* Functions `is_gram_negative()` and `is_gram_positive()` as wrappers around `mo_gramstain()`. They always return `TRUE` or `FALSE`, thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
* Functions `is_gram_negative()` and `is_gram_positive()` as wrappers around `mo_gramstain()`. They always return `TRUE` or `FALSE` (except when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria. If you have the `dplyr` package installed, they can even determine the column with microorganisms themselves inside `dplyr` functions:
```r
example_isolates %>%
filter(is_gram_positive())
#> NOTE: Using column `mo` as input for 'x'
```
* Functions `%not_like%` and `%not_like_case%` as wrappers around `%like%` and `%like_case%`. The RStudio addin to insert the text " %like% " as provided in this package now iterates over all like variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert ` %like% ` and by pressing it again it will be replaced with ` %not_like% `, etc.
* Functions `%not_like%` and `%not_like_case%` as wrappers around `%like%` and `%like_case%`. The RStudio addin to insert the text " %like% " as provided in this package now iterates over all like variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert ` %like% ` and by pressing it again it will be replaced with ` %not_like% `, etc.
#' Use this function to determine a valid microorganism ID ([`mo`]). Determination is done using intelligent rules and the complete taxonomic kingdoms Bacteria, Chromista, Protozoa, Archaea and most microbial species from the kingdom Fungi (see Source). The input can be almost anything: a full name (like `"Staphylococcus aureus"`), an abbreviated name (like `"S. aureus"`), an abbreviation known in the field (like `"MRSA"`), or just a genus. Please see *Examples*.
#' Use this function to determine a valid microorganism ID ([`mo`]). Determination is done using intelligent rules and the complete taxonomic kingdoms Bacteria, Chromista, Protozoa, Archaea and most microbial species from the kingdom Fungi (see Source). The input can be almost anything: a full name (like `"Staphylococcus aureus"`), an abbreviated name (like `"S. aureus"`), an abbreviation known in the field (like `"MRSA"`), or just a genus. Please see *Examples*.
#' @inheritSection lifecycle Stable lifecycle
#' @inheritSection lifecycle Stable lifecycle
#' @param x a character vector or a [data.frame] with one or two columns
#' @param x a character vector or a [data.frame] with one or two columns
#' @param Becker a logical to indicate whether *Staphylococci* should be categorised into coagulase-negative *Staphylococci* ("CoNS") and coagulase-positive *Staphylococci* ("CoPS") instead of their own species, according to Karsten Becker *et al.* (1,2,3).
#' @param Becker a logical to indicate whether staphylococci should be categorised into coagulase-negative staphylococci ("CoNS") and coagulase-positive staphylococci ("CoPS") instead of their own species, according to Karsten Becker *et al.* (1,2,3).
#'
#'
#' This excludes *Staphylococcus aureus* at default, use `Becker = "all"` to also categorise *S. aureus* as "CoPS".
#' This excludes *Staphylococcus aureus* at default, use `Becker = "all"` to also categorise *S. aureus* as "CoPS".
#' @param Lancefield a logical to indicate whether beta-haemolytic *Streptococci* should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield (4). These *Streptococci* will be categorised in their first group, e.g. *Streptococcus dysgalactiae* will be group C, although officially it was also categorised into groups G and L.
#' @param Lancefield a logical to indicate whether beta-haemolytic *Streptococci* should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield (4). These *Streptococci* will be categorised in their first group, e.g. *Streptococcus dysgalactiae* will be group C, although officially it was also categorised into groups G and L.
#' Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions [mo_kingdom()] and [mo_domain()] return the exact same results.
#' Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions [mo_kingdom()] and [mo_domain()] return the exact same results.
#'
#'
#' The Gram stain - [mo_gramstain()] - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318)), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [is_gram_negative()] and [is_gram_positive()] always return `TRUE` or `FALSE`, even for species outside the kingdom of Bacteria.
#' The Gram stain - [mo_gramstain()] - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318)), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [is_gram_negative()] and [is_gram_positive()] always return `TRUE` or `FALSE` (except when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria.
#'
#'
#' All output will be [translate]d where possible.
#' All output will be [translate]d where possible.
# exceptions for Streptococci: Streptococcus Group A -> GAS
# exceptions for streptococci: Group A Streptococcus -> GAS
shortnames[shortnames%like%"S. group [ABCDFGHK]"]<-paste0("G",gsub("S. group ([ABCDFGHK])","\\1",shortnames[shortnames%like%"S. group [ABCDFGHK]"]),"S")
shortnames[shortnames%like%"S. group [ABCDFGHK]"]<-paste0("G",gsub("S. group ([ABCDFGHK])","\\1",shortnames[shortnames%like%"S. group [ABCDFGHK]"]),"S")
<ahref="#last-updated-5-november-2020" class="anchor"></a><small>Last updated: 5 November 2020</small>
<ahref="#last-updated-9-november-2020" class="anchor"></a><small>Last updated: 9 November 2020</small>
</h2>
</h2>
<divid="new"class="section level3">
<divid="new"class="section level3">
<h3class="hasAnchor">
<h3class="hasAnchor">
<ahref="#new"class="anchor"></a>New</h3>
<ahref="#new"class="anchor"></a>New</h3>
<ul>
<ul>
<li>Functions <code><ahref="../reference/mo_property.html">is_gram_negative()</a></code> and <code><ahref="../reference/mo_property.html">is_gram_positive()</a></code> as wrappers around <code><ahref="../reference/mo_property.html">mo_gramstain()</a></code>. They always return <code>TRUE</code> or <code>FALSE</code>, thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</li>
<li>
<li>Functions <code><ahref="../reference/like.html">%not_like%</a></code> and <code><ahref="../reference/like.html">%not_like_case%</a></code> as wrappers around <code><ahref="../reference/like.html">%like%</a></code> and <code><ahref="../reference/like.html">%like_case%</a></code>. The RStudio addin to insert the text " %like% " as provided in this package now iterates over all like variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert <code><ahref="../reference/like.html">%like%</a></code> and by pressing it again it will be replaced with <code><ahref="../reference/like.html">%not_like%</a></code>, etc.</li>
<p>Functions <code><ahref="../reference/mo_property.html">is_gram_negative()</a></code> and <code><ahref="../reference/mo_property.html">is_gram_positive()</a></code> as wrappers around <code><ahref="../reference/mo_property.html">mo_gramstain()</a></code>. They always return <code>TRUE</code> or <code>FALSE</code> (except when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>), thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria. If you have the <code>dplyr</code> package installed, they can even determine the column with microorganisms themselves inside <code>dplyr</code> functions:</p>
<spanclass="co">#> NOTE: Using column `mo` as input for 'x'</span></pre></div>
</li>
<li><p>Functions <code><ahref="../reference/like.html">%not_like%</a></code> and <code><ahref="../reference/like.html">%not_like_case%</a></code> as wrappers around <code><ahref="../reference/like.html">%like%</a></code> and <code><ahref="../reference/like.html">%like_case%</a></code>. The RStudio addin to insert the text " %like% " as provided in this package now iterates over all like variants. So if you have defined the keyboard shortcut Ctrl/Cmd + L to this addin, it will first insert <code><ahref="../reference/like.html">%like%</a></code> and by pressing it again it will be replaced with <code><ahref="../reference/like.html">%not_like%</a></code>, etc.</p></li>
</ul>
</ul>
</div>
</div>
<divid="changed"class="section level3">
<divid="changed"class="section level3">
@ -287,7 +293,7 @@
<li>
<li>
<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>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>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>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>
<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>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>
<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>
<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>
<spanclass="co"># Columns 'IPM' and 'MEM' are in the example_isolates data set</span>
<spanclass="co"># Columns 'IPM' and 'MEM' are in the example_isolates data set</span>
@ -574,7 +580,7 @@ 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>Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline</p></li>
<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>
<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>
<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>
@ -602,7 +608,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<ul>
<li>
<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>
<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>
@ -612,7 +618,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
</li>
<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>
<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>
@ -692,7 +698,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<ul>
<li>
<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>
<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>
@ -720,7 +726,7 @@ 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>More intelligent way of coping with some consonants like “l” and “r”</p></li>
<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>
<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>
@ -778,13 +784,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<ul>
<li>
<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>
<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>
<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>
<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>
<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>
<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>
@ -808,7 +814,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<ul>
<li>
<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>
<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></pre></div>
<spanclass="co">#> NOTE: Use 'format()' on this result to get a publicable/printable format.</span></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>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 parameter <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>
<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 parameter <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>
@ -856,7 +862,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
</li>
<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>
<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>
@ -938,7 +944,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<ul>
<li>
<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>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>
<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>
@ -1203,19 +1209,19 @@ 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 antimicrobial resistance analysis per age group.</p></li>
<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 antimicrobial resistance analysis per age group.</p></li>
<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>
<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>
<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>
<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>
@ -1258,7 +1264,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
</li>
<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>
<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>
@ -1272,7 +1278,7 @@ 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>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>
<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>
<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="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>
<spanclass="co"># Warning: </span>
<spanclass="co"># one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.</span>
<spanclass="co"># one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.</span>
@ -1321,7 +1327,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<ul>
<ul>
<li>
<li>
<p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
<p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
<spanclass="fu"><ahref="https://dplyr.tidyverse.org/reference/select.html">select</a></span><spanclass="op">(</span><spanclass="op">-</span><spanclass="va">count</span>, <spanclass="op">-</span><spanclass="va">cum_count</span><spanclass="op">)</span><spanclass="co"># only get item, percent, cum_percent</span></pre></div>
<spanclass="fu"><ahref="https://dplyr.tidyverse.org/reference/select.html">select</a></span><spanclass="op">(</span><spanclass="op">-</span><spanclass="va">count</span>, <spanclass="op">-</span><spanclass="va">cum_count</span><spanclass="op">)</span><spanclass="co"># only get item, percent, cum_percent</span></pre></div>
@ -1506,7 +1512,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
</li>
</li>
</ul>
</ul>
<p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
<p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
<spanclass="fu"><ahref="../reference/mo_property.html">mo_gramstain</a></span><spanclass="op">(</span><spanclass="st">"E. coli"</span>, language <spanclass="op">=</span><spanclass="st">"de"</span><spanclass="op">)</span><spanclass="co"># German</span>
<spanclass="fu"><ahref="../reference/mo_property.html">mo_gramstain</a></span><spanclass="op">(</span><spanclass="st">"E. coli"</span>, language <spanclass="op">=</span><spanclass="st">"de"</span><spanclass="op">)</span><spanclass="co"># German</span>
@ -1516,7 +1522,7 @@ 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="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></pre></div>
<spanclass="co"># [1] "Streptococcus grupo A"</span></pre></div>
<p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
<p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
@ -1530,7 +1536,7 @@ 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>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>
<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>
<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>
<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>
<spanclass="co"># Unit: seconds</span>
<spanclass="co"># Unit: seconds</span>
@ -1571,7 +1577,7 @@ 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 three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</p></li>
<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>
<p>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.:</p>
@ -1587,7 +1593,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
<li><p>Added parameters <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code></p></li>
<li><p>Added parameters <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code></p></li>
<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>
<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">1.4.0.9008</span>
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">1.4.0.9013</span>
</span>
</span>
</div>
</div>
@ -270,7 +270,7 @@
</tr>
</tr>
<tr>
<tr>
<th>Becker</th>
<th>Becker</th>
<td><p>a logical to indicate whether <em>Staphylococci</em> should be categorised into coagulase-negative <em>Staphylococci</em> ("CoNS") and coagulase-positive <em>Staphylococci</em> ("CoPS") instead of their own species, according to Karsten Becker <em>et al.</em> (1,2,3).</p>
<td><p>a logical to indicate whether staphylococci should be categorised into coagulase-negative staphylococci ("CoNS") and coagulase-positive staphylococci ("CoPS") instead of their own species, according to Karsten Becker <em>et al.</em> (1,2,3).</p>
<p>This excludes <em>Staphylococcus aureus</em> at default, use <code>Becker = "all"</code> to also categorise <em>S. aureus</em> as "CoPS".</p></td>
<p>This excludes <em>Staphylococcus aureus</em> at default, use <code>Becker = "all"</code> to also categorise <em>S. aureus</em> as "CoPS".</p></td>
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">1.4.0.9008</span>
<spanclass="version label label-default"data-toggle="tooltip"data-placement="bottom"title="Latest development version">1.4.0.9013</span>
</span>
</span>
</div>
</div>
@ -340,7 +340,7 @@
<p>The short name - <code>mo_shortname()</code> - almost always returns the first character of the genus and the full species, like <code>"E. coli"</code>. Exceptions are abbreviations of staphylococci (like <em>"CoNS"</em>, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (like <em>"GBS"</em>, Group B Streptococci). Please bear in mind that e.g. <em>E. coli</em> could mean <em>Escherichia coli</em> (kingdom of Bacteria) as well as <em>Entamoeba coli</em> (kingdom of Protozoa). Returning to the full name will be done using <code><ahref='as.mo.html'>as.mo()</a></code> internally, giving priority to bacteria and human pathogens, i.e. <code>"E. coli"</code> will be considered <em>Escherichia coli</em>. In other words, <code>mo_fullname(mo_shortname("Entamoeba coli"))</code> returns <code>"Escherichia coli"</code>.</p>
<p>The short name - <code>mo_shortname()</code> - almost always returns the first character of the genus and the full species, like <code>"E. coli"</code>. Exceptions are abbreviations of staphylococci (like <em>"CoNS"</em>, Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (like <em>"GBS"</em>, Group B Streptococci). Please bear in mind that e.g. <em>E. coli</em> could mean <em>Escherichia coli</em> (kingdom of Bacteria) as well as <em>Entamoeba coli</em> (kingdom of Protozoa). Returning to the full name will be done using <code><ahref='as.mo.html'>as.mo()</a></code> internally, giving priority to bacteria and human pathogens, i.e. <code>"E. coli"</code> will be considered <em>Escherichia coli</em>. In other words, <code>mo_fullname(mo_shortname("Entamoeba coli"))</code> returns <code>"Escherichia coli"</code>.</p>
<p>Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions <code>mo_kingdom()</code> and <code>mo_domain()</code> return the exact same results.</p>
<p>Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions <code>mo_kingdom()</code> and <code>mo_domain()</code> return the exact same results.</p>
<p>The Gram stain - <code>mo_gramstain()</code> - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, <ahref='https://pubmed.ncbi.nlm.nih.gov/11837318'>PMID 11837318</a>), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value <code>NA</code>. Functions <code>is_gram_negative()</code> and <code>is_gram_positive()</code> always return <code>TRUE</code> or <code>FALSE</code>, even for species outside the kingdom of Bacteria.</p>
<p>The Gram stain - <code>mo_gramstain()</code> - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, <ahref='https://pubmed.ncbi.nlm.nih.gov/11837318'>PMID 11837318</a>), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value <code>NA</code>. Functions <code>is_gram_negative()</code> and <code>is_gram_positive()</code> always return <code>TRUE</code> or <code>FALSE</code> (except when the input is <code>NA</code> or the MO code is <code>UNKNOWN</code>), thus always return <code>FALSE</code> for species outside the taxonomic kingdom of Bacteria.</p>
<p>All output will be <ahref='translate.html'>translate</a>d where possible.</p>
<p>All output will be <ahref='translate.html'>translate</a>d where possible.</p>
<p>The function <code>mo_url()</code> will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.</p>
<p>The function <code>mo_url()</code> will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.</p>
@ -461,7 +461,7 @@ This package contains the complete taxonomic tree of almost all microorganisms (
<spanclass='fu'>mo_shortname</span><spanclass='op'>(</span><spanclass='st'>"S. pyo"</span>, Lancefield <spanclass='op'>=</span><spanclass='cn'>TRUE</span><spanclass='op'>)</span><spanclass='co'># "GAS" (='Group A Streptococci')</span>
<spanclass='fu'>mo_shortname</span><spanclass='op'>(</span><spanclass='st'>"S. pyo"</span>, Lancefield <spanclass='op'>=</span><spanclass='cn'>TRUE</span><spanclass='op'>)</span><spanclass='co'># "GAS" (='Group A Streptococci')</span>
<spanclass='co'># language support for German, Dutch, Spanish, Portuguese, Italian and French</span>
<spanclass='co'># language support --------------------------------------------------------</span>
<spanclass='fu'>mo_gramstain</span><spanclass='op'>(</span><spanclass='st'>"E. coli"</span>, language <spanclass='op'>=</span><spanclass='st'>"de"</span><spanclass='op'>)</span><spanclass='co'># "Gramnegativ"</span>
<spanclass='fu'>mo_gramstain</span><spanclass='op'>(</span><spanclass='st'>"E. coli"</span>, language <spanclass='op'>=</span><spanclass='st'>"de"</span><spanclass='op'>)</span><spanclass='co'># "Gramnegativ"</span>
<spanclass='fu'>mo_gramstain</span><spanclass='op'>(</span><spanclass='st'>"E. coli"</span>, language <spanclass='op'>=</span><spanclass='st'>"nl"</span><spanclass='op'>)</span><spanclass='co'># "Gram-negatief"</span>
<spanclass='fu'>mo_gramstain</span><spanclass='op'>(</span><spanclass='st'>"E. coli"</span>, language <spanclass='op'>=</span><spanclass='st'>"nl"</span><spanclass='op'>)</span><spanclass='co'># "Gram-negatief"</span>
<spanclass='fu'>mo_gramstain</span><spanclass='op'>(</span><spanclass='st'>"E. coli"</span>, language <spanclass='op'>=</span><spanclass='st'>"es"</span><spanclass='op'>)</span><spanclass='co'># "Gram negativo"</span>
<spanclass='fu'>mo_gramstain</span><spanclass='op'>(</span><spanclass='st'>"E. coli"</span>, language <spanclass='op'>=</span><spanclass='st'>"es"</span><spanclass='op'>)</span><spanclass='co'># "Gram negativo"</span>
@ -478,7 +478,11 @@ This package contains the complete taxonomic tree of almost all microorganisms (
\item{x}{a character vector or a \link{data.frame} with one or two columns}
\item{x}{a character vector or a \link{data.frame} with one or two columns}
\item{Becker}{a logical to indicate whether \emph{Staphylococci} should be categorised into coagulase-negative \emph{Staphylococci} ("CoNS") and coagulase-positive \emph{Staphylococci} ("CoPS") instead of their own species, according to Karsten Becker \emph{et al.} (1,2,3).
\item{Becker}{a logical to indicate whether staphylococci should be categorised into coagulase-negative staphylococci ("CoNS") and coagulase-positive staphylococci ("CoPS") instead of their own species, according to Karsten Becker \emph{et al.} (1,2,3).
This excludes \emph{Staphylococcus aureus} at default, use \code{Becker = "all"} to also categorise \emph{S. aureus} as "CoPS".}
This excludes \emph{Staphylococcus aureus} at default, use \code{Becker = "all"} to also categorise \emph{S. aureus} as "CoPS".}
@ -116,7 +116,7 @@ The short name - \code{\link[=mo_shortname]{mo_shortname()}} - almost always ret
Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions \code{\link[=mo_kingdom]{mo_kingdom()}} and \code{\link[=mo_domain]{mo_domain()}} return the exact same results.
Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions \code{\link[=mo_kingdom]{mo_kingdom()}} and \code{\link[=mo_domain]{mo_domain()}} return the exact same results.
The Gram stain - \code{\link[=mo_gramstain]{mo_gramstain()}} - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, \href{https://pubmed.ncbi.nlm.nih.gov/11837318}{PMID 11837318}), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value \code{NA}. Functions \code{\link[=is_gram_negative]{is_gram_negative()}} and \code{\link[=is_gram_positive]{is_gram_positive()}} always return \code{TRUE} or \code{FALSE}, even for species outside the kingdom of Bacteria.
The Gram stain - \code{\link[=mo_gramstain]{mo_gramstain()}} - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, \href{https://pubmed.ncbi.nlm.nih.gov/11837318}{PMID 11837318}), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value \code{NA}. Functions \code{\link[=is_gram_negative]{is_gram_negative()}} and \code{\link[=is_gram_positive]{is_gram_positive()}} always return \code{TRUE} or \code{FALSE} (except when the input is \code{NA} or the MO code is \code{UNKNOWN}), thus always return \code{FALSE} for species outside the taxonomic kingdom of Bacteria.
All output will be \link{translate}d where possible.
All output will be \link{translate}d where possible.
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