full organism names are always preferred.</p>
<p>To achieve this speed, the <code>as.mo</code> function also takes into account the prevalence of human pathogenic microorganisms. The downside is of course that less prevalent microorganisms will be determined less fast. See this example for the ID of <em>Methanosarcina semesiae</em> (<code>B_MTHNSR_SEMS</code>), a bug probably never found before in humans:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">M.semesiae &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"metsem"</span>),</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"METSEM"</span>),</a>
<a class="sourceLine" id="cb3-3" data-line-number="3"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"M. semesiae"</span>),</a>
<a class="sourceLine" id="cb3-4" data-line-number="4"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"M. semesiae"</span>),</a>
<a class="sourceLine" id="cb3-5" data-line-number="5"> <span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"Methanosarcina semesiae"</span>),</a>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">M.semesiae &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(<span class="kw">as.mo</span>(<span class="st">&quot;metsem&quot;</span>),</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"> <span class="kw">as.mo</span>(<span class="st">&quot;METSEM&quot;</span>),</a>
<a class="sourceLine" id="cb3-3" data-line-number="3"> <span class="kw">as.mo</span>(<span class="st">&quot;M. semesiae&quot;</span>),</a>
<a class="sourceLine" id="cb3-4" data-line-number="4"> <span class="kw">as.mo</span>(<span class="st">&quot;M. semesiae&quot;</span>),</a>
<a class="sourceLine" id="cb3-5" data-line-number="5"> <span class="kw">as.mo</span>(<span class="st">&quot;Methanosarcina semesiae&quot;</span>),</a>
<a class="sourceLine" id="cb3-6" data-line-number="6"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(M.semesiae, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="kw">print</span>(M.semesiae, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo("metsem") 1310.00 1340.0 1361.00 1358 1387.00</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo("METSEM") 1304.00 1320.0 1350.00 1341 1382.00</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo("M. semesiae") 1839.00 1968.0 1990.00 2006 2032.00</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo("M. semesiae") 1947.00 1978.0 2014.00 2019 2046.00</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo("Methanosarcina semesiae") 30.49 31.2 35.04 32 32.81</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co"># expr min lq mean median uq</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"><span class="co"># as.mo(&quot;metsem&quot;) 1343.00 1379.00 1415.00 1404.00 1424.00</span></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># as.mo(&quot;METSEM&quot;) 1335.00 1356.00 1418.00 1410.00 1451.00</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12"><span class="co"># as.mo(&quot;M. semesiae&quot;) 1852.00 2045.00 2081.00 2107.00 2154.00</span></a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># as.mo(&quot;M. semesiae&quot;) 1961.00 2037.00 2095.00 2085.00 2123.00</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14"><span class="co"># as.mo(&quot;Methanosarcina semesiae&quot;) 30.55 31.13 34.35 32.63 33.33</span></a>
<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co"># max neval</span></a>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># 1401.00 10</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># 1411.00 10</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># 2049.00 10</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co"># 2088.00 10</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co"># 63.03 10</span></a></code></pre></div>
<p>That takes 15.2 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Methanosarcina semesiae</em>) are almost fast - these are the most probable input from most data sets.</p>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co"># 1579.00 10</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co"># 1557.00 10</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co"># 2163.00 10</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co"># 2336.00 10</span></a>
<a class="sourceLine" id="cb3-20" data-line-number="20"><span class="co"># 54.12 10</span></a></code></pre></div>
<p>That takes 15.6 times as much time on average. A value of 100 milliseconds means it can only determine ~10 different input values per second. We can conclude that looking up arbitrary codes of less prevalent microorganisms is the worst way to go, in terms of calculation performance. Full names (like <em>Methanosarcina semesiae</em>) are almost fast - these are the most probable input from most data sets.</p>
<p>In the figure below, we compare <em>Escherichia coli</em> (which is very common) with <em>Prevotella brevis</em> (which is moderately common) and with <em>Methanosarcina semesiae</em> (which is uncommon):</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-9-1.png" width="562.5"></p>
<p>In reality, the <code><a href="../reference/as.mo.html">as.mo()</a></code> functions <strong>learns from its own output to speed up determinations for next times</strong>. In above figure, this effect was disabled to show the difference with the boxplot below - when you would use <code><a href="../reference/as.mo.html">as.mo()</a></code> yourself:</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-11-1.png" width="562.5"></p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-9-1.png" width="562.5" /></p>
<p>In reality, the <code>as.mo()</code> functions <strong>learns from its own output to speed up determinations for next times</strong>. In above figure, this effect was disabled to show the difference with the boxplot below - when you would use <code>as.mo()</code> yourself:</p>
<p><img src="benchmarks_files/figure-html/unnamed-chunk-11-1.png" width="562.5" /></p>
<p>The highest outliers are the first times. All next determinations were done in only thousands of seconds.</p>
<p>Uncommon microorganisms take a lot more time than common microorganisms. To relieve this pitfall and further improve performance, two important calculations take almost no time at all: <strong>repetitive results</strong> and <strong>already precalculated results</strong>.</p>
<div id="repetitive-results" class="section level3">
<h3 class="hasAnchor">
<a href="#repetitive-results" class="anchor"></a>Repetitive results</h3>
<p>Repetitive results are unique values that are present more than once. Unique values will only be calculated once by <code><a href="../reference/as.mo.html">as.mo()</a></code>. We will use <code><a href="../reference/mo_property.html">mo_name()</a></code> for this test - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code><a href="../reference/as.mo.html">as.mo()</a></code> internally.</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/library">library</a></span>(dplyr)</a>
<h3>Repetitive results</h3>
<p>Repetitive results are unique values that are present more than once. Unique values will only be calculated once by <code>as.mo()</code>. We will use <code>mo_name()</code> for this test - a helper function that returns the full microbial name (genus, species and possibly subspecies) which uses <code>as.mo()</code> internally.</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw">library</span>(dplyr)</a>
<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="co"># take all MO codes from the example_isolates data set</span></a>
<a class="sourceLine" id="cb4-3" data-line-number="3">x &lt;-<span class="st"> </span>example_isolates<span class="op">$</span>mo <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-4" data-line-number="4"><span class="st"> </span><span class="co"># keep only the unique ones</span></a>
<a class="sourceLine" id="cb4-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/unique">unique</a></span>() <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-5" data-line-number="5"><span class="st"> </span><span class="kw">unique</span>() <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-6" data-line-number="6"><span class="st"> </span><span class="co"># pick 50 of them at random</span></a>
<a class="sourceLine" id="cb4-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>(<span class="dv">50</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-7" data-line-number="7"><span class="st"> </span><span class="kw">sample</span>(<span class="dv">50</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-8" data-line-number="8"><span class="st"> </span><span class="co"># paste that 10,000 times</span></a>
<a class="sourceLine" id="cb4-9" data-line-number="9"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/rep">rep</a></span>(<span class="dv">10000</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-9" data-line-number="9"><span class="st"> </span><span class="kw">rep</span>(<span class="dv">10000</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb4-10" data-line-number="10"><span class="st"> </span><span class="co"># scramble it</span></a>
<a class="sourceLine" id="cb4-11" data-line-number="11"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/sample.html">sample</a></span>()</a>
<a class="sourceLine" id="cb4-11" data-line-number="11"><span class="st"> </span><span class="kw">sample</span>()</a>
<a class="sourceLine" id="cb4-12" data-line-number="12"> </a>
<a class="sourceLine" id="cb4-13" data-line-number="13"><span class="co"># got indeed 50 times 10,000 = half a million?</span></a>
<a class="sourceLine" id="cb4-14" data-line-number="14"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/length">length</a></span>(x)</a>
<a class="sourceLine" id="cb4-14" data-line-number="14"><span class="kw">length</span>(x)</a>
<a class="sourceLine" id="cb4-15" data-line-number="15"><span class="co"># [1] 500000</span></a>
<a class="sourceLine" id="cb4-16" data-line-number="16"></a>
<a class="sourceLine" id="cb4-17" data-line-number="17"><span class="co"># and how many unique values do we have?</span></a>
<a class="sourceLine" id="cb4-18" data-line-number="18"><span class="kw"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html">n_distinct</a></span>(x)</a>
<a class="sourceLine" id="cb4-18" data-line-number="18"><span class="kw">n_distinct</span>(x)</a>
<a class="sourceLine" id="cb4-19" data-line-number="19"><span class="co"># [1] 50</span></a>
<a class="sourceLine" id="cb4-20" data-line-number="20"></a>
<a class="sourceLine" id="cb4-21" data-line-number="21"><span class="co"># now let's see:</span></a>
<a class="sourceLine" id="cb4-22" data-line-number="22">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(x),</a>
<a class="sourceLine" id="cb4-21" data-line-number="21"><span class="co"># now let&#39;s see:</span></a>
<a class="sourceLine" id="cb4-22" data-line-number="22">run_it &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(<span class="kw">mo_name</span>(x),</a>
<a class="sourceLine" id="cb4-23" data-line-number="23"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb4-24" data-line-number="24"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb4-24" data-line-number="24"><span class="kw">print</span>(run_it, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb4-25" data-line-number="25"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb4-26" data-line-number="26"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 598 639 656 657 671 735 10</span></a></code></pre></div>
<a class="sourceLine" id="cb4-27" data-line-number="27"><span class="co"># mo_name(x) 626 639 663 658 682 731 10</span></a></code></pre></div>
<p>So transforming 500,000 values (!!) of 50 unique values only takes 0.66 seconds (657 ms). You only lose time on your unique input values.</p>
</div>
<div id="precalculated-results" class="section level3">
<h3 class="hasAnchor">
<a href="#precalculated-results" class="anchor"></a>Precalculated results</h3>
<p>What about precalculated results? If the input is an already precalculated result of a helper function like <code><a href="../reference/mo_property.html">mo_name()</a></code>, it almost doesn’t take any time at all (see ‘C’ below):</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"B_STPHY_AURS"</span>),</a>
<a class="sourceLine" id="cb5-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"S. aureus"</span>),</a>
<a class="sourceLine" id="cb5-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
<h3>Precalculated results</h3>
<p>What about precalculated results? If the input is an already precalculated result of a helper function like <code>mo_name()</code>, it almost doesn’t take any time at all (see ‘C’ below):</p>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(<span class="dt">A =</span> <span class="kw">mo_name</span>(<span class="st">&quot;B_STPHY_AURS&quot;</span>),</a>
<a class="sourceLine" id="cb5-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw">mo_name</span>(<span class="st">&quot;S. aureus&quot;</span>),</a>
<a class="sourceLine" id="cb5-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw">mo_name</span>(<span class="st">&quot;Staphylococcus aureus&quot;</span>),</a>
<a class="sourceLine" id="cb5-4" data-line-number="4"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb5-5" data-line-number="5"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb5-5" data-line-number="5"><span class="kw">print</span>(run_it, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.150 6.340 9.110 6.370 6.400 33.700 10</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 22.000 22.200 22.900 22.300 22.400 28.300 10</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.691 0.784 0.783 0.795 0.802 0.814 10</span></a></code></pre></div>
<p>So going from <code><a href="../reference/mo_property.html">mo_name("Staphylococcus aureus")</a></code> to <code>"Staphylococcus aureus"</code> takes 0.0008 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">A =</span> <span class="kw"><a href="../reference/mo_property.html">mo_species</a></span>(<span class="st">"aureus"</span>),</a>
<a class="sourceLine" id="cb6-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"Staphylococcus"</span>),</a>
<a class="sourceLine" id="cb6-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"Staphylococcus aureus"</span>),</a>
<a class="sourceLine" id="cb6-4" data-line-number="4"> <span class="dt">D =</span> <span class="kw"><a href="../reference/mo_property.html">mo_family</a></span>(<span class="st">"Staphylococcaceae"</span>),</a>
<a class="sourceLine" id="cb6-5" data-line-number="5"> <span class="dt">E =</span> <span class="kw"><a href="../reference/mo_property.html">mo_order</a></span>(<span class="st">"Bacillales"</span>),</a>
<a class="sourceLine" id="cb6-6" data-line-number="6"> <span class="dt">F =</span> <span class="kw"><a href="../reference/mo_property.html">mo_class</a></span>(<span class="st">"Bacilli"</span>),</a>
<a class="sourceLine" id="cb6-7" data-line-number="7"> <span class="dt">G =</span> <span class="kw"><a href="../reference/mo_property.html">mo_phylum</a></span>(<span class="st">"Firmicutes"</span>),</a>
<a class="sourceLine" id="cb6-8" data-line-number="8"> <span class="dt">H =</span> <span class="kw"><a href="../reference/mo_property.html">mo_kingdom</a></span>(<span class="st">"Bacteria"</span>),</a>
<a class="sourceLine" id="cb5-7" data-line-number="7"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="co"># A 6.260 6.320 9.050 6.360 6.810 32.40 10</span></a>
<a class="sourceLine" id="cb5-9" data-line-number="9"><span class="co"># B 22.800 23.000 23.800 23.200 23.900 28.20 10</span></a>
<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># C 0.709 0.813 0.836 0.843 0.854 0.96 10</span></a></code></pre></div>
<p>So going from <code>mo_name(&quot;Staphylococcus aureus&quot;)</code> to <code>&quot;Staphylococcus aureus&quot;</code> takes 0.0008 seconds - it doesn’t even start calculating <em>if the result would be the same as the expected resulting value</em>. That goes for all helper functions:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1">run_it &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(<span class="dt">A =</span> <span class="kw">mo_species</span>(<span class="st">&quot;aureus&quot;</span>),</a>
<a class="sourceLine" id="cb6-2" data-line-number="2"> <span class="dt">B =</span> <span class="kw">mo_genus</span>(<span class="st">&quot;Staphylococcus&quot;</span>),</a>
<a class="sourceLine" id="cb6-3" data-line-number="3"> <span class="dt">C =</span> <span class="kw">mo_name</span>(<span class="st">&quot;Staphylococcus aureus&quot;</span>),</a>
<a class="sourceLine" id="cb6-4" data-line-number="4"> <span class="dt">D =</span> <span class="kw">mo_family</span>(<span class="st">&quot;Staphylococcaceae&quot;</span>),</a>
<a class="sourceLine" id="cb6-5" data-line-number="5"> <span class="dt">E =</span> <span class="kw">mo_order</span>(<span class="st">&quot;Bacillales&quot;</span>),</a>
<a class="sourceLine" id="cb6-6" data-line-number="6"> <span class="dt">F =</span> <span class="kw">mo_class</span>(<span class="st">&quot;Bacilli&quot;</span>),</a>
<a class="sourceLine" id="cb6-7" data-line-number="7"> <span class="dt">G =</span> <span class="kw">mo_phylum</span>(<span class="st">&quot;Firmicutes&quot;</span>),</a>
<a class="sourceLine" id="cb6-8" data-line-number="8"> <span class="dt">H =</span> <span class="kw">mo_kingdom</span>(<span class="st">&quot;Bacteria&quot;</span>),</a>
<a class="sourceLine" id="cb6-9" data-line-number="9"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb6-10" data-line-number="10"><span class="kw">print</span>(run_it, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">3</span>)</a>
<a class="sourceLine" id="cb6-11" data-line-number="11"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb6-12" data-line-number="12"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.462 0.471 0.480 0.482 0.491 0.498 10</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.609 0.627 0.645 0.638 0.657 0.714 10</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.651 0.731 0.771 0.772 0.806 0.887 10</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.431 0.457 0.488 0.468 0.485 0.675 10</span></a>
<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.450 0.452 0.466 0.465 0.473 0.500 10</span></a>
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.461 0.466 0.481 0.474 0.495 0.514 10</span></a>
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.449 0.453 0.465 0.464 0.471 0.495 10</span></a>
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.455 0.458 0.481 0.465 0.485 0.594 10</span></a></code></pre></div>
<p>Of course, when running <code><a href="../reference/mo_property.html">mo_phylum("Firmicutes")</a></code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>"Firmicutes"</code> too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
<a class="sourceLine" id="cb6-13" data-line-number="13"><span class="co"># A 0.466 0.466 0.495 0.475 0.510 0.622 10</span></a>
<a class="sourceLine" id="cb6-14" data-line-number="14"><span class="co"># B 0.497 0.511 0.558 0.517 0.575 0.844 10</span></a>
<a class="sourceLine" id="cb6-15" data-line-number="15"><span class="co"># C 0.709 0.783 0.876 0.857 0.956 1.110 10</span></a>
<a class="sourceLine" id="cb6-16" data-line-number="16"><span class="co"># D 0.477 0.486 0.547 0.514 0.639 0.669 10</span></a>
<a class="sourceLine" id="cb6-17" data-line-number="17"><span class="co"># E 0.468 0.476 0.504 0.481 0.520 0.630 10</span></a>
<a class="sourceLine" id="cb6-18" data-line-number="18"><span class="co"># F 0.454 0.461 0.509 0.475 0.522 0.687 10</span></a>
<a class="sourceLine" id="cb6-19" data-line-number="19"><span class="co"># G 0.459 0.465 0.522 0.475 0.587 0.637 10</span></a>
<a class="sourceLine" id="cb6-20" data-line-number="20"><span class="co"># H 0.432 0.460 0.502 0.469 0.535 0.623 10</span></a></code></pre></div>
<p>Of course, when running <code>mo_phylum(&quot;Firmicutes&quot;)</code> the function has zero knowledge about the actual microorganism, namely <em>S. aureus</em>. But since the result would be <code>&quot;Firmicutes&quot;</code> too, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.</p>
</div>
<div id="results-in-other-languages" class="section level3">
<h3 class="hasAnchor">
<a href="#results-in-other-languages" class="anchor"></a>Results in other languages</h3>
<h3>Results in other languages</h3>
<p>When the system language is non-English and supported by this <code>AMR</code> package, some functions will have a translated result. This almost does’t take extra time:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"en"</span>) <span class="co"># or just mo_name("CoNS") on an English system</span></a>
<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="co"># [1] "Coagulase-negative Staphylococcus (CoNS)"</span></a>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1"><span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;en&quot;</span>) <span class="co"># or just mo_name(&quot;CoNS&quot;) on an English system</span></a>
<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="co"># [1] &quot;Coagulase-negative Staphylococcus (CoNS)&quot;</span></a>
<a class="sourceLine" id="cb7-3" data-line-number="3"></a>
<a class="sourceLine" id="cb7-4" data-line-number="4"><span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"es"</span>) <span class="co"># or just mo_name("CoNS") on a Spanish system</span></a>
<a class="sourceLine" id="cb7-5" data-line-number="5"><span class="co"># [1] "Staphylococcus coagulasa negativo (SCN)"</span></a>
<a class="sourceLine" id="cb7-4" data-line-number="4"><span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;es&quot;</span>) <span class="co"># or just mo_name(&quot;CoNS&quot;) on a Spanish system</span></a>
<a class="sourceLine" id="cb7-5" data-line-number="5"><span class="co"># [1] &quot;Staphylococcus coagulasa negativo (SCN)&quot;</span></a>
<a class="sourceLine" id="cb7-6" data-line-number="6"></a>
<a class="sourceLine" id="cb7-7" data-line-number="7"><span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"nl"</span>) <span class="co"># or just mo_name("CoNS") on a Dutch system</span></a>
<a class="sourceLine" id="cb7-8" data-line-number="8"><span class="co"># [1] "Coagulase-negatieve Staphylococcus (CNS)"</span></a>
<a class="sourceLine" id="cb7-7" data-line-number="7"><span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;nl&quot;</span>) <span class="co"># or just mo_name(&quot;CoNS&quot;) on a Dutch system</span></a>
<a class="sourceLine" id="cb7-8" data-line-number="8"><span class="co"># [1] &quot;Coagulase-negatieve Staphylococcus (CNS)&quot;</span></a>
<a class="sourceLine" id="cb7-9" data-line-number="9"></a>
<a class="sourceLine" id="cb7-10" data-line-number="10">run_it &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="dt">en =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"en"</span>),</a>
<a class="sourceLine" id="cb7-11" data-line-number="11"> <span class="dt">de =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"de"</span>),</a>
<a class="sourceLine" id="cb7-12" data-line-number="12"> <span class="dt">nl =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"nl"</span>),</a>
<a class="sourceLine" id="cb7-13" data-line-number="13"> <span class="dt">es =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"es"</span>),</a>
<a class="sourceLine" id="cb7-14" data-line-number="14"> <span class="dt">it =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"it"</span>),</a>
<a class="sourceLine" id="cb7-15" data-line-number="15"> <span class="dt">fr =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"fr"</span>),</a>
<a class="sourceLine" id="cb7-16" data-line-number="16"> <span class="dt">pt =</span> <span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"CoNS"</span>, <span class="dt">language =</span> <span class="st">"pt"</span>),</a>
<a class="sourceLine" id="cb7-10" data-line-number="10">run_it &lt;-<span class="st"> </span><span class="kw">microbenchmark</span>(<span class="dt">en =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;en&quot;</span>),</a>
<a class="sourceLine" id="cb7-11" data-line-number="11"> <span class="dt">de =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;de&quot;</span>),</a>
<a class="sourceLine" id="cb7-12" data-line-number="12"> <span class="dt">nl =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;nl&quot;</span>),</a>
<a class="sourceLine" id="cb7-13" data-line-number="13"> <span class="dt">es =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;es&quot;</span>),</a>
<a class="sourceLine" id="cb7-14" data-line-number="14"> <span class="dt">it =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;it&quot;</span>),</a>
<a class="sourceLine" id="cb7-15" data-line-number="15"> <span class="dt">fr =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;fr&quot;</span>),</a>
<a class="sourceLine" id="cb7-16" data-line-number="16"> <span class="dt">pt =</span> <span class="kw">mo_name</span>(<span class="st">&quot;CoNS&quot;</span>, <span class="dt">language =</span> <span class="st">&quot;pt&quot;</span>),</a>
<a class="sourceLine" id="cb7-17" data-line-number="17"> <span class="dt">times =</span> <span class="dv">10</span>)</a>
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/print">print</a></span>(run_it, <span class="dt">unit =</span> <span class="st">"ms"</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb7-18" data-line-number="18"><span class="kw">print</span>(run_it, <span class="dt">unit =</span> <span class="st">&quot;ms&quot;</span>, <span class="dt">signif =</span> <span class="dv">4</span>)</a>
<a class="sourceLine" id="cb7-19" data-line-number="19"><span class="co"># Unit: milliseconds</span></a>
<a class="sourceLine" id="cb7-20" data-line-number="20"><span class="co"># expr min lq mean median uq max neval</span></a>
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 17.93 18.18 19.34 18.76 19.02 26.27 10</span></a>
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 19.44 19.63 22.03 19.80 20.23 41.83 10</span></a>
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 24.54 24.78 27.37 25.23 25.55 47.06 10</span></a>
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 19.51 19.94 20.27 20.20 20.55 21.16 10</span></a>
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 19.40 19.67 24.91 19.99 20.90 46.83 10</span></a>
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 19.24 19.45 22.53 19.80 20.17 47.71 10</span></a>
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 19.18 19.33 19.87 19.72 20.62 20.75 10</span></a></code></pre></div>
<a class="sourceLine" id="cb7-21" data-line-number="21"><span class="co"># en 18.35 18.55 21.13 18.70 18.79 43.22 10</span></a>
<a class="sourceLine" id="cb7-22" data-line-number="22"><span class="co"># de 19.69 19.94 20.81 20.24 20.74 25.64 10</span></a>
<a class="sourceLine" id="cb7-23" data-line-number="23"><span class="co"># nl 25.28 25.42 28.05 25.55 26.59 48.83 10</span></a>
<a class="sourceLine" id="cb7-24" data-line-number="24"><span class="co"># es 19.77 19.95 22.83 20.29 20.76 46.03 10</span></a>
<a class="sourceLine" id="cb7-25" data-line-number="25"><span class="co"># it 19.81 19.88 20.19 20.13 20.55 20.85 10</span></a>
<a class="sourceLine" id="cb7-26" data-line-number="26"><span class="co"># fr 19.62 20.02 22.79 20.26 21.23 44.33 10</span></a>
<a class="sourceLine" id="cb7-27" data-line-number="27"><span class="co"># pt 20.05 20.37 23.19 20.67 21.46 44.96 10</span></a></code></pre></div>
<p>Currently supported are German, Dutch, Spanish, Italian, French and Portuguese.</p>
</div>
</div>
@ -390,18 +429,20 @@
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@ -283,7 +283,7 @@
<div id="microbial-taxonomic-reference-data" class="section level4">
<h4 class="hasAnchor">
<a href="#microbial-taxonomic-reference-data" class="anchor"></a>Microbial (taxonomic) reference data</h4>
<p>This package contains the complete taxonomic tree of almost all 70,000 microorganisms from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org">www.catalogueoflife.org</a>). With <code>catalogue_of_life_version()</code> can be checked which version of the CoL is included in this package.</p>
<p>This package contains the complete taxonomic tree of almost all 70,000 microorganisms from the authoritative and comprehensive Catalogue of Life (CoL, <a href="http://www.catalogueoflife.org">www.catalogueoflife.org</a>). With <code><a href="reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code> can be checked which version of the CoL is included in this package.</p>
<p>Read more about which data from the Catalogue of Life <a href="./reference/catalogue_of_life.html">in our manual</a>.</p>
</div>
<div id="antimicrobial-reference-data" class="section level4">
@ -307,32 +307,32 @@
<li>
<p>It <strong>cleanses existing data</strong> by providing new <em>classes</em> for microoganisms, antibiotics and antimicrobial results (both S/I/R and MIC). By installing this package, you teach R everything about microbiology that is needed for analysis. These functions all use intelligent rules to guess results that you would expect:</p>
<ul>
<li>Use <code>as.mo()</code> to get a microbial ID. The IDs are human readable for the trained eye - the ID of <em>Klebsiella pneumoniae</em> is “B_KLBSL_PNMN” (B stands for Bacteria) and the ID of <em>S. aureus</em> is “B_STPHY_AURS”. The function takes almost any text as input that looks like the name or code of a microorganism like “E. coli”, “esco” or “esccol” and tries to find expected results using intelligent rules combined with the included Catalogue of Life data set. It only takes milliseconds to find results, please see our <a href="./articles/benchmarks.html">benchmarks</a>. Moreover, it can group <em>Staphylococci</em> into coagulase negative and positive (CoNS and CoPS, see <a href="./reference/as.mo.html#source">source</a>) and can categorise <em>Streptococci</em> into Lancefield groups (like beta-haemolytic <em>Streptococcus</em> Group B, <a href="./reference/as.mo.html#source">source</a>).</li>
<li>Use <code>as.ab()</code> to get an antibiotic ID. Like microbial IDs, these IDs are also human readable based on those used by EARS-Net. For example, the ID of amoxicillin is <code>AMX</code> and the ID of gentamicin is <code>GEN</code>. The <code>as.ab()</code> function also uses intelligent rules to find results like accepting misspelling, trade names and abbrevations used in many laboratory systems. For instance, the values “Furabid”, “Furadantin”, “nitro” all return the ID of Nitrofurantoine. To accomplish this, the package contains a database with most LIS codes, official names, trade names, ATC codes, defined daily doses (DDD) and drug categories of antibiotics.</li>
<li>Use <code>as.rsi()</code> to get antibiotic interpretations based on raw MIC values (in mg/L) or disk diffusion values (in mm), or transform existing values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like “&lt;=0.002; S” (combined MIC/RSI) will result in “S”.</li>
<li>Use <code>as.mic()</code> to cleanse your MIC values. It produces a so-called factor (called <em>ordinal</em> in SPSS) with valid MIC values as levels. A value like “&lt;=0.002; S” (combined MIC/RSI) will result in “&lt;=0.002”.</li>
<li>Use <code><a href="reference/as.mo.html">as.mo()</a></code> to get a microbial ID. The IDs are human readable for the trained eye - the ID of <em>Klebsiella pneumoniae</em> is “B_KLBSL_PNMN” (B stands for Bacteria) and the ID of <em>S. aureus</em> is “B_STPHY_AURS”. The function takes almost any text as input that looks like the name or code of a microorganism like “E. coli”, “esco” or “esccol” and tries to find expected results using intelligent rules combined with the included Catalogue of Life data set. It only takes milliseconds to find results, please see our <a href="./articles/benchmarks.html">benchmarks</a>. Moreover, it can group <em>Staphylococci</em> into coagulase negative and positive (CoNS and CoPS, see <a href="./reference/as.mo.html#source">source</a>) and can categorise <em>Streptococci</em> into Lancefield groups (like beta-haemolytic <em>Streptococcus</em> Group B, <a href="./reference/as.mo.html#source">source</a>).</li>
<li>Use <code><a href="reference/as.ab.html">as.ab()</a></code> to get an antibiotic ID. Like microbial IDs, these IDs are also human readable based on those used by EARS-Net. For example, the ID of amoxicillin is <code>AMX</code> and the ID of gentamicin is <code>GEN</code>. The <code><a href="reference/as.ab.html">as.ab()</a></code> function also uses intelligent rules to find results like accepting misspelling, trade names and abbrevations used in many laboratory systems. For instance, the values “Furabid”, “Furadantin”, “nitro” all return the ID of Nitrofurantoine. To accomplish this, the package contains a database with most LIS codes, official names, trade names, ATC codes, defined daily doses (DDD) and drug categories of antibiotics.</li>
<li>Use <code><a href="reference/as.rsi.html">as.rsi()</a></code> to get antibiotic interpretations based on raw MIC values (in mg/L) or disk diffusion values (in mm), or transform existing values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like “&lt;=0.002; S” (combined MIC/RSI) will result in “S”.</li>
<li>Use <code><a href="reference/as.mic.html">as.mic()</a></code> to cleanse your MIC values. It produces a so-called factor (called <em>ordinal</em> in SPSS) with valid MIC values as levels. A value like “&lt;=0.002; S” (combined MIC/RSI) will result in “&lt;=0.002”.</li>
</ul>
</li>
<li>
<p>It <strong>enhances existing data</strong> and <strong>adds new data</strong> from data sets included in this package.</p>
<ul>
<li>Use <code>eucast_rules()</code> to apply <a href="http://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST expert rules to isolates</a> (not the translation from MIC to RSI values, use <code>as.rsi()</code> for that).</li>
<li>Use <code>first_isolate()</code> to identify the first isolates of every patient <a href="https://clsi.org/standards/products/microbiology/documents/m39/">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute).
<li>Use <code><a href="reference/eucast_rules.html">eucast_rules()</a></code> to apply <a href="http://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST expert rules to isolates</a> (not the translation from MIC to RSI values, use <code><a href="reference/as.rsi.html">as.rsi()</a></code> for that).</li>
<li>Use <code><a href="reference/first_isolate.html">first_isolate()</a></code> to identify the first isolates of every patient <a href="https://clsi.org/standards/products/microbiology/documents/m39/">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute).
<ul>
<li>You can also identify first <em>weighted</em> isolates of every patient, an adjusted version of the CLSI guideline. This takes into account key antibiotics of every strain and compares them.</li>
</ul>
</li>
<li>Use <code>mdro()</code> (abbreviation of Multi Drug Resistant Organisms) to check your isolates for exceptional resistance with country-specific guidelines or EUCAST rules. Currently, national guidelines for Germany and the Netherlands are supported.</li>
<li>The <a href="./reference/microorganisms.html">data set <code>microorganisms</code></a> contains the complete taxonomic tree of ~70,000 microorganisms. Furthermore, some colloquial names and all Gram stains are available, which enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like <code>mo_genus()</code>, <code>mo_family()</code>, <code>mo_gramstain()</code> or even <code>mo_phylum()</code>. As they use <code>as.mo()</code> internally, they also use the same intelligent rules for determination. For example, <code>mo_genus("MRSA")</code> and <code>mo_genus("S. aureus")</code> will both return <code>"Staphylococcus"</code>. They also come with support for German, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data.</li>
<li>The <a href="./reference/antibiotics.html">data set <code>antibiotics</code></a> contains ~450 antimicrobial drugs with their EARS-Net code, ATC code, PubChem compound ID, official name, common LIS codes and DDDs of both oral and parenteral administration. It also contains all (thousands of) trade names found in PubChem. The function <code>ab_atc()</code> will return the ATC code of an antibiotic as defined by the WHO. Use functions like <code>ab_name()</code>, <code>ab_group()</code> and <code>ab_tradenames()</code> to look up values. The <code>ab_*</code> functions use <code>as.ab()</code> internally so they support the same intelligent rules to guess the most probable result. For example, <code>ab_name("Fluclox")</code>, <code>ab_name("Floxapen")</code> and <code>ab_name("J01CF05")</code> will all return <code>"Flucloxacillin"</code>. These functions can again be used to add new variables to your data.</li>
<li>Use <code><a href="reference/mdro.html">mdro()</a></code> (abbreviation of Multi Drug Resistant Organisms) to check your isolates for exceptional resistance with country-specific guidelines or EUCAST rules. Currently, national guidelines for Germany and the Netherlands are supported.</li>
<li>The <a href="./reference/microorganisms.html">data set <code>microorganisms</code></a> contains the complete taxonomic tree of ~70,000 microorganisms. Furthermore, some colloquial names and all Gram stains are available, which enables resistance analysis of e.g. different antibiotics per Gram stain. The package also contains functions to look up values in this data set like <code><a href="reference/mo_property.html">mo_genus()</a></code>, <code><a href="reference/mo_property.html">mo_family()</a></code>, <code><a href="reference/mo_property.html">mo_gramstain()</a></code> or even <code><a href="reference/mo_property.html">mo_phylum()</a></code>. As they use <code><a href="reference/as.mo.html">as.mo()</a></code> internally, they also use the same intelligent rules for determination. For example, <code><a href="reference/mo_property.html">mo_genus("MRSA")</a></code> and <code><a href="reference/mo_property.html">mo_genus("S. aureus")</a></code> will both return <code>"Staphylococcus"</code>. They also come with support for German, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data.</li>
<li>The <a href="./reference/antibiotics.html">data set <code>antibiotics</code></a> contains ~450 antimicrobial drugs with their EARS-Net code, ATC code, PubChem compound ID, official name, common LIS codes and DDDs of both oral and parenteral administration. It also contains all (thousands of) trade names found in PubChem. The function <code><a href="reference/ab_property.html">ab_atc()</a></code> will return the ATC code of an antibiotic as defined by the WHO. Use functions like <code><a href="reference/ab_property.html">ab_name()</a></code>, <code><a href="reference/ab_property.html">ab_group()</a></code> and <code><a href="reference/ab_property.html">ab_tradenames()</a></code> to look up values. The <code>ab_*</code> functions use <code><a href="reference/as.ab.html">as.ab()</a></code> internally so they support the same intelligent rules to guess the most probable result. For example, <code><a href="reference/ab_property.html">ab_name("Fluclox")</a></code>, <code><a href="reference/ab_property.html">ab_name("Floxapen")</a></code> and <code><a href="reference/ab_property.html">ab_name("J01CF05")</a></code> will all return <code>"Flucloxacillin"</code>. These functions can again be used to add new variables to your data.</li>
</ul>
</li>
<li>
<p>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</p>
<ul>
<li>Calculate the resistance (and even co-resistance) of microbial isolates with the <code>portion_R()</code>, <code>portion_IR()</code>, <code>portion_I()</code>, <code>portion_SI()</code> and <code>portion_S()</code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code>count_R()</code>, <code>count_IR()</code>, <code>count_I()</code>, <code>count_SI()</code> and <code>count_S()</code> functions. All these functions can be used with the <code>dplyr</code> package (e.g. in conjunction with <code>summarise()</code>)</li>
<li>Plot AMR results with <code>geom_rsi()</code>, a function made for the <code>ggplot2</code> package</li>
<li>Predict antimicrobial resistance for the nextcoming years using logistic regression models with the <code>resistance_predict()</code> function</li>
<li>Calculate the resistance (and even co-resistance) of microbial isolates with the <code><a href="reference/portion.html">portion_R()</a></code>, <code><a href="reference/portion.html">portion_IR()</a></code>, <code><a href="reference/portion.html">portion_I()</a></code>, <code><a href="reference/portion.html">portion_SI()</a></code> and <code><a href="reference/portion.html">portion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><a href="reference/count.html">count_R()</a></code>, <code><a href="reference/count.html">count_IR()</a></code>, <code><a href="reference/count.html">count_I()</a></code>, <code><a href="reference/count.html">count_SI()</a></code> and <code><a href="reference/count.html">count_S()</a></code> functions. All these functions can be used with the <code>dplyr</code> package (e.g. in conjunction with <code>summarise()</code>)</li>
<li>Plot AMR results with <code><a href="reference/ggplot_rsi.html">geom_rsi()</a></code>, a function made for the <code>ggplot2</code> package</li>
<li>Predict antimicrobial resistance for the nextcoming years using logistic regression models with the <code><a href="reference/resistance_predict.html">resistance_predict()</a></code> function</li>
</ul>
</li>
<li>

348
docs/news/index.html
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@ -78,7 +78,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9080</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9081</span>
</span>
</div>
@ -225,18 +225,18 @@
</div>
<div id="amr-0-7-1-9080" class="section level1">
<div id="amr-0-7-1-9081" class="section level1">
<h1 class="page-header">
<a href="#amr-0-7-1-9080" class="anchor"></a>AMR 0.7.1.9080<small> Unreleased </small>
<a href="#amr-0-7-1-9081" class="anchor"></a>AMR 0.7.1.9081<small> Unreleased </small>
</h1>
<p><small>Last updated: 22-Sep-2019</small></p>
<p><small>Last updated: 23-Sep-2019</small></p>
<div id="breaking" class="section level3">
<h3 class="hasAnchor">
<a href="#breaking" class="anchor"></a>Breaking</h3>
<ul>
<li>
<p>Determination of first isolates now <strong>excludes</strong> all ‘unknown’ microorganisms at default, i.e. microbial code <code>"UNKNOWN"</code>. They can be included with the new parameter <code>include_unknown</code>:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw">first_isolate</span>(..., <span class="dt">include_unknown =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(..., <span class="dt">include_unknown =</span> <span class="ot">TRUE</span>)</a></code></pre></div>
For WHONET users, this means that all records/isolates with organism code <code>"con"</code> (<em>contamination</em>) will be excluded at default, since <code>as.mo("con") = "UNKNOWN"</code>. The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.</li>
<li>
<p>For code consistency, classes <code>ab</code> and <code>mo</code> will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in <code>NA</code>:</p>
@ -247,12 +247,12 @@ For WHONET users, this means that all records/isolates with organism code <code>
<a class="sourceLine" id="cb2-5" data-line-number="5"><span class="co">#&gt; invalid factor level, NA generated</span></a>
<a class="sourceLine" id="cb2-6" data-line-number="6"></a>
<a class="sourceLine" id="cb2-7" data-line-number="7"><span class="co"># how it now works similarly for classes 'mo' and 'ab':</span></a>
<a class="sourceLine" id="cb2-8" data-line-number="8">x &lt;-<span class="st"> </span><span class="kw">as.mo</span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb2-8" data-line-number="8">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb2-9" data-line-number="9">x[<span class="dv">1</span>] &lt;-<span class="st"> "testvalue"</span></a>
<a class="sourceLine" id="cb2-10" data-line-number="10"><span class="co">#&gt; Warning message:</span></a>
<a class="sourceLine" id="cb2-11" data-line-number="11"><span class="co">#&gt; invalid microorganism code, NA generated</span></a></code></pre></div>
This is important, because a value like <code>"testvalue"</code> could never be understood by e.g. <code>mo_name()</code>, although the class would suggest a valid microbial code.</li>
<li><p>Function <code>freq()</code> has moved to a new package, <a href="https://github.com/msberends/clean"><code>clean</code></a> (<a href="https://cran.r-project.org/package=clean">CRAN link</a>), since creating frequency tables actually does not fit the scope of this package. The <code>freq()</code> function still works, since it is re-exported from the <code>clean</code> package (which will be installed automatically upon updating this <code>AMR</code> package).</p></li>
This is important, because a value like <code>"testvalue"</code> could never be understood by e.g. <code><a href="../reference/mo_property.html">mo_name()</a></code>, although the class would suggest a valid microbial code.</li>
<li><p>Function <code><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code> has moved to a new package, <a href="https://github.com/msberends/clean"><code>clean</code></a> (<a href="https://cran.r-project.org/package=clean">CRAN link</a>), since creating frequency tables actually does not fit the scope of this package. The <code><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code> function still works, since it is re-exported from the <code>clean</code> package (which will be installed automatically upon updating this <code>AMR</code> package).</p></li>
</ul>
</div>
<div id="new" class="section level3">
@ -260,16 +260,26 @@ This is important, because a value like <code>"testvalue"</code> could never be
<a href="#new" class="anchor"></a>New</h3>
<ul>
<li>
<p>Function <code>bug_drug_combinations()</code> to quickly get a <code>data.frame</code> with the antimicrobial resistance of any bug-drug combination in a data set:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">x &lt;-<span class="st"> </span><span class="kw">bug_drug_combinations</span>(example_isolates)</a>
<a class="sourceLine" id="cb3-2" data-line-number="2">x</a>
<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `mo` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="co">#&gt; ab mo S I R total</span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="co">#&gt; 1 AMC B_ESCHR_COLI 332 74 61 467</span></a>
<a class="sourceLine" id="cb3-6" data-line-number="6"><span class="co">#&gt; 2 AMC B_KLBSL_PNMN 49 3 6 58</span></a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="co">#&gt; 3 AMC B_PROTS_MRBL 28 7 1 36</span></a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co">#&gt; 4 AMC B_PSDMN_AERG 0 0 30 30</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co">#&gt; 5 AMC B_STPHY_AURS 234 0 1 235</span></a></code></pre></div>
<p>Function <code><a href="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> to quickly get a <code>data.frame</code> with the antimicrobial resistance of any bug-drug combination in a data set. The columns with microorganism codes is guessed automatically and its input is transformed with <code><a href="../reference/mo_property.html">mo_shortname()</a></code> at default:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span>(example_isolates)</a>
<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `mo` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb3-3" data-line-number="3">x[<span class="dv">1</span><span class="op">:</span><span class="dv">5</span>, ]</a>
<a class="sourceLine" id="cb3-4" data-line-number="4"><span class="co">#&gt; ab mo S I R total</span></a>
<a class="sourceLine" id="cb3-5" data-line-number="5"><span class="co">#&gt; 1 AMC CoNS 178 0 132 310</span></a>
<a class="sourceLine" id="cb3-6" data-line-number="6"><span class="co">#&gt; 2 AMC E. coli 332 74 61 467</span></a>
<a class="sourceLine" id="cb3-7" data-line-number="7"><span class="co">#&gt; 3 AMC K. pneumoniae 49 3 6 58</span></a>
<a class="sourceLine" id="cb3-8" data-line-number="8"><span class="co">#&gt; 4 AMC P. aeruginosa 0 0 30 30</span></a>
<a class="sourceLine" id="cb3-9" data-line-number="9"><span class="co">#&gt; 5 AMC P. mirabilis 28 7 1 36</span></a>
<a class="sourceLine" id="cb3-10" data-line-number="10"></a>
<a class="sourceLine" id="cb3-11" data-line-number="11"><span class="co"># change the transformation with the FUN argument to anything you like:</span></a>
<a class="sourceLine" id="cb3-12" data-line-number="12">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/bug_drug_combinations.html">bug_drug_combinations</a></span>(example_isolates, <span class="dt">FUN =</span> mo_gramstain)</a>
<a class="sourceLine" id="cb3-13" data-line-number="13"><span class="co"># </span><span class="al">NOTE</span><span class="co">: Using column `mo` as input for `col_mo`.</span></a>
<a class="sourceLine" id="cb3-14" data-line-number="14">x[<span class="dv">1</span><span class="op">:</span><span class="dv">4</span>, ]</a>
<a class="sourceLine" id="cb3-15" data-line-number="15"><span class="co">#&gt; ab mo S I R total</span></a>
<a class="sourceLine" id="cb3-16" data-line-number="16"><span class="co">#&gt; 1 AMC Gram-negative 469 89 174 732</span></a>
<a class="sourceLine" id="cb3-17" data-line-number="17"><span class="co">#&gt; 2 AMC Gram-positive 873 2 272 1147</span></a>
<a class="sourceLine" id="cb3-18" data-line-number="18"><span class="co">#&gt; 3 AMK Gram-negative 251 0 2 253</span></a>
<a class="sourceLine" id="cb3-19" data-line-number="19"><span class="co">#&gt; 4 AMK Gram-positive 0 0 100 100</span></a></code></pre></div>
<p>You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R <code><a href="https://www.rdocumentation.org/packages/base/topics/format">format()</a></code> function:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/format">format</a></span>(x, <span class="dt">combine_IR =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
</li>
@ -306,7 +316,7 @@ Since this is a major change, usage of the old <code>also_single_tested</code> w
<h3 class="hasAnchor">
<a href="#changed" class="anchor"></a>Changed</h3>
<ul>
<li>Many algorithm improvements for <code>as.mo()</code> (of which some led to additions to the <code>microorganisms</code> data set). Many thanks to all contributors that helped improving the algorithms.
<li>Many algorithm improvements for <code><a href="../reference/as.mo.html">as.mo()</a></code> (of which some led to additions to the <code>microorganisms</code> data set). Many thanks to all contributors that helped improving the algorithms.
<ul>
<li>Self-learning algorithm - the function now gains experience from previously determined microorganism IDs and learns from it (yielding 80-95% speed improvement for any guess after the first try)</li>
<li>Big improvement for misspelled input</li>
@ -317,39 +327,39 @@ Since this is a major change, usage of the old <code>also_single_tested</code> w
</li>
<li>Added support for 5,000 new fungi</li>
<li>Added support for unknown yeasts and fungi</li>
<li>Changed most microorganism IDs to improve readability. <strong>IMPORTANT:</strong> Because of these changes, the microorganism IDs have been changed to a slightly different format. Old microorganism IDs are still supported, but support will be dropped in a future version. Use <code>as.mo()</code> on your old codes to transform them to the new format.</li>
<li>Changed most microorganism IDs to improve readability. For example, the old code <code>B_ENTRC_FAE</code> could have been both <em>E. faecalis</em> and <em>E. faecium</em>. Its new code is <code>B_ENTRC_FCLS</code> and <em>E. faecium</em> has become <code>B_ENTRC_FACM</code>. Also, the Latin character æ (ae) is now preserved at the start of each genus and species abbreviation. For example, the old code for <em>Aerococcus urinae</em> was <code>B_ARCCC_NAE</code>. This is now <code>B_AERCC_URIN</code>. <strong>IMPORTANT:</strong> Old microorganism IDs are still supported, but support will be dropped in a future version. Use <code><a href="../reference/as.mo.html">as.mo()</a></code> on your old codes to transform them to the new format. Using functions from the <code>mo_*</code> family (like <code><a href="../reference/mo_property.html">mo_name()</a></code> and <code><a href="../reference/mo_property.html">mo_gramstain()</a></code>) on old codes, will throw a warning.</li>
</ul>
</li>
<li>Renamed data set <code>septic_patients</code> to <code>example_isolates</code>
</li>
<li>Function <code>eucast_rules()</code>:
<li>Function <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:
<ul>
<li>Fixed a bug for <em>Yersinia pseudotuberculosis</em>
</li>
<li>Added more informative errors and warnings</li>
<li>Printed info now distinguishes between added and changes values</li>
<li>Using Verbose mode (i.e. <code>eucast_rules(..., verbose = TRUE)</code>) returns more informative and readable output</li>
<li>Using Verbose mode (i.e. <code><a href="../reference/eucast_rules.html">eucast_rules(..., verbose = TRUE)</a></code>) returns more informative and readable output</li>
<li>Using factors as input now adds missing factors levels when the function changes antibiotic results</li>
</ul>
</li>
<li>Improved the internal auto-guessing function for determining antibiotics in your data set (<code>AMR:::get_column_abx()</code>)</li>
<li>Removed class <code>atc</code> - using <code>as.atc()</code> is now deprecated in favour of <code>ab_atc()</code> and this will return a character, not the <code>atc</code> class anymore</li>
<li>Removed class <code>atc</code> - using <code><a href="../reference/AMR-deprecated.html">as.atc()</a></code> is now deprecated in favour of <code><a href="../reference/ab_property.html">ab_atc()</a></code> and this will return a character, not the <code>atc</code> class anymore</li>
<li>Removed deprecated functions <code>abname()</code>, <code>ab_official()</code>, <code>atc_name()</code>, <code>atc_official()</code>, <code>atc_property()</code>, <code>atc_tradenames()</code>, <code>atc_trivial_nl()</code>
</li>
<li>Fix and speed improvement for <code>mo_shortname()</code>
<li>Fix and speed improvement for <code><a href="../reference/mo_property.html">mo_shortname()</a></code>
</li>
<li>Fix for using <code>mo_*</code> functions where the coercion uncertainties and failures would not be available through <code>mo_uncertainties()</code> and <code>mo_failures()</code> anymore</li>
<li>Deprecated the <code>country</code> parameter of <code>mdro()</code> in favour of the already existing <code>guideline</code> parameter to support multiple guidelines within one country</li>
<li>Fix for using <code>mo_*</code> functions where the coercion uncertainties and failures would not be available through <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code> and <code><a href="../reference/as.mo.html">mo_failures()</a></code> anymore</li>
<li>Deprecated the <code>country</code> parameter of <code><a href="../reference/mdro.html">mdro()</a></code> in favour of the already existing <code>guideline</code> parameter to support multiple guidelines within one country</li>
<li>The <code>name</code> of <code>RIF</code> is now Rifampicin instead of Rifampin</li>
<li>The <code>antibiotics</code> data set is now sorted by name and all cephalosporins now have their generation between brackets</li>
<li>Speed improvement for <code>guess_ab_col()</code> which is now 30 times faster for antibiotic abbreviations</li>
<li>Improved <code>filter_ab_class()</code> to be more reliable and to support 5th generation cephalosporins</li>
<li>Function <code>availability()</code> now uses <code>portion_R()</code> instead of <code>portion_IR()</code>, to comply with EUCAST insights</li>
<li>Functions <code>age()</code> and <code>age_groups()</code> now have a <code>na.rm</code> parameter to remove empty values</li>
<li>Renamed function <code>p.symbol()</code> to <code>p_symbol()</code> (the former is now deprecated and will be removed in a future version)</li>
<li>Using negative values for <code>x</code> in <code>age_groups()</code> will now introduce <code>NA</code>s and not return an error anymore</li>
<li>Speed improvement for <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code> which is now 30 times faster for antibiotic abbreviations</li>
<li>Improved <code><a href="../reference/filter_ab_class.html">filter_ab_class()</a></code> to be more reliable and to support 5th generation cephalosporins</li>
<li>Function <code><a href="../reference/availability.html">availability()</a></code> now uses <code><a href="../reference/portion.html">portion_R()</a></code> instead of <code><a href="../reference/portion.html">portion_IR()</a></code>, to comply with EUCAST insights</li>
<li>Functions <code><a href="../reference/age.html">age()</a></code> and <code><a href="../reference/age_groups.html">age_groups()</a></code> now have a <code>na.rm</code> parameter to remove empty values</li>
<li>Renamed function <code><a href="../reference/AMR-deprecated.html">p.symbol()</a></code> to <code><a href="../reference/p_symbol.html">p_symbol()</a></code> (the former is now deprecated and will be removed in a future version)</li>
<li>Using negative values for <code>x</code> in <code><a href="../reference/age_groups.html">age_groups()</a></code> will now introduce <code>NA</code>s and not return an error anymore</li>
<li>Fix for determining the system’s language</li>
<li>Fix for <code>key_antibiotics()</code> on foreign systems</li>
<li>Fix for <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> on foreign systems</li>
<li>Added 80 new LIS codes for microorganisms</li>
</ul>
<div id="other" class="section level4">
@ -370,10 +380,10 @@ Since this is a major change, usage of the old <code>also_single_tested</code> w
<a href="#new-1" class="anchor"></a>New</h4>
<ul>
<li>
<p>Function <code>rsi_df()</code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code>count_df()</code> and <code>portion_df()</code> to immediately show resistance percentages and number of available isolates:</p>
<p>Function <code><a href="../reference/portion.html">rsi_df()</a></code> to transform a <code>data.frame</code> to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions <code><a href="../reference/count.html">count_df()</a></code> and <code><a href="../reference/portion.html">portion_df()</a></code> to immediately show resistance percentages and number of available isolates:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(AMX, CIP) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb7-3" data-line-number="3"><span class="st"> </span><span class="kw">rsi_df</span>()</a>
<a class="sourceLine" id="cb7-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="../reference/portion.html">rsi_df</a></span>()</a>
<a class="sourceLine" id="cb7-4" data-line-number="4"><span class="co"># antibiotic interpretation value isolates</span></a>
<a class="sourceLine" id="cb7-5" data-line-number="5"><span class="co"># 1 Amoxicillin SI 0.4442636 546</span></a>
<a class="sourceLine" id="cb7-6" data-line-number="6"><span class="co"># 2 Amoxicillin R 0.5557364 683</span></a>
@ -396,41 +406,41 @@ Since this is a major change, usage of the old <code>also_single_tested</code> w
<li>UPEC (Uropathogenic <em>E. coli</em>)</li>
</ul>
<p>All these lead to the microbial ID of <em>E. coli</em>:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1"><span class="kw">as.mo</span>(<span class="st">"UPEC"</span>)</a>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"UPEC"</span>)</a>
<a class="sourceLine" id="cb8-2" data-line-number="2"><span class="co"># B_ESCHR_COL</span></a>
<a class="sourceLine" id="cb8-3" data-line-number="3"><span class="kw">mo_name</span>(<span class="st">"UPEC"</span>)</a>
<a class="sourceLine" id="cb8-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_name</a></span>(<span class="st">"UPEC"</span>)</a>
<a class="sourceLine" id="cb8-4" data-line-number="4"><span class="co"># "Escherichia coli"</span></a>
<a class="sourceLine" id="cb8-5" data-line-number="5"><span class="kw">mo_gramstain</span>(<span class="st">"EHEC"</span>)</a>
<a class="sourceLine" id="cb8-5" data-line-number="5"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"EHEC"</span>)</a>
<a class="sourceLine" id="cb8-6" data-line-number="6"><span class="co"># "Gram-negative"</span></a></code></pre></div>
</li>
<li>Function <code>mo_info()</code> as an analogy to <code>ab_info()</code>. The <code>mo_info()</code> prints a list with the full taxonomy, authors, and the URL to the online database of a microorganism</li>
<li><p>Function <code>mo_synonyms()</code> to get all previously accepted taxonomic names of a microorganism</p></li>
<li>Function <code><a href="../reference/mo_property.html">mo_info()</a></code> as an analogy to <code><a href="../reference/ab_property.html">ab_info()</a></code>. The <code><a href="../reference/mo_property.html">mo_info()</a></code> prints a list with the full taxonomy, authors, and the URL to the online database of a microorganism</li>
<li><p>Function <code><a href="../reference/mo_property.html">mo_synonyms()</a></code> to get all previously accepted taxonomic names of a microorganism</p></li>
</ul>
</div>
<div id="changed-1" class="section level4">
<h4 class="hasAnchor">
<a href="#changed-1" class="anchor"></a>Changed</h4>
<ul>
<li>Column names of output <code>count_df()</code> and <code>portion_df()</code> are now lowercase</li>
<li>Column names of output <code><a href="../reference/count.html">count_df()</a></code> and <code><a href="../reference/portion.html">portion_df()</a></code> are now lowercase</li>
<li>Fixed bug in translation of microorganism names</li>
<li>Fixed bug in determining taxonomic kingdoms</li>
<li>Algorithm improvements for <code>as.ab()</code> and <code>as.mo()</code> to understand even more severely misspelled input</li>
<li>Function <code>as.ab()</code> now allows spaces for coercing antibiotics names</li>
<li>Algorithm improvements for <code><a href="../reference/as.ab.html">as.ab()</a></code> and <code><a href="../reference/as.mo.html">as.mo()</a></code> to understand even more severely misspelled input</li>
<li>Function <code><a href="../reference/as.ab.html">as.ab()</a></code> now allows spaces for coercing antibiotics names</li>
<li>Added <code>ggplot2</code> methods for automatically determining the scale type of classes <code>mo</code> and <code>ab</code>
</li>
<li>Added names of object in the header in frequency tables, even when using pipes</li>
<li>Prevented <code>"bacteria"</code> from getting coerced by <code>as.ab()</code> because Bacterial is a brand name of trimethoprim (TMP)</li>
<li>Fixed a bug where setting an antibiotic would not work for <code>eucast_rules()</code> and <code>mdro()</code>
<li>Prevented <code>"bacteria"</code> from getting coerced by <code><a href="../reference/as.ab.html">as.ab()</a></code> because Bacterial is a brand name of trimethoprim (TMP)</li>
<li>Fixed a bug where setting an antibiotic would not work for <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> and <code><a href="../reference/mdro.html">mdro()</a></code>
</li>
<li>Fixed a EUCAST rule for Staphylococci, where amikacin resistance would not be inferred from tobramycin</li>
<li>Removed <code>latest_annual_release</code> from the <code>catalogue_of_life_version()</code> function</li>
<li>Removed <code>latest_annual_release</code> from the <code><a href="../reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code> function</li>
<li>Removed antibiotic code <code>PVM1</code> from the <code>antibiotics</code> data set as this was a duplicate of <code>PME</code>
</li>
<li>Fixed bug where not all old taxonomic names would be printed, when using a vector as input for <code>as.mo()</code>
<li>Fixed bug where not all old taxonomic names would be printed, when using a vector as input for <code><a href="../reference/as.mo.html">as.mo()</a></code>
</li>
<li>Manually added <em>Trichomonas vaginalis</em> from the kingdom of Protozoa, which is missing from the Catalogue of Life</li>
<li>Small improvements to <code><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> and <code><a href="https://www.rdocumentation.org/packages/graphics/topics/barplot">barplot()</a></code> for MIC and RSI classes</li>
<li>Allow Catalogue of Life IDs to be coerced by <code>as.mo()</code>
<li>Allow Catalogue of Life IDs to be coerced by <code><a href="../reference/as.mo.html">as.mo()</a></code>
</li>
</ul>
</div>
@ -450,18 +460,18 @@ Since this is a major change, usage of the old <code>also_single_tested</code> w
<h4 class="hasAnchor">
<a href="#new-2" class="anchor"></a>New</h4>
<ul>
<li>Support for translation of disk diffusion and MIC values to RSI values (i.e. antimicrobial interpretations). Supported guidelines are EUCAST (2011 to 2019) and CLSI (2011 to 2019). Use <code>as.rsi()</code> on an MIC value (created with <code>as.mic()</code>), a disk diffusion value (created with the new <code>as.disk()</code>) or on a complete date set containing columns with MIC or disk diffusion values.</li>
<li>Function <code>mo_name()</code> as alias of <code>mo_fullname()</code>
<li>Support for translation of disk diffusion and MIC values to RSI values (i.e. antimicrobial interpretations). Supported guidelines are EUCAST (2011 to 2019) and CLSI (2011 to 2019). Use <code><a href="../reference/as.rsi.html">as.rsi()</a></code> on an MIC value (created with <code><a href="../reference/as.mic.html">as.mic()</a></code>), a disk diffusion value (created with the new <code><a href="../reference/as.disk.html">as.disk()</a></code>) or on a complete date set containing columns with MIC or disk diffusion values.</li>
<li>Function <code><a href="../reference/mo_property.html">mo_name()</a></code> as alias of <code><a href="../reference/mo_property.html">mo_fullname()</a></code>
</li>
<li>Added guidelines of the WHO to determine multi-drug resistance (MDR) for TB (<code>mdr_tb()</code>) and added a new vignette about MDR. Read this tutorial <a href="https://msberends.gitlab.io/AMR/articles/MDR.html">here on our website</a>.</li>
<li>Added guidelines of the WHO to determine multi-drug resistance (MDR) for TB (<code><a href="../reference/mdro.html">mdr_tb()</a></code>) and added a new vignette about MDR. Read this tutorial <a href="https://msberends.gitlab.io/AMR/articles/MDR.html">here on our website</a>.</li>
</ul>
</div>
<div id="changed-2" class="section level4">
<h4 class="hasAnchor">
<a href="#changed-2" class="anchor"></a>Changed</h4>
<ul>
<li>Fixed a critical bug in <code>first_isolate()</code> where missing species would lead to incorrect FALSEs. This bug was not present in AMR v0.5.0, but was in v0.6.0 and v0.6.1.</li>
<li>Fixed a bug in <code>eucast_rules()</code> where antibiotics from WHONET software would not be recognised</li>
<li>Fixed a critical bug in <code><a href="../reference/first_isolate.html">first_isolate()</a></code> where missing species would lead to incorrect FALSEs. This bug was not present in AMR v0.5.0, but was in v0.6.0 and v0.6.1.</li>
<li>Fixed a bug in <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> where antibiotics from WHONET software would not be recognised</li>
<li>Completely reworked the <code>antibiotics</code> data set:
<ul>
<li>All entries now have 3 different identifiers:
@ -480,20 +490,20 @@ Since this is a major change, usage of the old <code>also_single_tested</code> w
Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=Translation%20suggestion">create an issue in one of our repositories</a> if you want additions in this file.</li>
</ul>
</li>
<li>Improvements to plotting AMR results with <code>ggplot_rsi()</code>:
<li>Improvements to plotting AMR results with <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code>:
<ul>
<li>New parameter <code>colours</code> to set the bar colours</li>
<li>New parameters <code>title</code>, <code>subtitle</code>, <code>caption</code>, <code>x.title</code> and <code>y.title</code> to set titles and axis descriptions</li>
</ul>
</li>
<li>Improved intelligence of looking up antibiotic columns in a data set using <code>guess_ab_col()</code>
<li>Improved intelligence of looking up antibiotic columns in a data set using <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code>
</li>
<li>Added ~5,000 more old taxonomic names to the <code>microorganisms.old</code> data set, which leads to better results finding when using the <code>as.mo()</code> function</li>
<li>This package now honours the new EUCAST insight (2019) that S and I are but classified as susceptible, where I is defined as ‘increased exposure’ and not ‘intermediate’ anymore. For functions like <code>portion_df()</code> and <code>count_df()</code> this means that their new parameter <code>combine_SI</code> is TRUE at default. Our plotting function <code>ggplot_rsi()</code> also reflects this change since it uses <code>count_df()</code> internally.</li>
<li>The <code>age()</code> function gained a new parameter <code>exact</code> to determine ages with decimals</li>
<li>Added ~5,000 more old taxonomic names to the <code>microorganisms.old</code> data set, which leads to better results finding when using the <code><a href="../reference/as.mo.html">as.mo()</a></code> function</li>
<li>This package now honours the new EUCAST insight (2019) that S and I are but classified as susceptible, where I is defined as ‘increased exposure’ and not ‘intermediate’ anymore. For functions like <code><a href="../reference/portion.html">portion_df()</a></code> and <code><a href="../reference/count.html">count_df()</a></code> this means that their new parameter <code>combine_SI</code> is TRUE at default. Our plotting function <code><a href="../reference/ggplot_rsi.html">ggplot_rsi()</a></code> also reflects this change since it uses <code><a href="../reference/count.html">count_df()</a></code> internally.</li>
<li>The <code><a href="../reference/age.html">age()</a></code> function gained a new parameter <code>exact</code> to determine ages with decimals</li>
<li>Removed deprecated functions <code>guess_mo()</code>, <code>guess_atc()</code>, <code>EUCAST_rules()</code>, <code>interpretive_reading()</code>, <code>rsi()</code>
</li>
<li>Frequency tables (<code>freq()</code>):
<li>Frequency tables (<code><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code>):
<ul>
<li>speed improvement for microbial IDs</li>
<li>fixed factor level names for R Markdown</li>
@ -501,12 +511,12 @@ Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=Tra
<li>
<p>support for boxplots:</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb9-2" data-line-number="2"><span class="st"> </span><span class="kw">freq</span>(age) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb9-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(age) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb9-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/boxplot">boxplot</a></span>()</a>
<a class="sourceLine" id="cb9-4" data-line-number="4"><span class="co"># grouped boxplots:</span></a>
<a class="sourceLine" id="cb9-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb9-6" data-line-number="6"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb9-7" data-line-number="7"><span class="st"> </span><span class="kw">freq</span>(age) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb9-7" data-line-number="7"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(age) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb9-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/boxplot">boxplot</a></span>()</a></code></pre></div>
</li>
</ul>
@ -516,18 +526,18 @@ Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=Tra
Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=EUCAST%20edit">create an issue in one of our repositories</a> if you want changes in this file.</li>
<li>Added ceftazidim intrinsic resistance to <em>Streptococci</em>
</li>
<li>Changed default settings for <code>age_groups()</code>, to let groups of fives and tens end with 100+ instead of 120+</li>
<li>Fix for <code>freq()</code> for when all values are <code>NA</code>
<li>Changed default settings for <code><a href="../reference/age_groups.html">age_groups()</a></code>, to let groups of fives and tens end with 100+ instead of 120+</li>
<li>Fix for <code><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code> for when all values are <code>NA</code>
</li>
<li>Fix for <code>first_isolate()</code> for when dates are missing</li>
<li>Improved speed of <code>guess_ab_col()</code>
<li>Fix for <code><a href="../reference/first_isolate.html">first_isolate()</a></code> for when dates are missing</li>
<li>Improved speed of <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code>
</li>
<li>Function <code>as.mo()</code> now gently interprets any number of whitespace characters (like tabs) as one space</li>
<li>Function <code>as.mo()</code> now returns <code>UNKNOWN</code> for <code>"con"</code> (WHONET ID of ‘contamination’) and returns <code>NA</code> for <code>"xxx"</code>(WHONET ID of ‘no growth’)</li>
<li>Small algorithm fix for <code>as.mo()</code>
<li>Function <code><a href="../reference/as.mo.html">as.mo()</a></code> now gently interprets any number of whitespace characters (like tabs) as one space</li>
<li>Function <code><a href="../reference/as.mo.html">as.mo()</a></code> now returns <code>UNKNOWN</code> for <code>"con"</code> (WHONET ID of ‘contamination’) and returns <code>NA</code> for <code>"xxx"</code>(WHONET ID of ‘no growth’)</li>
<li>Small algorithm fix for <code><a href="../reference/as.mo.html">as.mo()</a></code>
</li>
<li>Removed viruses from data set <code>microorganisms.codes</code> and cleaned it up</li>
<li><p>Fix for <code>mo_shortname()</code> where species would not be determined correctly</p></li>
<li><p>Fix for <code><a href="../reference/mo_property.html">mo_shortname()</a></code> where species would not be determined correctly</p></li>
</ul>
</div>
<div id="other-2" class="section level4">
@ -547,7 +557,7 @@ Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=EUC
<h4 class="hasAnchor">
<a href="#changed-3" class="anchor"></a>Changed</h4>
<ul>
<li>Fixed a critical bug when using <code>eucast_rules()</code> with <code>verbose = TRUE</code>
<li>Fixed a critical bug when using <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code> with <code>verbose = TRUE</code>
</li>
<li>Coercion of microbial IDs are now written to the package namespace instead of the user’s home folder, to comply with the CRAN policy</li>
</ul>
@ -568,7 +578,7 @@ Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=EUC
<a href="#new-3" class="anchor"></a>New</h4>
<ul>
<li>
<strong>BREAKING</strong>: removed deprecated functions, parameters and references to ‘bactid’. Use <code>as.mo()</code> to identify an MO code.</li>
<strong>BREAKING</strong>: removed deprecated functions, parameters and references to ‘bactid’. Use <code><a href="../reference/as.mo.html">as.mo()</a></code> to identify an MO code.</li>
<li>Catalogue of Life as a new taxonomic source for data about microorganisms, which also contains all ITIS data we used previously. The <code>microorganisms</code> data set now contains:
<ul>
<li>All ~55,000 (sub)species from the kingdoms of Archaea, Bacteria and Protozoa</li>
@ -577,36 +587,36 @@ Please <a href="https://gitlab.com/msberends/AMR/issues/new?issue%5Btitle%5D=EUC
<li>All ~15,000 previously accepted names of included (sub)species that have been taxonomically renamed</li>
<li>
<p>The responsible author(s) and year of scientific publication</p>
This data is updated annually - check the included version with the new function <code>catalogue_of_life_version()</code>.</li>
This data is updated annually - check the included version with the new function <code><a href="../reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code>.</li>
<li>Due to this change, some <code>mo</code> codes changed (e.g. <em>Streptococcus</em> changed from <code>B_STRPTC</code> to <code>B_STRPT</code>). A translation table is used internally to support older microorganism IDs, so users will not notice this difference.</li>
<li>New function <code>mo_rank()</code> for the taxonomic rank (genus, species, infraspecies, etc.)</li>
<li>New function <code>mo_url()</code> to get the direct URL of a species from the Catalogue of Life</li>
<li>New function <code><a href="../reference/mo_property.html">mo_rank()</a></code> for the taxonomic rank (genus, species, infraspecies, etc.)</li>
<li>New function <code><a href="../reference/mo_property.html">mo_url()</a></code> to get the direct URL of a species from the Catalogue of Life</li>
</ul>
</li>
<li>Support for data from <a href="https://whonet.org/">WHONET</a> and <a href="https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net">EARS-Net</a> (European Antimicrobial Resistance Surveillance Network):
<ul>
<li>Exported files from WHONET can be read and used in this package. For functions like <code>first_isolate()</code> and <code>eucast_rules()</code>, all parameters will be filled in automatically.</li>
<li>Exported files from WHONET can be read and used in this package. For functions like <code><a href="../reference/first_isolate.html">first_isolate()</a></code> and <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>, all parameters will be filled in automatically.</li>
<li>This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the <code>antibiotics</code> data set now contains a column <code>ears_net</code>.</li>
<li>The function <code>as.mo()</code> now knows all WHONET species abbreviations too, because almost 2,000 microbial abbreviations were added to the <code>microorganisms.codes</code> data set.</li>
<li>The function <code><a href="../reference/as.mo.html">as.mo()</a></code> now knows all WHONET species abbreviations too, because almost 2,000 microbial abbreviations were added to the <code>microorganisms.codes</code> data set.</li>
</ul>
</li>
<li>
<p>New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1"><span class="kw">filter_aminoglycosides</span>()</a>
<a class="sourceLine" id="cb10-2" data-line-number="2"><span class="kw">filter_carbapenems</span>()</a>
<a class="sourceLine" id="cb10-3" data-line-number="3"><span class="kw">filter_cephalosporins</span>()</a>
<a class="sourceLine" id="cb10-4" data-line-number="4"><span class="kw">filter_1st_cephalosporins</span>()</a>
<a class="sourceLine" id="cb10-5" data-line-number="5"><span class="kw">filter_2nd_cephalosporins</span>()</a>
<a class="sourceLine" id="cb10-6" data-line-number="6"><span class="kw">filter_3rd_cephalosporins</span>()</a>
<a class="sourceLine" id="cb10-7" data-line-number="7"><span class="kw">filter_4th_cephalosporins</span>()</a>
<a class="sourceLine" id="cb10-8" data-line-number="8"><span class="kw">filter_fluoroquinolones</span>()</a>
<a class="sourceLine" id="cb10-9" data-line-number="9"><span class="kw">filter_glycopeptides</span>()</a>
<a class="sourceLine" id="cb10-10" data-line-number="10"><span class="kw">filter_macrolides</span>()</a>
<a class="sourceLine" id="cb10-11" data-line-number="11"><span class="kw">filter_tetracyclines</span>()</a></code></pre></div>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1"><span class="kw"><a href="../reference/filter_ab_class.html">filter_aminoglycosides</a></span>()</a>
<a class="sourceLine" id="cb10-2" data-line-number="2"><span class="kw"><a href="../reference/filter_ab_class.html">filter_carbapenems</a></span>()</a>
<a class="sourceLine" id="cb10-3" data-line-number="3"><span class="kw"><a href="../reference/filter_ab_class.html">filter_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb10-4" data-line-number="4"><span class="kw"><a href="../reference/filter_ab_class.html">filter_1st_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb10-5" data-line-number="5"><span class="kw"><a href="../reference/filter_ab_class.html">filter_2nd_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb10-6" data-line-number="6"><span class="kw"><a href="../reference/filter_ab_class.html">filter_3rd_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb10-7" data-line-number="7"><span class="kw"><a href="../reference/filter_ab_class.html">filter_4th_cephalosporins</a></span>()</a>
<a class="sourceLine" id="cb10-8" data-line-number="8"><span class="kw"><a href="../reference/filter_ab_class.html">filter_fluoroquinolones</a></span>()</a>
<a class="sourceLine" id="cb10-9" data-line-number="9"><span class="kw"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>()</a>
<a class="sourceLine" id="cb10-10" data-line-number="10"><span class="kw"><a href="../reference/filter_ab_class.html">filter_macrolides</a></span>()</a>
<a class="sourceLine" id="cb10-11" data-line-number="11"><span class="kw"><a href="../reference/filter_ab_class.html">filter_tetracyclines</a></span>()</a></code></pre></div>
<p>The <code>antibiotics</code> data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set. For example:</p>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb11-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">filter_glycopeptides</span>(<span class="dt">result =</span> <span class="st">"R"</span>)</a>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb11-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>(<span class="dt">result =</span> <span class="st">"R"</span>)</a>
<a class="sourceLine" id="cb11-2" data-line-number="2"><span class="co"># Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R</span></a>
<a class="sourceLine" id="cb11-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">filter_glycopeptides</span>(<span class="dt">result =</span> <span class="st">"R"</span>, <span class="dt">scope =</span> <span class="st">"all"</span>)</a>
<a class="sourceLine" id="cb11-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/filter_ab_class.html">filter_glycopeptides</a></span>(<span class="dt">result =</span> <span class="st">"R"</span>, <span class="dt">scope =</span> <span class="st">"all"</span>)</a>
<a class="sourceLine" id="cb11-4" data-line-number="4"><span class="co"># Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is R</span></a></code></pre></div>
</li>
<li>
@ -618,33 +628,33 @@ This data is updated annually - check the included version with the new function
<a class="sourceLine" id="cb12-5" data-line-number="5">ab_certe -&gt;<span class="st"> </span><span class="kw">atc_certe</span>()</a>
<a class="sourceLine" id="cb12-6" data-line-number="6">ab_umcg -&gt;<span class="st"> </span><span class="kw">atc_umcg</span>()</a>
<a class="sourceLine" id="cb12-7" data-line-number="7">ab_tradenames -&gt;<span class="st"> </span><span class="kw">atc_tradenames</span>()</a></code></pre></div>
These functions use <code>as.atc()</code> internally. The old <code>atc_property</code> has been renamed <code>atc_online_property()</code>. This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class <code>atc</code> or must be coerable to this class. Properties of these classes should start with the same class name, analogous to <code>as.mo()</code> and e.g. <code>mo_genus</code>.</li>
<li>New functions <code>set_mo_source()</code> and <code>get_mo_source()</code> to use your own predefined MO codes as input for <code>as.mo()</code> and consequently all <code>mo_*</code> functions</li>
These functions use <code><a href="../reference/AMR-deprecated.html">as.atc()</a></code> internally. The old <code>atc_property</code> has been renamed <code><a href="../reference/atc_online.html">atc_online_property()</a></code>. This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class <code>atc</code> or must be coerable to this class. Properties of these classes should start with the same class name, analogous to <code><a href="../reference/as.mo.html">as.mo()</a></code> and e.g. <code>mo_genus</code>.</li>
<li>New functions <code><a href="../reference/mo_source.html">set_mo_source()</a></code> and <code><a href="../reference/mo_source.html">get_mo_source()</a></code> to use your own predefined MO codes as input for <code><a href="../reference/as.mo.html">as.mo()</a></code> and consequently all <code>mo_*</code> functions</li>
<li>Support for the upcoming <a href="https://dplyr.tidyverse.org"><code>dplyr</code></a> version 0.8.0</li>
<li>New function <code>guess_ab_col()</code> to find an antibiotic column in a table</li>
<li>New function <code>mo_failures()</code> to review values that could not be coerced to a valid MO code, using <code>as.mo()</code>. This latter function will now only show a maximum of 10 uncoerced values and will refer to <code>mo_failures()</code>.</li>
<li>New function <code>mo_uncertainties()</code> to review values that could be coerced to a valid MO code using <code>as.mo()</code>, but with uncertainty.</li>
<li>New function <code>mo_renamed()</code> to get a list of all returned values from <code>as.mo()</code> that have had taxonomic renaming</li>
<li>New function <code>age()</code> to calculate the (patients) age in years</li>
<li>New function <code>age_groups()</code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.</li>
<li>New function <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code> to find an antibiotic column in a table</li>
<li>New function <code><a href="../reference/as.mo.html">mo_failures()</a></code> to review values that could not be coerced to a valid MO code, using <code><a href="../reference/as.mo.html">as.mo()</a></code>. This latter function will now only show a maximum of 10 uncoerced values and will refer to <code><a href="../reference/as.mo.html">mo_failures()</a></code>.</li>
<li>New function <code><a href="../reference/as.mo.html">mo_uncertainties()</a></code> to review values that could be coerced to a valid MO code using <code><a href="../reference/as.mo.html">as.mo()</a></code>, but with uncertainty.</li>
<li>New function <code><a href="../reference/as.mo.html">mo_renamed()</a></code> to get a list of all returned values from <code><a href="../reference/as.mo.html">as.mo()</a></code> that have had taxonomic renaming</li>
<li>New function <code><a href="../reference/age.html">age()</a></code> to calculate the (patients) age in years</li>
<li>New function <code><a href="../reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.</li>
<li>
<p>New function <code>ggplot_rsi_predict()</code> as well as the base R <code><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> function can now be used for resistance prediction calculated with <code>resistance_predict()</code>:</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">x &lt;-<span class="st"> </span><span class="kw">resistance_predict</span>(septic_patients, <span class="dt">col_ab =</span> <span class="st">"amox"</span>)</a>
<p>New function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(septic_patients, <span class="dt">col_ab =</span> <span class="st">"amox"</span>)</a>
<a class="sourceLine" id="cb13-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot</a></span>(x)</a>
<a class="sourceLine" id="cb13-3" data-line-number="3"><span class="kw">ggplot_rsi_predict</span>(x)</a></code></pre></div>
<a class="sourceLine" id="cb13-3" data-line-number="3"><span class="kw"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>(x)</a></code></pre></div>
</li>
<li>
<p>Functions <code>filter_first_isolate()</code> and <code>filter_first_weighted_isolate()</code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">filter_first_isolate</span>(...)</a>
<p>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(...)</a>
<a class="sourceLine" id="cb14-2" data-line-number="2"><span class="co"># or</span></a>
<a class="sourceLine" id="cb14-3" data-line-number="3"><span class="kw">filter_first_isolate</span>(septic_patients, ...)</a></code></pre></div>
<a class="sourceLine" id="cb14-3" data-line-number="3"><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(septic_patients, ...)</a></code></pre></div>
<p>is equal to:</p>
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb15-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">only_firsts =</span> <span class="kw">first_isolate</span>(septic_patients, ...)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb15-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">only_firsts =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(septic_patients, ...)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb15-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span>(only_firsts <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb15-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span>only_firsts)</a></code></pre></div>
</li>
<li>New function <code>availability()</code> to check the number of available (non-empty) results in a <code>data.frame</code>
<li>New function <code><a href="../reference/availability.html">availability()</a></code> to check the number of available (non-empty) results in a <code>data.frame</code>
</li>
<li><p>New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the <em>G</em>-test and more. These are also available (and even easier readable) on our website: <a href="https://msberends.gitlab.io/AMR" class="uri">https://msberends.gitlab.io/AMR</a>.</p></li>
</ul>
@ -653,48 +663,48 @@ These functions use <code>as.atc()</code> internally. The old <code>atc_property
<h4 class="hasAnchor">
<a href="#changed-4" class="anchor"></a>Changed</h4>
<ul>
<li>Function <code>eucast_rules()</code>:
<li>Function <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:
<ul>
<li>Updated EUCAST Clinical breakpoints to <a href="http://www.eucast.org/clinical_breakpoints/">version 9.0 of 1 January 2019</a>, the data set <code>septic_patients</code> now reflects these changes</li>
<li>Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately</li>
<li>Emphasised in manual that penicillin is meant as benzylpenicillin (ATC <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE01">J01CE01</a>)</li>
<li>New info is returned when running this function, stating exactly what has been changed or added. Use <code>eucast_rules(..., verbose = TRUE)</code> to get a data set with all changed per bug and drug combination.</li>
<li>New info is returned when running this function, stating exactly what has been changed or added. Use <code><a href="../reference/eucast_rules.html">eucast_rules(..., verbose = TRUE)</a></code> to get a data set with all changed per bug and drug combination.</li>
</ul>
</li>
<li>Removed data sets <code>microorganisms.oldDT</code>, <code>microorganisms.prevDT</code>, <code>microorganisms.unprevDT</code> and <code>microorganismsDT</code> since they were no longer needed and only contained info already available in the <code>microorganisms</code> data set</li>
<li>Added 65 antibiotics to the <code>antibiotics</code> data set, from the <a href="http://ec.europa.eu/health/documents/community-register/html/atc.htm">Pharmaceuticals Community Register</a> of the European Commission</li>
<li>Removed columns <code>atc_group1_nl</code> and <code>atc_group2_nl</code> from the <code>antibiotics</code> data set</li>
<li>Functions <code>atc_ddd()</code> and <code>atc_groups()</code> have been renamed <code>atc_online_ddd()</code> and <code>atc_online_groups()</code>. The old functions are deprecated and will be removed in a future version.</li>
<li>Function <code>guess_mo()</code> is now deprecated in favour of <code>as.mo()</code> and will be removed in future versions</li>
<li>Function <code>guess_atc()</code> is now deprecated in favour of <code>as.atc()</code> and will be removed in future versions</li>
<li>Improvements for <code>as.mo()</code>:
<li>Functions <code>atc_ddd()</code> and <code>atc_groups()</code> have been renamed <code><a href="../reference/atc_online.html">atc_online_ddd()</a></code> and <code><a href="../reference/atc_online.html">atc_online_groups()</a></code>. The old functions are deprecated and will be removed in a future version.</li>
<li>Function <code>guess_mo()</code> is now deprecated in favour of <code><a href="../reference/as.mo.html">as.mo()</a></code> and will be removed in future versions</li>
<li>Function <code>guess_atc()</code> is now deprecated in favour of <code><a href="../reference/AMR-deprecated.html">as.atc()</a></code> and will be removed in future versions</li>
<li>Improvements for <code><a href="../reference/as.mo.html">as.mo()</a></code>:
<ul>
<li>
<p>Now handles incorrect spelling, like <code>i</code> instead of <code>y</code> and <code>f</code> instead of <code>ph</code>:</p>
<div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb16-1" data-line-number="1"><span class="co"># mo_fullname() uses as.mo() internally</span></a>
<a class="sourceLine" id="cb16-2" data-line-number="2"></a>
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="kw">mo_fullname</span>(<span class="st">"Sthafilokockus aaureuz"</span>)</a>
<a class="sourceLine" id="cb16-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"Sthafilokockus aaureuz"</span>)</a>
<a class="sourceLine" id="cb16-4" data-line-number="4"><span class="co">#&gt; [1] "Staphylococcus aureus"</span></a>
<a class="sourceLine" id="cb16-5" data-line-number="5"></a>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="kw">mo_fullname</span>(<span class="st">"S. klossi"</span>)</a>
<a class="sourceLine" id="cb16-6" data-line-number="6"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. klossi"</span>)</a>
<a class="sourceLine" id="cb16-7" data-line-number="7"><span class="co">#&gt; [1] "Staphylococcus kloosii"</span></a></code></pre></div>
</li>
<li>
<p>Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default <code>allow_uncertain = TRUE</code> is equal to uncertainty level 2. Run <code>?as.mo</code> for more info about these levels.</p>
<p>Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default <code>allow_uncertain = TRUE</code> is equal to uncertainty level 2. Run <code><a href="../reference/as.mo.html">?as.mo</a></code> for more info about these levels.</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" data-line-number="1"><span class="co"># equal:</span></a>
<a class="sourceLine" id="cb17-2" data-line-number="2"><span class="kw">as.mo</span>(..., <span class="dt">allow_uncertain =</span> <span class="ot">TRUE</span>)</a>
<a class="sourceLine" id="cb17-3" data-line-number="3"><span class="kw">as.mo</span>(..., <span class="dt">allow_uncertain =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb17-2" data-line-number="2"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="ot">TRUE</span>)</a>
<a class="sourceLine" id="cb17-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="dv">2</span>)</a>
<a class="sourceLine" id="cb17-4" data-line-number="4"></a>
<a class="sourceLine" id="cb17-5" data-line-number="5"><span class="co"># also equal:</span></a>
<a class="sourceLine" id="cb17-6" data-line-number="6"><span class="kw">as.mo</span>(..., <span class="dt">allow_uncertain =</span> <span class="ot">FALSE</span>)</a>
<a class="sourceLine" id="cb17-7" data-line-number="7"><span class="kw">as.mo</span>(..., <span class="dt">allow_uncertain =</span> <span class="dv">0</span>)</a></code></pre></div>
Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable results.</li>
<a class="sourceLine" id="cb17-6" data-line-number="6"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="ot">FALSE</span>)</a>
<a class="sourceLine" id="cb17-7" data-line-number="7"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(..., <span class="dt">allow_uncertain =</span> <span class="dv">0</span>)</a></code></pre></div>
Using <code><a href="../reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a></code> could lead to very unreliable results.</li>
<li>Implemented the latest publication of Becker <em>et al.</em> (2019), for categorising coagulase-negative <em>Staphylococci</em>
</li>
<li>All microbial IDs that found are now saved to a local file <code>~/.Rhistory_mo</code>. Use the new function <code>clean_mo_history()</code> to delete this file, which resets the algorithms.</li>
<li>
<p>Incoercible results will now be considered ‘unknown’, MO code <code>UNKNOWN</code>. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:</p>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb18-1" data-line-number="1"><span class="kw">mo_genus</span>(<span class="st">"qwerty"</span>, <span class="dt">language =</span> <span class="st">"es"</span>)</a>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb18-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(<span class="st">"qwerty"</span>, <span class="dt">language =</span> <span class="st">"es"</span>)</a>
<a class="sourceLine" id="cb18-2" data-line-number="2"><span class="co"># Warning: </span></a>
<a class="sourceLine" id="cb18-3" data-line-number="3"><span class="co"># one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.</span></a>
<a class="sourceLine" id="cb18-4" data-line-number="4"><span class="co">#&gt; [1] "(género desconocido)"</span></a></code></pre></div>
@ -712,7 +722,7 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<li>Console will return the percentage of uncoercable input</li>
</ul>
</li>
<li>Function <code>first_isolate()</code>:
<li>Function <code><a href="../reference/first_isolate.html">first_isolate()</a></code>:
<ul>
<li>Fixed a bug where distances between dates would not be calculated right - in the <code>septic_patients</code> data set this yielded a difference of 0.15% more isolates</li>
<li>Will now use a column named like “patid” for the patient ID (parameter <code>col_patientid</code>), when this parameter was left blank</li>
@ -724,38 +734,38 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<li>A note to the manual pages of the <code>portion</code> functions, that low counts can influence the outcome and that the <code>portion</code> functions may camouflage this, since they only return the portion (albeit being dependent on the <code>minimum</code> parameter)</li>
<li>Merged data sets <code>microorganisms.certe</code> and <code>microorganisms.umcg</code> into <code>microorganisms.codes</code>
</li>
<li>Function <code>mo_taxonomy()</code> now contains the kingdom too</li>
<li>Reduce false positives for <code>is.rsi.eligible()</code> using the new <code>threshold</code> parameter</li>
<li>New colours for <code>scale_rsi_colours()</code>
<li>Function <code><a href="../reference/mo_property.html">mo_taxonomy()</a></code> now contains the kingdom too</li>
<li>Reduce false positives for <code><a href="../reference/as.rsi.html">is.rsi.eligible()</a></code> using the new <code>threshold</code> parameter</li>
<li>New colours for <code><a href="../reference/ggplot_rsi.html">scale_rsi_colours()</a></code>
</li>
<li>Summaries of class <code>mo</code> will now return the top 3 and the unique count, e.g. using <code><a href="https://www.rdocumentation.org/packages/base/topics/summary">summary(mo)</a></code>
</li>
<li>Small text updates to summaries of class <code>rsi</code> and <code>mic</code>
</li>
<li>Function <code>as.rsi()</code>:
<li>Function <code><a href="../reference/as.rsi.html">as.rsi()</a></code>:
<ul>
<li>Now gives a warning when inputting MIC values</li>
<li>Now accepts high and low resistance: <code>"HIGH S"</code> will return <code>S</code>
</li>
</ul>
</li>
<li>Frequency tables (<code>freq()</code> function):
<li>Frequency tables (<code><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code> function):
<ul>
<li>
<p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb19-1" data-line-number="1"><span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span></a>
<a class="sourceLine" id="cb19-2" data-line-number="2"><span class="co"># OLD WAY</span></a>
<a class="sourceLine" id="cb19-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb19-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">genus =</span> <span class="kw">mo_genus</span>(mo)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb19-5" data-line-number="5"><span class="st"> </span><span class="kw">freq</span>(genus)</a>
<a class="sourceLine" id="cb19-4" data-line-number="4"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span>(<span class="dt">genus =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo)) <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb19-5" data-line-number="5"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(genus)</a>
<a class="sourceLine" id="cb19-6" data-line-number="6"><span class="co"># NEW WAY</span></a>
<a class="sourceLine" id="cb19-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb19-8" data-line-number="8"><span class="st"> </span><span class="kw">freq</span>(<span class="kw">mo_genus</span>(mo))</a>
<a class="sourceLine" id="cb19-8" data-line-number="8"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a>
<a class="sourceLine" id="cb19-9" data-line-number="9"></a>
<a class="sourceLine" id="cb19-10" data-line-number="10"><span class="co"># Even supports grouping variables:</span></a>
<a class="sourceLine" id="cb19-11" data-line-number="11">septic_patients <span class="op">%&gt;%</span></a>
<a class="sourceLine" id="cb19-12" data-line-number="12"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(gender) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb19-13" data-line-number="13"><span class="st"> </span><span class="kw">freq</span>(<span class="kw">mo_genus</span>(mo))</a></code></pre></div>
<a class="sourceLine" id="cb19-13" data-line-number="13"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a></code></pre></div>
</li>
<li>Header info is now available as a list, with the <code>header</code> function</li>
<li>The parameter <code>header</code> is now set to <code>TRUE</code> at default, even for markdown</li>
@ -770,11 +780,11 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<li>Fix for using <code><a href="https://dplyr.tidyverse.org/reference/select.html">select()</a></code> on frequency tables</li>
</ul>
</li>
<li>Function <code>scale_y_percent()</code> now contains the <code>limits</code> parameter</li>
<li>Automatic parameter filling for <code>mdro()</code>, <code>key_antibiotics()</code> and <code>eucast_rules()</code>
<li>Function <code><a href="../reference/ggplot_rsi.html">scale_y_percent()</a></code> now contains the <code>limits</code> parameter</li>
<li>Automatic parameter filling for <code><a href="../reference/mdro.html">mdro()</a></code>, <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> and <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>
</li>
<li>Updated examples for resistance prediction (<code>resistance_predict()</code> function)</li>
<li>Fix for <code>as.mic()</code> to support more values ending in (several) zeroes</li>
<li>Updated examples for resistance prediction (<code><a href="../reference/resistance_predict.html">resistance_predict()</a></code> function)</li>
<li>Fix for <code><a href="../reference/as.mic.html">as.mic()</a></code> to support more values ending in (several) zeroes</li>
<li>if using different lengths of pattern and x in <code>%like%</code>, it will now return the call</li>
</ul>
</div>
@ -830,30 +840,30 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<li>Fewer than 3 characters as input for <code>as.mo</code> will return NA</li>
<li>
<p>Function <code>as.mo</code> (and all <code>mo_*</code> wrappers) now supports genus abbreviations with “species” attached</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1"><span class="kw">as.mo</span>(<span class="st">"E. species"</span>) <span class="co"># B_ESCHR</span></a>
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="kw">mo_fullname</span>(<span class="st">"E. spp."</span>) <span class="co"># "Escherichia species"</span></a>
<a class="sourceLine" id="cb20-3" data-line-number="3"><span class="kw">as.mo</span>(<span class="st">"S. spp"</span>) <span class="co"># B_STPHY</span></a>
<a class="sourceLine" id="cb20-4" data-line-number="4"><span class="kw">mo_fullname</span>(<span class="st">"S. species"</span>) <span class="co"># "Staphylococcus species"</span></a></code></pre></div>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. species"</span>) <span class="co"># B_ESCHR</span></a>
<a class="sourceLine" id="cb20-2" data-line-number="2"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"E. spp."</span>) <span class="co"># "Escherichia species"</span></a>
<a class="sourceLine" id="cb20-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. spp"</span>) <span class="co"># B_STPHY</span></a>
<a class="sourceLine" id="cb20-4" data-line-number="4"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. species"</span>) <span class="co"># "Staphylococcus species"</span></a></code></pre></div>
</li>
<li>Added parameter <code>combine_IR</code> (TRUE/FALSE) to functions <code>portion_df</code> and <code>count_df</code>, to indicate that all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)</li>
<li>Fix for <code>portion_*(..., as_percent = TRUE)</code> when minimal number of isolates would not be met</li>
<li>Added parameter <code>also_single_tested</code> for <code>portion_*</code> and <code>count_*</code> functions to also include cases where not all antibiotics were tested but at least one of the tested antibiotics includes the target antimicribial interpretation, see <code>?portion</code>
<li>Added parameter <code>also_single_tested</code> for <code>portion_*</code> and <code>count_*</code> functions to also include cases where not all antibiotics were tested but at least one of the tested antibiotics includes the target antimicribial interpretation, see <code><a href="../reference/portion.html">?portion</a></code>
</li>
<li>Using <code>portion_*</code> functions now throws a warning when total available isolate is below parameter <code>minimum</code>
</li>
<li>Functions <code>as.mo</code>, <code>as.rsi</code>, <code>as.mic</code>, <code>as.atc</code> and <code>freq</code> will not set package name as attribute anymore</li>
<li>Frequency tables - <code>freq()</code>:
<li>Frequency tables - <code><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq()</a></code>:
<ul>
<li>
<p>Support for grouping variables, test with:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb21-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/group_by.html">group_by</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb21-3" data-line-number="3"><span class="st"> </span><span class="kw">freq</span>(gender)</a></code></pre></div>
<a class="sourceLine" id="cb21-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(gender)</a></code></pre></div>
</li>
<li>
<p>Support for (un)selecting columns:</p>
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb22-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb22-2" data-line-number="2"><span class="st"> </span><span class="kw">freq</span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb22-2" data-line-number="2"><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
<a class="sourceLine" id="cb22-3" data-line-number="3"><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(<span class="op">-</span>count, <span class="op">-</span>cum_count) <span class="co"># only get item, percent, cum_percent</span></a></code></pre></div>
</li>
<li>Check for <code><a href="https://www.rdocumentation.org/packages/hms/topics/Deprecated">hms::is.hms</a></code>
@ -934,16 +944,16 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
</li>
</ul>
<p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" data-line-number="1"><span class="kw">mo_gramstain</span>(<span class="st">"E. coli"</span>)</a>
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb23-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb23-2" data-line-number="2"><span class="co"># [1] "Gram negative"</span></a>
<a class="sourceLine" id="cb23-3" data-line-number="3"><span class="kw">mo_gramstain</span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"de"</span>) <span class="co"># German</span></a>
<a class="sourceLine" id="cb23-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"de"</span>) <span class="co"># German</span></a>
<a class="sourceLine" id="cb23-4" data-line-number="4"><span class="co"># [1] "Gramnegativ"</span></a>
<a class="sourceLine" id="cb23-5" data-line-number="5"><span class="kw">mo_gramstain</span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"es"</span>) <span class="co"># Spanish</span></a>
<a class="sourceLine" id="cb23-5" data-line-number="5"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"es"</span>) <span class="co"># Spanish</span></a>
<a class="sourceLine" id="cb23-6" data-line-number="6"><span class="co"># [1] "Gram negativo"</span></a>
<a class="sourceLine" id="cb23-7" data-line-number="7"><span class="kw">mo_fullname</span>(<span class="st">"S. group A"</span>, <span class="dt">language =</span> <span class="st">"pt"</span>) <span class="co"># Portuguese</span></a>
<a class="sourceLine" id="cb23-7" data-line-number="7"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. group A"</span>, <span class="dt">language =</span> <span class="st">"pt"</span>) <span class="co"># Portuguese</span></a>
<a class="sourceLine" id="cb23-8" data-line-number="8"><span class="co"># [1] "Streptococcus grupo A"</span></a></code></pre></div>
<p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1"><span class="kw">mo_gramstain</span>(<span class="st">"Esc blattae"</span>)</a>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"Esc blattae"</span>)</a>
<a class="sourceLine" id="cb24-2" data-line-number="2"><span class="co"># Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)</span></a>
<a class="sourceLine" id="cb24-3" data-line-number="3"><span class="co"># [1] "Gram negative"</span></a></code></pre></div>
</li>
@ -956,15 +966,15 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
</li>
<li>
<p>Functions <code>as.mo</code> and <code>is.mo</code> as replacements for <code>as.bactid</code> and <code>is.bactid</code> (since the <code>microoganisms</code> data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The <code>as.mo</code> function determines microbial IDs using intelligent rules:</p>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1"><span class="kw">as.mo</span>(<span class="st">"E. coli"</span>)</a>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb25-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. coli"</span>)</a>
<a class="sourceLine" id="cb25-2" data-line-number="2"><span class="co"># [1] B_ESCHR_COL</span></a>
<a class="sourceLine" id="cb25-3" data-line-number="3"><span class="kw">as.mo</span>(<span class="st">"MRSA"</span>)</a>
<a class="sourceLine" id="cb25-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"MRSA"</span>)</a>
<a class="sourceLine" id="cb25-4" data-line-number="4"><span class="co"># [1] B_STPHY_AUR</span></a>
<a class="sourceLine" id="cb25-5" data-line-number="5"><span class="kw">as.mo</span>(<span class="st">"S group A"</span>)</a>
<a class="sourceLine" id="cb25-5" data-line-number="5"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S group A"</span>)</a>
<a class="sourceLine" id="cb25-6" data-line-number="6"><span class="co"># [1] B_STRPTC_GRA</span></a></code></pre></div>
<p>And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb26-1" data-line-number="1">thousands_of_E_colis &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/rep">rep</a></span>(<span class="st">"E. coli"</span>, <span class="dv">25000</span>)</a>
<a class="sourceLine" id="cb26-2" data-line-number="2">microbenchmark<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw">as.mo</span>(thousands_of_E_colis), <span class="dt">unit =</span> <span class="st">"s"</span>)</a>
<a class="sourceLine" id="cb26-2" data-line-number="2">microbenchmark<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(thousands_of_E_colis), <span class="dt">unit =</span> <span class="st">"s"</span>)</a>
<a class="sourceLine" id="cb26-3" data-line-number="3"><span class="co"># Unit: seconds</span></a>
<a class="sourceLine" id="cb26-4" data-line-number="4"><span class="co"># min median max neval</span></a>
<a class="sourceLine" id="cb26-5" data-line-number="5"><span class="co"># 0.01817717 0.01843957 0.03878077 100</span></a></code></pre></div>
@ -997,9 +1007,9 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<p>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.:</p>
<div class="sourceCode" id="cb27"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb27-1" data-line-number="1"><span class="kw">ab_official</span>(<span class="st">"Bactroban"</span>)</a>
<a class="sourceLine" id="cb27-2" data-line-number="2"><span class="co"># [1] "Mupirocin"</span></a>
<a class="sourceLine" id="cb27-3" data-line-number="3"><span class="kw">ab_name</span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
<a class="sourceLine" id="cb27-3" data-line-number="3"><span class="kw"><a href="../reference/ab_property.html">ab_name</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
<a class="sourceLine" id="cb27-4" data-line-number="4"><span class="co"># [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin"</span></a>
<a class="sourceLine" id="cb27-5" data-line-number="5"><span class="kw">ab_atc</span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
<a class="sourceLine" id="cb27-5" data-line-number="5"><span class="kw"><a href="../reference/ab_property.html">ab_atc</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
<a class="sourceLine" id="cb27-6" data-line-number="6"><span class="co"># [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"</span></a></code></pre></div>
</li>
<li>For <code>first_isolate</code>, rows will be ignored when there’s no species available</li>
@ -1011,13 +1021,13 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
</li>
<li>
<p>Support for quasiquotation in the functions series <code>count_*</code> and <code>portions_*</code>, and <code>n_rsi</code>. This allows to check for more than 2 vectors or columns.</p>
<div class="sourceCode" id="cb28"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb28-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(amox, cipr) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">count_IR</span>()</a>
<div class="sourceCode" id="cb28"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb28-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span>(amox, cipr) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>()</a>
<a class="sourceLine" id="cb28-2" data-line-number="2"><span class="co"># which is the same as:</span></a>
<a class="sourceLine" id="cb28-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">count_IR</span>(amox, cipr)</a>
<a class="sourceLine" id="cb28-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>(amox, cipr)</a>
<a class="sourceLine" id="cb28-4" data-line-number="4"></a>
<a class="sourceLine" id="cb28-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">portion_S</span>(amcl)</a>
<a class="sourceLine" id="cb28-6" data-line-number="6">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">portion_S</span>(amcl, gent)</a>
<a class="sourceLine" id="cb28-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">portion_S</span>(amcl, gent, pita)</a></code></pre></div>
<a class="sourceLine" id="cb28-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl)</a>
<a class="sourceLine" id="cb28-6" data-line-number="6">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl, gent)</a>
<a class="sourceLine" id="cb28-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl, gent, pita)</a></code></pre></div>
</li>
<li>Edited <code>ggplot_rsi</code> and <code>geom_rsi</code> so they can cope with <code>count_df</code>. The new <code>fun</code> parameter has value <code>portion_df</code> at default, but can be set to <code>count_df</code>.</li>
<li>Fix for <code>ggplot_rsi</code> when the <code>ggplot2</code> package was not loaded</li>
@ -1032,11 +1042,11 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<li>
<p>Support for types (classes) list and matrix for <code>freq</code></p>
<div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb29-1" data-line-number="1">my_matrix =<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/with">with</a></span>(septic_patients, <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/matrix">matrix</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(age, gender), <span class="dt">ncol =</span> <span class="dv">2</span>))</a>
<a class="sourceLine" id="cb29-2" data-line-number="2"><span class="kw">freq</span>(my_matrix)</a></code></pre></div>
<a class="sourceLine" id="cb29-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(my_matrix)</a></code></pre></div>
<p>For lists, subsetting is possible:</p>
<div class="sourceCode" id="cb30"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb30-1" data-line-number="1">my_list =<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/list">list</a></span>(<span class="dt">age =</span> septic_patients<span class="op">$</span>age, <span class="dt">gender =</span> septic_patients<span class="op">$</span>gender)</a>
<a class="sourceLine" id="cb30-2" data-line-number="2">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">freq</span>(age)</a>
<a class="sourceLine" id="cb30-3" data-line-number="3">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">freq</span>(gender)</a></code></pre></div>
<a class="sourceLine" id="cb30-2" data-line-number="2">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(age)</a>
<a class="sourceLine" id="cb30-3" data-line-number="3">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq</a></span>(gender)</a></code></pre></div>
</li>
</ul>
</div>
@ -1078,7 +1088,7 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<ul>
<li>
<code>septic_patients %&gt;% select(tobr, gent) %&gt;% ggplot_rsi</code> will show portions of S, I and R immediately in a pretty plot</li>
<li>Support for grouped variables, see <code>?ggplot_rsi</code>
<li>Support for grouped variables, see <code><a href="../reference/ggplot_rsi.html">?ggplot_rsi</a></code>
</li>
</ul>
</li>
@ -1110,13 +1120,13 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<ul>
<li>A vignette to explain its usage</li>
<li>Support for <code>rsi</code> (antimicrobial resistance) to use as input</li>
<li>Support for <code>table</code> to use as input: <code>freq(table(x, y))</code>
<li>Support for <code>table</code> to use as input: <code><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq(table(x, y))</a></code>
</li>
<li>Support for existing functions <code>hist</code> and <code>plot</code> to use a frequency table as input: <code><a href="https://www.rdocumentation.org/packages/graphics/topics/hist">hist(freq(df$age))</a></code>
</li>
<li>Support for <code>as.vector</code>, <code>as.data.frame</code>, <code>as_tibble</code> and <code>format</code>
</li>
<li>Support for quasiquotation: <code>freq(mydata, mycolumn)</code> is the same as <code>mydata %&gt;% freq(mycolumn)</code>
<li>Support for quasiquotation: <code><a href="https://www.rdocumentation.org/packages/clean/topics/freq">freq(mydata, mycolumn)</a></code> is the same as <code>mydata %&gt;% freq(mycolumn)</code>
</li>
<li>Function <code>top_freq</code> function to return the top/below <em>n</em> items as vector</li>
<li>Header of frequency tables now also show Mean Absolute Deviaton (MAD) and Interquartile Range (IQR)</li>
@ -1148,14 +1158,14 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<li>Combined MIC/RSI values will now be coerced by the <code>rsi</code> and <code>mic</code> functions:
<ul>
<li>
<code>as.rsi("&lt;=0.002; S")</code> will return <code>S</code>
<code><a href="../reference/as.rsi.html">as.rsi("&lt;=0.002; S")</a></code> will return <code>S</code>
</li>
<li>
<code>as.mic("&lt;=0.002; S")</code> will return <code>&lt;=0.002</code>
<code><a href="../reference/as.mic.html">as.mic("&lt;=0.002; S")</a></code> will return <code>&lt;=0.002</code>
</li>
</ul>
</li>
<li>Now possible to coerce MIC values with a space between operator and value, i.e. <code>as.mic("&lt;= 0.002")</code> now works</li>
<li>Now possible to coerce MIC values with a space between operator and value, i.e. <code><a href="../reference/as.mic.html">as.mic("&lt;= 0.002")</a></code> now works</li>
<li>Classes <code>rsi</code> and <code>mic</code> do not add the attribute <code>package.version</code> anymore</li>
<li>Added <code>"groups"</code> option for <code>atc_property(..., property)</code>. It will return a vector of the ATC hierarchy as defined by the <a href="https://www.whocc.no/atc/structure_and_principles/">WHO</a>. The new function <code>atc_groups</code> is a convenient wrapper around this.</li>
<li>Build-in host check for <code>atc_property</code> as it requires the host set by <code>url</code> to be responsive</li>
@ -1206,7 +1216,7 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<li>Functions <code>BRMO</code> and <code>MRGN</code> are wrappers for Dutch and German guidelines, respectively</li>
</ul>
</li>
<li>New algorithm to determine weighted isolates, can now be <code>"points"</code> or <code>"keyantibiotics"</code>, see <code>?first_isolate</code>
<li>New algorithm to determine weighted isolates, can now be <code>"points"</code> or <code>"keyantibiotics"</code>, see <code><a href="../reference/first_isolate.html">?first_isolate</a></code>
</li>
<li>New print format for <code>tibble</code>s and <code>data.table</code>s</li>
</ul>
@ -1270,7 +1280,7 @@ Using <code>as.mo(..., allow_uncertain = 3)</code> could lead to very unreliable
<div id="tocnav">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#amr-0-7-1-9080">0.7.1.9080</a></li>
<li><a href="#amr-0-7-1-9081">0.7.1.9081</a></li>
<li><a href="#amr-0-7-1">0.7.1</a></li>
<li><a href="#amr-0-7-0">0.7.0</a></li>
<li><a href="#amr-0-6-1">0.6.1</a></li>

9
docs/pkgdown.yml
View File

@ -1,7 +1,14 @@
pandoc: 2.3.1
pkgdown: 1.3.0
pkgdown_sha: ~
articles: []
articles:
AMR: AMR.html
EUCAST: EUCAST.html
MDR: MDR.html
SPSS: SPSS.html
WHONET: WHONET.html
benchmarks: benchmarks.html
resistance_predict: resistance_predict.html
urls:
reference: https://msberends.gitlab.io/AMR/reference
article: https://msberends.gitlab.io/AMR/articles

56
docs/reference/as.mo.html
View File

@ -80,7 +80,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9079</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9081</span>
</span>
</div>
@ -305,41 +305,35 @@ A microorganism ID from this package (class: <code>mo</code>) typically looks li
<p><strong>Self-learning algoritm</strong> <br />
The <code>as.mo()</code> function gains experience from previously determined microorganism IDs and learns from it. This drastically improves both speed and reliability. Use <code>clear_mo_history()</code> to reset the algorithms. Only experience from your current <code>AMR</code> package version is used. This is done because in the future the taxonomic tree (which is included in this package) may change for any organism and it consequently has to rebuild its knowledge.</p>
<p>Usually, any guess after the first try runs 80-95% faster than the first try.</p>
<p><strong>Intelligent rules</strong> <br />
This function uses intelligent rules to help getting fast and logical results. It tries to find matches in this order:</p><ul>
<li><p>Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations</p></li>
<li><p>Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones (see <em>Microbial prevalence of pathogens in humans</em> below)</p></li>
<li><p>Taxonomic kingdom: it first searches in Bacteria, then Fungi, then Protozoa, then Archaea, then others</p></li>
<li><p>Breakdown of input values: from here it starts to breakdown input values to find possible matches</p></li>
<p>This resets with every update of this <code>AMR</code> package since results are saved to your local package library folder.</p>
<p><strong>Intelligent rules</strong> <br />
The <code>as.mo()</code> function uses several coercion rules for fast and logical results. It assesses the input matching criteria in the following order:</p><ul>
<li><p>Human pathogenic prevalence: the function starts with more prevalent microorganisms, followed by less prevalent ones;</p></li>
<li><p>Taxonomic kingdom: the function starts with determining Bacteria, then Fungi, then Protozoa, then others;</p></li>
<li><p>Breakdown of input values to identify possible matches.</p></li>
</ul>
<p>A couple of effects because of these rules:</p><ul>
<li><p><code>"E. coli"</code> will return the ID of <em>Escherichia coli</em> and not <em>Entamoeba coli</em>, although the latter would alphabetically come first</p></li>
<li><p><code>"H. influenzae"</code> will return the ID of <em>Haemophilus influenzae</em> and not <em>Haematobacter influenzae</em> for the same reason</p></li>
<li><p>Something like <code>"stau"</code> or <code>"S aur"</code> will return the ID of <em>Staphylococcus aureus</em> and not <em>Staphylococcus auricularis</em></p></li>
</ul><p>This means that looking up human pathogenic microorganisms takes less time than looking up human non-pathogenic microorganisms.</p>
<p><strong>Uncertain results</strong> <br />
The algorithm can additionally use three different levels of uncertainty to guess valid results. The default is <code>allow_uncertain = TRUE</code>, which is equal to uncertainty level 2. Using <code>allow_uncertain = FALSE</code> will skip all of these additional rules:</p><ul>
<li><p>(uncertainty level 1): It tries to look for only matching genera, previously accepted (but now invalid) taxonomic names and misspelled input</p></li>
<li><p>(uncertainty level 2): It removed parts between brackets, strips off words from the end one by one and re-evaluates the input with all previous rules</p></li>
<li><p>(uncertainty level 3): It strips off words from the start one by one and tries any part of the name</p></li>
<p>This will lead to the effect that e.g. <code>"E. coli"</code> (a highly prevalent microorganism found in humans) will return the microbial ID of <em>Escherichia coli</em> and not <em>Entamoeba coli</em> (a less prevalent microorganism in humans), although the latter would alphabetically come first. In addition, the <code>as.mo()</code> function can differentiate four levels of uncertainty to guess valid results:</p>
<ul>
<li><p>Uncertainty level 0: no additional rules are applied;</p></li>
<li><p>Uncertainty level 1: allow previously accepted (but now invalid) taxonomic names and minor spelling errors;</p></li>
<li><p>Uncertainty level 2: allow all of level 1, strip values between brackets, inverse the words of the input, strip off text elements from the end keeping at least two elements;</p></li>
<li><p>Uncertainty level 3: allow all of level 1 and 2, strip off text elements from the end, allow any part of a taxonomic name.</p></li>
</ul>
<p>You can also use e.g. <code>as.mo(..., allow_uncertain = 1)</code> to only allow up to level 1 uncertainty.</p>
<p>Examples:</p><ul>
<p>This leads to e.g.:</p>
<ul>
<li><p><code>"Streptococcus group B (known as S. agalactiae)"</code>. The text between brackets will be removed and a warning will be thrown that the result <em>Streptococcus group B</em> (<code>B_STRPT_GRPB</code>) needs review.</p></li>
<li><p><code>"S. aureus - please mind: MRSA"</code>. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result <em>Staphylococcus aureus</em> (<code>B_STPHY_AUR</code>) needs review.</p></li>
<li><p><code>"Fluoroquinolone-resistant Neisseria gonorrhoeae"</code>. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result <em>Neisseria gonorrhoeae</em> (<code>B_NESSR_GON</code>) needs review.</p></li>
<li><p><code>"S. aureus - please mind: MRSA"</code>. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result <em>Staphylococcus aureus</em> (<code>B_STPHY_AURS</code>) needs review.</p></li>
<li><p><code>"Fluoroquinolone-resistant Neisseria gonorrhoeae"</code>. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result <em>Neisseria gonorrhoeae</em> (<code>B_NESSR_GNRR</code>) needs review.</p></li>
</ul>
<p>Use <code>mo_failures()</code> to get a vector with all values that could not be coerced to a valid value.</p>
<p>Use <code>mo_uncertainties()</code> to get a data.frame with all values that were coerced to a valid value, but with uncertainty.</p>
<p>Use <code>mo_renamed()</code> to get a data.frame with all values that could be coerced based on an old, previously accepted taxonomic name.</p>
<p>The level of uncertainty can be set using the argument <code>allow_uncertain</code>. The default is <code>allow_uncertain = TRUE</code>, which is equal to uncertainty level 2. Using <code>allow_uncertain = FALSE</code> is equal to uncertainty level 0 and will skip all rules. You can also use e.g. <code>as.mo(..., allow_uncertain = 1)</code> to only allow up to level 1 uncertainty.</p>
<p>Use <code>mo_failures()</code> to get a vector with all values that could not be coerced to a valid value. <br />
Use <code>mo_uncertainties()</code> to get a <code>data.frame</code> with all values that were coerced to a valid value, but with uncertainty. <br />
Use <code>mo_renamed()</code> to get a <code>data.frame</code> with all values that could be coerced based on an old, previously accepted taxonomic name.</p>
<p><strong>Microbial prevalence of pathogens in humans</strong> <br />
The intelligent rules take into account microbial prevalence of pathogens in humans. It uses three groups and all (sub)species are in only one group. These groups are:</p><ul>
<li><p>1 (most prevalent): class is Gammaproteobacteria <strong>or</strong> genus is one of: <em>Enterococcus</em>, <em>Staphylococcus</em>, <em>Streptococcus</em>.</p></li>
<li><p>2: phylum is one of: Proteobacteria, Firmicutes, Actinobacteria, Sarcomastigophora <strong>or</strong> genus is one of: <em>Aspergillus</em>, <em>Bacteroides</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Chryseobacterium</em>, <em>Cryptococcus</em>, <em>Elisabethkingia</em>, <em>Flavobacterium</em>, <em>Fusobacterium</em>, <em>Giardia</em>, <em>Leptotrichia</em>, <em>Mycoplasma</em>, <em>Prevotella</em>, <em>Rhodotorula</em>, <em>Treponema</em>, <em>Trichophyton</em>, <em>Ureaplasma</em>.</p></li>
<li><p>3 (least prevalent): all others.</p></li>
</ul>
<p>Group 1 contains all common Gram positives and Gram negatives, like all Enterobacteriaceae and e.g. <em>Pseudomonas</em> and <em>Legionella</em>.</p>
<p>Group 2 contains probably less pathogenic microorganisms; all other members of phyla that were found in humans in the Northern Netherlands between 2001 and 2018.</p>
The intelligent rules consider the prevalence of microorganisms in humans grouped into three groups, which is available as the <code>prevalence</code> columns in the <code><a href='microorganisms.html'>microorganisms</a></code> and <code><a href='microorganisms.old.html'>microorganisms.old</a></code> data sets. The grouping into prevalence groups is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence.</p>
<p>Group 1 (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is <em>Enterococcus</em>, <em>Staphylococcus</em> or <em>Streptococcus</em>. This group consequently contains all common Gram-negative bacteria, such as <em>Pseudomonas</em> and <em>Legionella</em> and all species within the order Enterobacteriales.</p>
<p>Group 2 consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is <em>Aspergillus</em>, <em>Bacteroides</em>, <em>Candida</em>, <em>Capnocytophaga</em>, <em>Chryseobacterium</em>, <em>Cryptococcus</em>, <em>Elisabethkingia</em>, <em>Flavobacterium</em>, <em>Fusobacterium</em>, <em>Giardia</em>, <em>Leptotrichia</em>, <em>Mycoplasma</em>, <em>Prevotella</em>, <em>Rhodotorula</em>, <em>Treponema</em>, <em>Trichophyton</em> or <em>Ureaplasma</em>.</p>
<p>Group 3 (least prevalent microorganisms) consists of all other microorganisms.</p>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>

37
docs/reference/bug_drug_combinations.html
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@ -80,7 +80,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9067</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9081</span>
</span>
</div>
@ -234,11 +234,13 @@
</div>
<pre class="usage"><span class='fu'>bug_drug_combinations</span>(<span class='no'>x</span>, <span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>)
<pre class="usage"><span class='fu'>bug_drug_combinations</span>(<span class='no'>x</span>, <span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>,
<span class='kw'>FUN</span> <span class='kw'>=</span> <span class='no'>mo_shortname</span>, <span class='no'>...</span>)
<span class='co'># S3 method for bug_drug_combinations</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/format'>format</a></span>(<span class='no'>x</span>, <span class='kw'>combine_IR</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>add_ab_group</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='no'>...</span>)</pre>
<span class='kw'>add_ab_group</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>decimal.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"OutDec"</span>),
<span class='kw'>big.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/ifelse'>ifelse</a></span>(<span class='no'>decimal.mark</span> <span class='kw'>==</span> <span class='st'>","</span>, <span class='st'>"."</span>, <span class='st'>","</span>))</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
@ -255,6 +257,14 @@
<th>minimum</th>
<td><p>the minimum allowed number of available (tested) isolates. Any isolate count lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.</p></td>
</tr>
<tr>
<th>FUN</th>
<td><p>the function to call on the <code>mo</code> column to transform the microorganism IDs, defaults to <code><a href='mo_property.html'>mo_shortname</a></code></p></td>
</tr>
<tr>
<th>...</th>
<td><p>argumments passed on to <code>FUN</code></p></td>
</tr>
<tr>
<th>combine_IR</th>
<td><p>logical to indicate whether values R and I should be summed</p></td>
@ -264,8 +274,15 @@
<td><p>logical to indicate where the group of the antimicrobials must be included as a first column</p></td>
</tr>
<tr>
<th>...</th>
<td><p>argumments passed on to <code><a href='mo_property.html'>mo_name</a></code></p></td>
<th>decimal.mark</th>
<td><p>the character to be used to indicate the numeric
decimal point.</p></td>
</tr>
<tr>
<th>big.mark</th>
<td><p>character; if not empty used as mark between every
<code>big.interval</code> decimals <em>before</em> (hence <code>big</code>) the
decimal point.</p></td>
</tr>
</table>
@ -276,6 +293,7 @@
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The function <code>format</code> calculates the resistance per bug-drug combination. Use <code>combine_IR = FALSE</code> (default) to test R vs. S+I and <code>combine_IR = TRUE</code> to test R+I vs. S.</p>
<p>The language of the output can be overwritten with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>options(AMR_locale)</a></code>, please see <a href='translate.html'>translate</a>.</p>
<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
@ -288,6 +306,15 @@
<span class='no'>x</span> <span class='kw'>&lt;-</span> <span class='fu'>bug_drug_combinations</span>(<span class='no'>example_isolates</span>)
<span class='no'>x</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/format'>format</a></span>(<span class='no'>x</span>)
<span class='co'># Use FUN to change to transformation of microorganism codes</span>
<span class='no'>x</span> <span class='kw'>&lt;-</span> <span class='fu'>bug_drug_combinations</span>(<span class='no'>example_isolates</span>,
<span class='kw'>FUN</span> <span class='kw'>=</span> <span class='no'>mo_gramstain</span>)
<span class='no'>x</span> <span class='kw'>&lt;-</span> <span class='fu'>bug_drug_combinations</span>(<span class='no'>example_isolates</span>,
<span class='kw'>FUN</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>x</span>) <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/ifelse'>ifelse</a></span>(<span class='no'>x</span> <span class='kw'>==</span> <span class='st'>"B_ESCHR_COLI"</span>,
<span class='st'>"E. coli"</span>,
<span class='st'>"Others"</span>))
<span class='co'># }</span></pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="sidebar">

4
docs/reference/filter_ab_class.html
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@ -80,7 +80,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9080</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9081</span>
</span>
</div>
@ -287,7 +287,7 @@
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The <code>group</code> column in <code>antibiotics</code> data set will be searched for <code>ab_class</code> (case-insensitive). If no results are found, the <code>atc_group1</code> and <code>atc_group2</code> columns will be searched. Next, <code>x</code> will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set.</p>
<p>The <code>group</code> column in <code><a href='antibiotics.html'>antibiotics</a></code> data set will be searched for <code>ab_class</code> (case-insensitive). If no results are found, the <code>atc_group1</code> and <code>atc_group2</code> columns will be searched. Next, <code>x</code> will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>

2
docs/reference/index.html
View File

@ -78,7 +78,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9080</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9081</span>
</span>
</div>

2
docs/reference/microorganisms.codes.html
View File

@ -80,7 +80,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9080</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9081</span>
</span>
</div>

2
docs/reference/microorganisms.html
View File

@ -80,7 +80,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9080</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">0.7.1.9081</span>
</span>
</div>

56
man/as.mo.Rd
View File

@ -75,59 +75,47 @@ The \code{as.mo()} function gains experience from previously determined microorg
Usually, any guess after the first try runs 80-95\% faster than the first try.
This resets with every update of this \code{AMR} package since results are saved to your local package library folder.
\strong{Intelligent rules} \cr
This function uses intelligent rules to help getting fast and logical results. It tries to find matches in this order:
The \code{as.mo()} function uses several coercion rules for fast and logical results. It assesses the input matching criteria in the following order:
\itemize{
\item{Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations}
\item{Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones (see \emph{Microbial prevalence of pathogens in humans} below)}
\item{Taxonomic kingdom: it first searches in Bacteria, then Fungi, then Protozoa, then Archaea, then others}
\item{Breakdown of input values: from here it starts to breakdown input values to find possible matches}
\item{Human pathogenic prevalence: the function starts with more prevalent microorganisms, followed by less prevalent ones;}
\item{Taxonomic kingdom: the function starts with determining Bacteria, then Fungi, then Protozoa, then others;}
\item{Breakdown of input values to identify possible matches.}
}
This will lead to the effect that e.g. \code{"E. coli"} (a highly prevalent microorganism found in humans) will return the microbial ID of \emph{Escherichia coli} and not \emph{Entamoeba coli} (a less prevalent microorganism in humans), although the latter would alphabetically come first. In addition, the \code{as.mo()} function can differentiate four levels of uncertainty to guess valid results:
A couple of effects because of these rules:
\itemize{
\item{\code{"E. coli"} will return the ID of \emph{Escherichia coli} and not \emph{Entamoeba coli}, although the latter would alphabetically come first}
\item{\code{"H. influenzae"} will return the ID of \emph{Haemophilus influenzae} and not \emph{Haematobacter influenzae} for the same reason}
\item{Something like \code{"stau"} or \code{"S aur"} will return the ID of \emph{Staphylococcus aureus} and not \emph{Staphylococcus auricularis}}
}
This means that looking up human pathogenic microorganisms takes less time than looking up human non-pathogenic microorganisms.
\strong{Uncertain results} \cr
The algorithm can additionally use three different levels of uncertainty to guess valid results. The default is \code{allow_uncertain = TRUE}, which is equal to uncertainty level 2. Using \code{allow_uncertain = FALSE} will skip all of these additional rules:
\itemize{
\item{(uncertainty level 1): It tries to look for only matching genera, previously accepted (but now invalid) taxonomic names and misspelled input}
\item{(uncertainty level 2): It removed parts between brackets, strips off words from the end one by one and re-evaluates the input with all previous rules}
\item{(uncertainty level 3): It strips off words from the start one by one and tries any part of the name}
\item{Uncertainty level 0: no additional rules are applied;}
\item{Uncertainty level 1: allow previously accepted (but now invalid) taxonomic names and minor spelling errors;}
\item{Uncertainty level 2: allow all of level 1, strip values between brackets, inverse the words of the input, strip off text elements from the end keeping at least two elements;}
\item{Uncertainty level 3: allow all of level 1 and 2, strip off text elements from the end, allow any part of a taxonomic name.}
}
You can also use e.g. \code{as.mo(..., allow_uncertain = 1)} to only allow up to level 1 uncertainty.
This leads to e.g.:
Examples:
\itemize{
\item{\code{"Streptococcus group B (known as S. agalactiae)"}. The text between brackets will be removed and a warning will be thrown that the result \emph{Streptococcus group B} (\code{B_STRPT_GRPB}) needs review.}
\item{\code{"S. aureus - please mind: MRSA"}. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result \emph{Staphylococcus aureus} (\code{B_STPHY_AUR}) needs review.}
\item{\code{"Fluoroquinolone-resistant Neisseria gonorrhoeae"}. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result \emph{Neisseria gonorrhoeae} (\code{B_NESSR_GON}) needs review.}
\item{\code{"S. aureus - please mind: MRSA"}. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result \emph{Staphylococcus aureus} (\code{B_STPHY_AURS}) needs review.}
\item{\code{"Fluoroquinolone-resistant Neisseria gonorrhoeae"}. The first word will be stripped, after which the function will try to find a match. A warning will be thrown that the result \emph{Neisseria gonorrhoeae} (\code{B_NESSR_GNRR}) needs review.}
}
Use \code{mo_failures()} to get a vector with all values that could not be coerced to a valid value.
The level of uncertainty can be set using the argument \code{allow_uncertain}. The default is \code{allow_uncertain = TRUE}, which is equal to uncertainty level 2. Using \code{allow_uncertain = FALSE} is equal to uncertainty level 0 and will skip all rules. You can also use e.g. \code{as.mo(..., allow_uncertain = 1)} to only allow up to level 1 uncertainty.
Use \code{mo_uncertainties()} to get a data.frame with all values that were coerced to a valid value, but with uncertainty.
Use \code{mo_renamed()} to get a data.frame with all values that could be coerced based on an old, previously accepted taxonomic name.
Use \code{mo_failures()} to get a vector with all values that could not be coerced to a valid value. \cr
Use \code{mo_uncertainties()} to get a \code{data.frame} with all values that were coerced to a valid value, but with uncertainty. \cr
Use \code{mo_renamed()} to get a \code{data.frame} with all values that could be coerced based on an old, previously accepted taxonomic name.
\strong{Microbial prevalence of pathogens in humans} \cr
The intelligent rules take into account microbial prevalence of pathogens in humans. It uses three groups and all (sub)species are in only one group. These groups are:
\itemize{
\item{1 (most prevalent): class is Gammaproteobacteria \strong{or} genus is one of: \emph{Enterococcus}, \emph{Staphylococcus}, \emph{Streptococcus}.}
\item{2: phylum is one of: Proteobacteria, Firmicutes, Actinobacteria, Sarcomastigophora \strong{or} genus is one of: \emph{Aspergillus}, \emph{Bacteroides}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Chryseobacterium}, \emph{Cryptococcus}, \emph{Elisabethkingia}, \emph{Flavobacterium}, \emph{Fusobacterium}, \emph{Giardia}, \emph{Leptotrichia}, \emph{Mycoplasma}, \emph{Prevotella}, \emph{Rhodotorula}, \emph{Treponema}, \emph{Trichophyton}, \emph{Ureaplasma}.}
\item{3 (least prevalent): all others.}
}
The intelligent rules consider the prevalence of microorganisms in humans grouped into three groups, which is available as the \code{prevalence} columns in the \code{\link{microorganisms}} and \code{\link{microorganisms.old}} data sets. The grouping into prevalence groups is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence.
Group 1 contains all common Gram positives and Gram negatives, like all Enterobacteriaceae and e.g. \emph{Pseudomonas} and \emph{Legionella}.
Group 1 (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacteriales.
Group 2 contains probably less pathogenic microorganisms; all other members of phyla that were found in humans in the Northern Netherlands between 2001 and 2018.
Group 2 consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Aspergillus}, \emph{Bacteroides}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Chryseobacterium}, \emph{Cryptococcus}, \emph{Elisabethkingia}, \emph{Flavobacterium}, \emph{Fusobacterium}, \emph{Giardia}, \emph{Leptotrichia}, \emph{Mycoplasma}, \emph{Prevotella}, \emph{Rhodotorula}, \emph{Treponema}, \emph{Trichophyton} or \emph{Ureaplasma}.
Group 3 (least prevalent microorganisms) consists of all other microorganisms.
}
\section{Source}{

30
man/bug_drug_combinations.Rd
View File

@ -8,10 +8,12 @@
\strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
}
\usage{
bug_drug_combinations(x, col_mo = NULL, minimum = 30)
bug_drug_combinations(x, col_mo = NULL, minimum = 30,
FUN = mo_shortname, ...)
\method{format}{bug_drug_combinations}(x, combine_IR = FALSE,
add_ab_group = TRUE, ...)
add_ab_group = TRUE, decimal.mark = getOption("OutDec"),
big.mark = ifelse(decimal.mark == ",", ".", ","))
}
\arguments{
\item{x}{data with antibiotic columns, like e.g. \code{AMX} and \code{AMC}}
@ -20,17 +22,28 @@ bug_drug_combinations(x, col_mo = NULL, minimum = 30)
\item{minimum}{the minimum allowed number of available (tested) isolates. Any isolate count lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.}
\item{FUN}{the function to call on the \code{mo} column to transform the microorganism IDs, defaults to \code{\link{mo_shortname}}}
\item{...}{argumments passed on to \code{FUN}}
\item{combine_IR}{logical to indicate whether values R and I should be summed}
\item{add_ab_group}{logical to indicate where the group of the antimicrobials must be included as a first column}
\item{...}{argumments passed on to \code{\link{mo_name}}}
\item{decimal.mark}{the character to be used to indicate the numeric
decimal point.}
\item{big.mark}{character; if not empty used as mark between every
\code{big.interval} decimals \emph{before} (hence \code{big}) the
decimal point.}
}
\description{
Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use \code{format} on the result to prettify it to a printable format, see Examples.
}
\details{
The function \code{format} calculates the resistance per bug-drug combination. Use \code{combine_IR = FALSE} (default) to test R vs. S+I and \code{combine_IR = TRUE} to test R+I vs. S.
The function \code{format} calculates the resistance per bug-drug combination. Use \code{combine_IR = FALSE} (default) to test R vs. S+I and \code{combine_IR = TRUE} to test R+I vs. S.
The language of the output can be overwritten with \code{options(AMR_locale)}, please see \link{translate}.
}
\section{Read more on our website!}{
@ -42,5 +55,14 @@ On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://
x <- bug_drug_combinations(example_isolates)
x
format(x)
# Use FUN to change to transformation of microorganism codes
x <- bug_drug_combinations(example_isolates,
FUN = mo_gramstain)
x <- bug_drug_combinations(example_isolates,
FUN = function(x) ifelse(x == "B_ESCHR_COLI",
"E. coli",
"Others"))
}
}

3
tests/testthat/test-bug_drug_combinations.R
View File

@ -24,6 +24,7 @@ context("bug_drug_combinations.R")
test_that("bug_drug_combinations works", {
b <- suppressWarnings(bug_drug_combinations(example_isolates))
expect_s3_class(b, "bug_drug_combinations")
expect_message(print(b))
expect_output(print(b))
expect_true(is.data.frame(format(b)))
expect_true(is.data.frame(format(b, combine_IR = TRUE, add_ab_group = FALSE)))
})