#> Filtering on oxazolidinones: value in column `LNZ` (linezolid) is either "R", "S" or "I"
```
* Support for custom MDRO guidelines, using the new `custom_mdro_guideline()` function, please see `mdro()` for additional info
* Function `isolate_identifier()`, which will paste a microorganism code with all antimicrobial results of a data set into one string for each row. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available.
* `ggplot()` generics for classes `<mic>` and `<disk>`
* Function `mo_is_yeast()`, which determines whether a microorganism is a member of the taxonomic class Saccharomycetes or the taxonomic order Saccharomycetales:
```r
@ -57,7 +56,16 @@
* `is.rsi()` and `is.rsi.eligible()` now return a vector of `TRUE`/`FALSE` when the input is a data set, by iterating over all columns
* Using functions without setting a data set (e.g., `mo_is_gram_negative()`, `mo_is_gram_positive()`, `mo_is_intrinsic_resistant()`, `first_isolate()`, `mdro()`) now work with `dplyr`s `group_by()` again
* `first_isolate()` can be used with `group_by()` (also when using a dot `.` as input for the data) and now returns the names of the groups
* MIC values now allow for any mathematical processing, such as usage inside functions `min()`, `max()`, `range()`, and with binary operators (+, -, etc.). This also enables other functions, such as `fivenum()`.
* MIC values (see `as.mic()`) can now be used in any mathematical processing, such as usage inside functions `min()`, `max()`, `range()`, and with binary operators (+, -, etc.). This allows easy distribution analysis and fast filtering on MIC values:
* Updated the data set `microorganisms.codes` (which contains popular LIS and WHONET codes for microorganisms) for some species of *Mycobacterium* that previously incorrectly returned *M. africanum*
* WHONET code `"PNV"` will now correctly be interpreted as `PHN`, the antibiotic code for phenoxymethylpenicillin ('peni V')
* Fix for verbose output of `mdro(..., verbose = TRUE)` for German guideline (3MGRN and 4MGRN) and Dutch guideline (BRMO, only *P. aeruginosa*)
#' This function will paste the microorganism code with all antimicrobial results into one string for each row in a data set. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available.
#' @param cols_ab a character vector of column names of `x`, or (a combination with) an [antibiotic selector function]([ab_class()]), such as [carbapenems()] and [aminoglycosides()]
#' @rdname isolate_identifier
#' @export
#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # automatic selection of microorganism and antibiotics (i.e., all <rsi> columns, see ?as.rsi)
#' x <- isolate_identifier(example_isolates)
#'
#' # ignore microorganism codes, only use antimicrobial results
<spanclass="co">#> Filtering on oxazolidinones: value in column `LNZ` (linezolid) is either "R", "S" or "I"</span></code></pre></div>
</li>
<li><p>Support for custom MDRO guidelines, using the new <code><ahref="../reference/mdro.html">custom_mdro_guideline()</a></code> function, please see <code><ahref="../reference/mdro.html">mdro()</a></code> for additional info</p></li>
<li><p>Function <code><ahref="../reference/isolate_identifier.html">isolate_identifier()</a></code>, which will paste a microorganism code with all antimicrobial results of a data set into one string for each row. This is useful to compare isolates, e.g.between institutions or regions, when there is no genotyping available.</p></li>
<li><p><code>ggplot()</code> generics for classes <code><mic></code> and <code><disk></code></p></li>
<li>
<p>Function <code><ahref="../reference/mo_property.html">mo_is_yeast()</a></code>, which determines whether a microorganism is a member of the taxonomic class Saccharomycetes or the taxonomic order Saccharomycetales:</p>
@ -309,14 +308,16 @@
<h3class="hasAnchor">
<ahref="#changed"class="anchor"></a>Changed</h3>
<ul>
<li>Updated the bacterial taxonomy to 3 March 2021 (using <ahref="https://lpsn.dsmz.de">LSPN</a>)
<li>
<p>Updated the bacterial taxonomy to 3 March 2021 (using <ahref="https://lpsn.dsmz.de">LSPN</a>)</p>
<ul>
<li>Added 3,372 new species and 1,523 existing species became synomyms</li>
<li>The URL of a bacterial species (<code><ahref="../reference/mo_property.html">mo_url()</a></code>) will now lead to <ahref="https://lpsn.dsmz.de"class="uri">https://lpsn.dsmz.de</a>
</li>
</ul>
</li>
<li>Big update for plotting classes <code>rsi</code>, <code><mic></code>, and <code><disk></code>:
<li>
<p>Big update for plotting classes <code>rsi</code>, <code><mic></code>, and <code><disk></code>:</p>
<ul>
<li>Plotting of MIC and disk diffusion values now support interpretation colouring if you supply the microorganism and antimicrobial agent</li>
<li>All colours were updated to colour-blind friendly versions for values R, S and I for all plot methods (also applies to tibble printing)</li>
@ -324,34 +325,37 @@
<li>Plotting is now possible with base R using <code><ahref="../reference/plot.html">plot()</a></code> and with ggplot2 using <code>ggplot()</code> on any vector of MIC and disk diffusion values</li>
</ul>
</li>
<li><p><code><ahref="../reference/as.rsi.html">is.rsi()</a></code> and <code><ahref="../reference/as.rsi.html">is.rsi.eligible()</a></code> now return a vector of <code>TRUE</code>/<code>FALSE</code> when the input is a data set, by iterating over all columns</p></li>
<li><p>Using functions without setting a data set (e.g., <code><ahref="../reference/mo_property.html">mo_is_gram_negative()</a></code>, <code><ahref="../reference/mo_property.html">mo_is_gram_positive()</a></code>, <code><ahref="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>, <code><ahref="../reference/first_isolate.html">first_isolate()</a></code>, <code><ahref="../reference/mdro.html">mdro()</a></code>) now work with <code>dplyr</code>s <code><ahref="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> again</p></li>
<li><p><code><ahref="../reference/first_isolate.html">first_isolate()</a></code> can be used with <code><ahref="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> (also when using a dot <code>.</code> as input for the data) and now returns the names of the groups</p></li>
<li>
<code><ahref="../reference/as.rsi.html">is.rsi()</a></code> and <code><ahref="../reference/as.rsi.html">is.rsi.eligible()</a></code> now return a vector of <code>TRUE</code>/<code>FALSE</code> when the input is a data set, by iterating over all columns</li>
<li>Using functions without setting a data set (e.g., <code><ahref="../reference/mo_property.html">mo_is_gram_negative()</a></code>, <code><ahref="../reference/mo_property.html">mo_is_gram_positive()</a></code>, <code><ahref="../reference/mo_property.html">mo_is_intrinsic_resistant()</a></code>, <code><ahref="../reference/first_isolate.html">first_isolate()</a></code>, <code><ahref="../reference/mdro.html">mdro()</a></code>) now work with <code>dplyr</code>s <code><ahref="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> again</li>
<li>
<code><ahref="../reference/first_isolate.html">first_isolate()</a></code> can be used with <code><ahref="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code> (also when using a dot <code>.</code> as input for the data) and now returns the names of the groups</li>
<li>MIC values now allow for any mathematical processing, such as usage inside functions <code><ahref="https://rdrr.io/r/base/Extremes.html">min()</a></code>, <code><ahref="https://rdrr.io/r/base/Extremes.html">max()</a></code>, <code><ahref="https://rdrr.io/r/base/range.html">range()</a></code>, and with binary operators (+, -, etc.). This also enables other functions, such as <code><ahref="https://rdrr.io/r/stats/fivenum.html">fivenum()</a></code>.</li>
<li>Updated the data set <code>microorganisms.codes</code> (which contains popular LIS and WHONET codes for microorganisms) for some species of <em>Mycobacterium</em> that previously incorrectly returned <em>M. africanum</em>
<p>MIC values (see <code><ahref="../reference/as.mic.html">as.mic()</a></code>) can now be used in any mathematical processing, such as usage inside functions <code><ahref="https://rdrr.io/r/base/Extremes.html">min()</a></code>, <code><ahref="https://rdrr.io/r/base/Extremes.html">max()</a></code>, <code><ahref="https://rdrr.io/r/base/range.html">range()</a></code>, and with binary operators (+, -, etc.). This allows easy distribution analysis and fast filtering on MIC values:</p>
<li>WHONET code <code>"PNV"</code> will now correctly be interpreted as <code>PHN</code>, the antibiotic code for phenoxymethylpenicillin (‘peni V’)</li>
<li>Fix for verbose output of <code><ahref="../reference/mdro.html">mdro(..., verbose = TRUE)</a></code> for German guideline (3MGRN and 4MGRN) and Dutch guideline (BRMO, only <em>P. aeruginosa</em>)</li>
<li>
<code><ahref="../reference/as.rsi.html">is.rsi.eligible()</a></code> now detects if the column name resembles an antibiotic name or code and now returns <code>TRUE</code> immediately if the input contains any of the values “R”, “S” or “I”. This drastically improves speed, also for a lot of other functions that rely on automatic determination of antibiotic columns.</li>
<li>Functions <code><ahref="../reference/get_episode.html">get_episode()</a></code> and <code><ahref="../reference/get_episode.html">is_new_episode()</a></code> now support less than a day as value for argument <code>episode_days</code> (e.g., to include one patient/test per hour)</li>
<li>Argument <code>ampc_cephalosporin_resistance</code> in <code><ahref="../reference/eucast_rules.html">eucast_rules()</a></code> now also applies to value “I” (not only “S”)</li>
<li>Functions <code><ahref="https://rdrr.io/r/base/print.html">print()</a></code> and <code><ahref="https://rdrr.io/r/base/summary.html">summary()</a></code> on a Principal Components Analysis object (<code><ahref="../reference/pca.html">pca()</a></code>) now print additional group info if the original data was grouped using <code><ahref="https://dplyr.tidyverse.org/reference/group_by.html">dplyr::group_by()</a></code>
</li>
<li>Improved speed and reliability of <code><ahref="../reference/guess_ab_col.html">guess_ab_col()</a></code>. As this also internally improves the reliability of <code><ahref="../reference/first_isolate.html">first_isolate()</a></code> and <code><ahref="../reference/mdro.html">mdro()</a></code>, this might have a slight impact on the results of those functions.</li>
<li>Fix for <code><ahref="../reference/mo_property.html">mo_name()</a></code> when used in other languages than English</li>
<li>The <code><ahref="../reference/like.html">like()</a></code> function (and its fast alias <code><ahref="../reference/like.html">%like%</a></code>) now always use Perl compatibility, improving speed for many functions in this package (e.g., <code><ahref="../reference/as.mo.html">as.mo()</a></code> is now up to 4 times faster)</li>
<li>
<em>Staphylococcus cornubiensis</em> is now correctly categorised as coagulase-positive</li>
<li>
<code><ahref="../reference/random.html">random_disk()</a></code> and <code><ahref="../reference/random.html">random_mic()</a></code> now have an expanded range in their randomisation</li>
<li>Support for GISA (glycopeptide-intermediate <em>S. aureus</em>), so e.g.<code><ahref="../reference/mo_property.html">mo_genus("GISA")</a></code> will return <code>"Staphylococcus"</code>
</li>
<li>Added translations of German and Spanish for more than 200 antimicrobial drugs</li>
<li>Speed improvement for <code><ahref="../reference/as.ab.html">as.ab()</a></code> when the input is an official name or ATC code</li>
<li>Added argument <code>include_untested_rsi</code> to the <code><ahref="../reference/first_isolate.html">first_isolate()</a></code> functions (defaults to <code>TRUE</code> to keep existing behaviour), to be able to exclude rows where all R/SI values (class <code><rsi></code>, see <code><ahref="../reference/as.rsi.html">as.rsi()</a></code>) are empty</li>
<li><p>Updated the data set <code>microorganisms.codes</code> (which contains popular LIS and WHONET codes for microorganisms) for some species of <em>Mycobacterium</em> that previously incorrectly returned <em>M. africanum</em></p></li>
<li><p>WHONET code <code>"PNV"</code> will now correctly be interpreted as <code>PHN</code>, the antibiotic code for phenoxymethylpenicillin (‘peni V’)</p></li>
<li><p>Fix for verbose output of <code><ahref="../reference/mdro.html">mdro(..., verbose = TRUE)</a></code> for German guideline (3MGRN and 4MGRN) and Dutch guideline (BRMO, only <em>P. aeruginosa</em>)</p></li>
<li><p><code><ahref="../reference/as.rsi.html">is.rsi.eligible()</a></code> now detects if the column name resembles an antibiotic name or code and now returns <code>TRUE</code> immediately if the input contains any of the values “R”, “S” or “I”. This drastically improves speed, also for a lot of other functions that rely on automatic determination of antibiotic columns.</p></li>
<li><p>Functions <code><ahref="../reference/get_episode.html">get_episode()</a></code> and <code><ahref="../reference/get_episode.html">is_new_episode()</a></code> now support less than a day as value for argument <code>episode_days</code> (e.g., to include one patient/test per hour)</p></li>
<li><p>Argument <code>ampc_cephalosporin_resistance</code> in <code><ahref="../reference/eucast_rules.html">eucast_rules()</a></code> now also applies to value “I” (not only “S”)</p></li>
<li><p>Functions <code><ahref="https://rdrr.io/r/base/print.html">print()</a></code> and <code><ahref="https://rdrr.io/r/base/summary.html">summary()</a></code> on a Principal Components Analysis object (<code><ahref="../reference/pca.html">pca()</a></code>) now print additional group info if the original data was grouped using <code><ahref="https://dplyr.tidyverse.org/reference/group_by.html">dplyr::group_by()</a></code></p></li>
<li><p>Improved speed and reliability of <code><ahref="../reference/guess_ab_col.html">guess_ab_col()</a></code>. As this also internally improves the reliability of <code><ahref="../reference/first_isolate.html">first_isolate()</a></code> and <code><ahref="../reference/mdro.html">mdro()</a></code>, this might have a slight impact on the results of those functions.</p></li>
<li><p>Fix for <code><ahref="../reference/mo_property.html">mo_name()</a></code> when used in other languages than English</p></li>
<li><p>The <code><ahref="../reference/like.html">like()</a></code> function (and its fast alias <code><ahref="../reference/like.html">%like%</a></code>) now always use Perl compatibility, improving speed for many functions in this package (e.g., <code><ahref="../reference/as.mo.html">as.mo()</a></code> is now up to 4 times faster)</p></li>
<li><p><em>Staphylococcus cornubiensis</em> is now correctly categorised as coagulase-positive</p></li>
<li><p><code><ahref="../reference/random.html">random_disk()</a></code> and <code><ahref="../reference/random.html">random_mic()</a></code> now have an expanded range in their randomisation</p></li>
<li><p>Support for GISA (glycopeptide-intermediate <em>S. aureus</em>), so e.g.<code><ahref="../reference/mo_property.html">mo_genus("GISA")</a></code> will return <code>"Staphylococcus"</code></p></li>
<li><p>Added translations of German and Spanish for more than 200 antimicrobial drugs</p></li>
<li><p>Speed improvement for <code><ahref="../reference/as.ab.html">as.ab()</a></code> when the input is an official name or ATC code</p></li>
<li><p>Added argument <code>include_untested_rsi</code> to the <code><ahref="../reference/first_isolate.html">first_isolate()</a></code> functions (defaults to <code>TRUE</code> to keep existing behaviour), to be able to exclude rows where all R/SI values (class <code><rsi></code>, see <code><ahref="../reference/as.rsi.html">as.rsi()</a></code>) are empty</p></li>
</ul>
</div>
<divid="other"class="section level3">
@ -374,7 +378,7 @@
<ul>
<li>
<p>Functions <code><ahref="../reference/get_episode.html">get_episode()</a></code> and <code><ahref="../reference/get_episode.html">is_new_episode()</a></code> to determine (patient) episodes which are not necessarily based on microorganisms. The <code><ahref="../reference/get_episode.html">get_episode()</a></code> function returns the index number of the episode per group, while the <code><ahref="../reference/get_episode.html">is_new_episode()</a></code> function returns values <code>TRUE</code>/<code>FALSE</code> to indicate whether an item in a vector is the start of a new episode. They also support <code>dplyr</code>s grouping (i.e.using <code><ahref="https://dplyr.tidyverse.org/reference/group_by.html">group_by()</a></code>):</p>
<spanclass="co"># to select first isolates that are Gram-negative </span>
<spanclass="co"># and view results of cephalosporins and aminoglycosides:</span>
@ -440,7 +444,7 @@
</li>
<li>
<p>For antibiotic selection functions (such as <code><ahref="../reference/antibiotic_class_selectors.html">cephalosporins()</a></code>, <code><ahref="../reference/antibiotic_class_selectors.html">aminoglycosides()</a></code>) to select columns based on a certain antibiotic group, the dependency on the <code>tidyselect</code> package was removed, meaning that they can now also be used without the need to have this package installed and now also work in base R function calls (they rely on R 3.2 or later):</p>
<p>Data set <code>intrinsic_resistant</code>. This data set contains all bug-drug combinations where the ‘bug’ is intrinsic resistant to the ‘drug’ according to the latest EUCAST insights. It contains just two columns: <code>microorganism</code> and <code>antibiotic</code>.</p>
<p>Curious about which enterococci are actually intrinsic resistant to vancomycin?</p>
<p>Support for using <code>dplyr</code>’s <code><ahref="https://dplyr.tidyverse.org/reference/across.html">across()</a></code> to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.</p>
<p>Added intelligent data cleaning to <code><ahref="../reference/as.disk.html">as.disk()</a></code>, so numbers can also be extracted from text and decimal numbers will always be rounded up:</p>
<li><p>Function <code><ahref="../reference/ab_from_text.html">ab_from_text()</a></code> to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g.health care records, which also corrects for misspelling since it uses <code><ahref="../reference/as.ab.html">as.ab()</a></code> internally</p></li>
<li>
<p><ahref="https://tidyselect.r-lib.org/reference/language.html">Tidyverse selection helpers</a> for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like <code><ahref="https://dplyr.tidyverse.org/reference/select.html">dplyr::select()</a></code> and <code><ahref="https://tidyr.tidyverse.org/reference/pivot_longer.html">tidyr::pivot_longer()</a></code>:</p>
@ -782,7 +786,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline</p></li>
<li>
<p>Interpretation from MIC values (and disk zones) to R/SI can now be used with <code><ahref="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at()</a></code> of the <code>dplyr</code> package:</p>
<spanclass="fu"><ahref="https://dplyr.tidyverse.org/reference/mutate_all.html">mutate_at</a></span><spanclass="op">(</span><spanclass="fu"><ahref="https://dplyr.tidyverse.org/reference/vars.html">vars</a></span><spanclass="op">(</span><spanclass="va">antibiotic1</span><spanclass="op">:</span><spanclass="va">antibiotic25</span><spanclass="op">)</span>, <spanclass="va">as.rsi</span>, mo <spanclass="op">=</span><spanclass="st">"E. coli"</span><spanclass="op">)</span>
@ -811,7 +815,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Support for LOINC codes in the <code>antibiotics</code> data set. Use <code><ahref="../reference/ab_property.html">ab_loinc()</a></code> to retrieve LOINC codes, or use a LOINC code for input in any <code>ab_*</code> function:</p>
@ -822,7 +826,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>Support for SNOMED CT codes in the <code>microorganisms</code> data set. Use <code><ahref="../reference/mo_property.html">mo_snomed()</a></code> to retrieve SNOMED codes, or use a SNOMED code for input in any <code>mo_*</code> function:</p>
@ -905,7 +909,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Functions <code><ahref="../reference/proportion.html">susceptibility()</a></code> and <code><ahref="../reference/proportion.html">resistance()</a></code> as aliases of <code><ahref="../reference/proportion.html">proportion_SI()</a></code> and <code><ahref="../reference/proportion.html">proportion_R()</a></code>, respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.</p>
@ -934,7 +938,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>More intelligent way of coping with some consonants like “l” and “r”</p></li>
<li>
<p>Added a score (a certainty percentage) to <code><ahref="../reference/as.mo.html">mo_uncertainties()</a></code>, that is calculated using the <ahref="https://en.wikipedia.org/wiki/Levenshtein_distance">Levenshtein distance</a>:</p>
@ -993,14 +997,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<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 argument <code>include_unknown</code>:</p>
<p>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.</p>
</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>
@ -1025,7 +1029,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Function <code><ahref="../reference/bug_drug_combinations.html">bug_drug_combinations()</a></code> to quickly get a <code>data.frame</code> with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with <code><ahref="../reference/mo_property.html">mo_shortname()</a></code> at default:</p>
<spanclass="co">#> NOTE: Use 'format()' on this result to get a publicable/printable format.</span></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><ahref="https://rdrr.io/r/base/format.html">format()</a></code> function:</p>
<p>Additional way to calculate co-resistance, i.e.when using multiple antimicrobials as input for <code>portion_*</code> functions or <code>count_*</code> functions. This can be used to determine the empiric susceptibility of a combination therapy. A new argument <code>only_all_tested</code> (<strong>which defaults to <code>FALSE</code></strong>) replaces the old <code>also_single_tested</code> and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the <code>portion</code> and <code>count</code> help pages), where the %SI is being determined:</p>
@ -1076,7 +1080,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p><code>tibble</code> printing support for classes <code>rsi</code>, <code>mic</code>, <code>disk</code>, <code>ab</code><code>mo</code>. When using <code>tibble</code>s containing antimicrobial columns, values <code>S</code> will print in green, values <code>I</code> will print in yellow and values <code>R</code> will print in red. Microbial IDs (class <code>mo</code>) will emphasise on the genus and species, not on the kingdom.</p>
@ -1159,7 +1163,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Function <code><ahref="../reference/proportion.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><ahref="../reference/count.html">count_df()</a></code> and <code>portion_df()</code> to immediately show resistance percentages and number of available isolates:</p>
<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>
@ -1430,7 +1434,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>New function <code><ahref="../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 AMR data analysis per age group.</p></li>
<li>
<p>New function <code><ahref="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><ahref="../reference/plot.html">plot()</a></code> function can now be used for resistance prediction calculated with <code><ahref="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
@ -1438,13 +1442,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
<li>
<p>Functions <code><ahref="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><ahref="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
@ -1489,7 +1493,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</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><ahref="../reference/as.mo.html">?as.mo</a></code> for more info about these levels.</p>
@ -1504,7 +1508,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>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.</p></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>
<spanclass="fu"><ahref="../reference/mo_property.html">mo_genus</a></span><spanclass="op">(</span><spanclass="st">"qwerty"</span>, language <spanclass="op">=</span><spanclass="st">"es"</span><spanclass="op">)</span>
<spanclass="co"># Warning: </span>
@ -1554,7 +1558,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<li>
<p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
@ -1754,7 +1758,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<spanclass="fu"><ahref="../reference/mo_property.html">mo_fullname</a></span><spanclass="op">(</span><spanclass="st">"S. group A"</span>, language <spanclass="op">=</span><spanclass="st">"pt"</span><spanclass="op">)</span><spanclass="co"># Portuguese</span>
<spanclass="co"># [1] "Streptococcus grupo A"</span></code></pre></div>
<p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
<spanclass="co"># Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)</span>
@ -1769,7 +1773,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Function <code>is.rsi.eligible</code> to check for columns that have valid antimicrobial results, but do not have the <code>rsi</code> class yet. Transform the columns of your raw data with: <code>data %>% mutate_if(is.rsi.eligible, as.rsi)</code></p></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>
<spanclass="fu">microbenchmark</span><spanclass="fu">::</span><spanclass="fu"><ahref="https://rdrr.io/pkg/microbenchmark/man/microbenchmark.html">microbenchmark</a></span><spanclass="op">(</span><spanclass="fu"><ahref="../reference/as.mo.html">as.mo</a></span><spanclass="op">(</span><spanclass="va">thousands_of_E_colis</span><spanclass="op">)</span>, unit <spanclass="op">=</span><spanclass="st">"s"</span><spanclass="op">)</span>
@ -1812,7 +1816,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</p></li>
<li>
<p>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.:</p>
@ -1829,7 +1833,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Added arguments <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code></p></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>
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">1.5.0.9032</span>
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">1.5.0.9040</span>
</span>
</div>
@ -429,7 +429,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<p>On our website <ahref='https://msberends.github.io/AMR/'>https://msberends.github.io/AMR/</a> you can find <ahref='https://msberends.github.io/AMR/articles/AMR.html'>a comprehensive tutorial</a> about how to conduct AMR data analysis, the <ahref='https://msberends.github.io/AMR/reference/'>complete documentation of all functions</a> and <ahref='https://msberends.github.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>. As we would like to better understand the backgrounds and needs of our users, please <ahref='https://msberends.github.io/AMR/survey.html'>participate in our survey</a>!</p>
\item{x}{data with antibiotic columns, such as \code{amox}, \code{AMX} and \code{AMC}}
\item{col_mo}{column name of the IDs of the microorganisms (see \code{\link[=as.mo]{as.mo()}}), defaults to the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.}
\item{cols_ab}{a character vector of column names of \code{x}, or (a combination with) an \href{[ab_class()]}{antibiotic selector function}, such as \code{\link[=carbapenems]{carbapenems()}} and \code{\link[=aminoglycosides]{aminoglycosides()}}}
\item{target}{\R object.}
\item{current}{other \R object, to be compared with \code{target}.}
\item{ignore_empty_results}{a logical to indicate whether empty results must be ignored, so that only values R, S and I will be compared}
\item{...}{column name of an antibiotic, see section \emph{Antibiotics} below}
}
\description{
This function will paste the microorganism code with all antimicrobial results into one string for each row in a data set. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available.
The \link[=lifecycle]{lifecycle} of this function is \strong{experimental}. An experimental function is in early stages of development. The unlying code might be changing frequently. Experimental functions might be removed without deprecation, so you are generally best off waiting until a function is more mature before you use it in production code. Experimental functions are only available in development versions of this \code{AMR} package and will thus not be included in releases that are submitted to CRAN, since such functions have not yet matured enough.
}
\section{Read more on Our Website!}{
On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
}
\examples{
# automatic selection of microorganism and antibiotics (i.e., all <rsi> columns, see ?as.rsi)
x <- isolate_identifier(example_isolates)
# ignore microorganism codes, only use antimicrobial results
