#' @param I_as_R a logical to indicate whether values \code{I} should be treated as \code{R}
#' @param I_as_R a logical to indicate whether values \code{I} should be treated as \code{R}
#' @param preserve_measurements a logical to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be \code{NA}.
#' @param preserve_measurements a logical to indicate whether predictions of years that are actually available in the data should be overwritten by the original data. The standard errors of those years will be \code{NA}.
#' @param info a logical to indicate whether textual analysis should be printed with the name and \code{\link{summary}} of the statistical model.
#' @param info a logical to indicate whether textual analysis should be printed with the name and \code{\link{summary}} of the statistical model.
#' @param main title of the plot
#' @return \code{data.frame} with extra class \code{"resistance_predict"} with columns:
#' @return \code{data.frame} with extra class \code{"resistance_predict"} with columns:
<p>It will be downloaded and installed automatically.</p>
<p>It will be downloaded and installed automatically.</p>
</div>
</div>
<divid="get-started"class="section level3">
<divid="get-started"class="section level3">
@ -245,17 +245,17 @@
<ahref="#overview-of-functions"class="anchor"></a>Overview of functions</h4>
<ahref="#overview-of-functions"class="anchor"></a>Overview of functions</h4>
<p>The <code>AMR</code> package basically does four important things:</p>
<p>The <code>AMR</code> package basically does four important things:</p>
<ol>
<ol>
<li>It <strong>cleanses existing data</strong>, by transforming it to reproducible and profound <em>classes</em>, making the most efficient use of R. These functions all use artificial intelligence to guess results that you would expect:</li>
<li>
</ol>
<p>It <strong>cleanses existing data</strong>, by transforming it to reproducible and profound <em>classes</em>, making the most efficient use of R. These functions all use artificial intelligence to guess results that you would expect:</p>
<ul>
<ul>
<li>Use <code><ahref="reference/as.mo.html">as.mo()</a></code> to get an ID of a microorganism. The IDs are human readable for the trained eye - the ID of <em>Klebsiella pneumoniae</em> is “B_KLBSL_PNE” (B stands for Bacteria) and the ID of <em>S. aureus</em> is “B_STPHY_AUR”. 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 artificial intelligence (AI) on the included ITIS data set, consisting of almost 20,000 microorganisms. It is <em>very</em> fast, please see our <ahref="./articles/benchmarks.html">benchmarks</a>. Moreover, it can group <em>Staphylococci</em> into coagulase negative and positive (CoNS and CoPS, see <ahref="./reference/as.mo.html#source">source</a>) and can categorise <em>Streptococci</em> into Lancefield groups (like beta-haemolytic <em>Streptococcus</em> Group B, <ahref="./reference/as.mo.html#source">source</a>).</li>
<li>Use <code><ahref="reference/as.mo.html">as.mo()</a></code> to get an ID of a microorganism. The IDs are human readable for the trained eye - the ID of <em>Klebsiella pneumoniae</em> is “B_KLBSL_PNE” (B stands for Bacteria) and the ID of <em>S. aureus</em> is “B_STPHY_AUR”. 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 artificial intelligence (AI) on the included ITIS data set, consisting of almost 20,000 microorganisms. It is <em>very</em> fast, please see our <ahref="./articles/benchmarks.html">benchmarks</a>. Moreover, it can group <em>Staphylococci</em> into coagulase negative and positive (CoNS and CoPS, see <ahref="./reference/as.mo.html#source">source</a>) and can categorise <em>Streptococci</em> into Lancefield groups (like beta-haemolytic <em>Streptococcus</em> Group B, <ahref="./reference/as.mo.html#source">source</a>).</li>
<li>Use <code><ahref="reference/as.rsi.html">as.rsi()</a></code> to transform values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like “<=0.002; S” (combined MIC/RSI) will result in “S”.</li>
<li>Use <code><ahref="reference/as.rsi.html">as.rsi()</a></code> to transform values to valid antimicrobial results. It produces just S, I or R based on your input and warns about invalid values. Even values like “<=0.002; S” (combined MIC/RSI) will result in “S”.</li>
<li>Use <code><ahref="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 “<=0.002; S” (combined MIC/RSI) will result in “<=0.002”.</li>
<li>Use <code><ahref="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 “<=0.002; S” (combined MIC/RSI) will result in “<=0.002”.</li>
<li>Use <code><ahref="reference/as.atc.html">as.atc()</a></code> to get the ATC code of an antibiotic as defined by the WHO. This package contains a database with most LIS codes, official names, DDDs and even trade names of antibiotics. For example, the values “Furabid”, “Furadantin”, “nitro” all return the ATC code of Nitrofurantoine.</li>
<li>Use <code><ahref="reference/as.atc.html">as.atc()</a></code> to get the ATC code of an antibiotic as defined by the WHO. This package contains a database with most LIS codes, official names, DDDs and even trade names of antibiotics. For example, the values “Furabid”, “Furadantin”, “nitro” all return the ATC code of Nitrofurantoine.</li>
</ul>
</ul>
<ol>
</li>
<li>It <strong>enhances existing data</strong> and <strong>adds new data</strong> from data sets included in this package.</li>
<li>
</ol>
<p>It <strong>enhances existing data</strong> and <strong>adds new data</strong> from data sets included in this package.</p>
<ul>
<ul>
<li>Use <code><ahref="reference/eucast_rules.html">eucast_rules()</a></code> to apply <ahref="http://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST expert rules to isolates</a>.</li>
<li>Use <code><ahref="reference/eucast_rules.html">eucast_rules()</a></code> to apply <ahref="http://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST expert rules to isolates</a>.</li>
<li>Use <code><ahref="reference/first_isolate.html">first_isolate()</a></code> to identify the first isolates of every patient <ahref="https://clsi.org/standards/products/microbiology/documents/m39/">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute).
<li>Use <code><ahref="reference/first_isolate.html">first_isolate()</a></code> to identify the first isolates of every patient <ahref="https://clsi.org/standards/products/microbiology/documents/m39/">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute).
@ -267,9 +267,9 @@
<li>The data set <code>microorganisms</code> contains the complete taxonomic tree of more than 18,000 microorganisms (bacteria, fungi/yeasts and protozoa). Furthermore, the colloquial name and Gram stain 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><ahref="reference/mo_property.html">mo_genus()</a></code>, <code><ahref="reference/mo_property.html">mo_family()</a></code>, <code><ahref="reference/mo_property.html">mo_gramstain()</a></code> or even <code><ahref="reference/mo_property.html">mo_phylum()</a></code>. As they use <code><ahref="reference/as.mo.html">as.mo()</a></code> internally, they also use artificial intelligence. For example, <code><ahref="reference/mo_property.html">mo_genus("MRSA")</a></code> and <code><ahref="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 data set <code>microorganisms</code> contains the complete taxonomic tree of more than 18,000 microorganisms (bacteria, fungi/yeasts and protozoa). Furthermore, the colloquial name and Gram stain 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><ahref="reference/mo_property.html">mo_genus()</a></code>, <code><ahref="reference/mo_property.html">mo_family()</a></code>, <code><ahref="reference/mo_property.html">mo_gramstain()</a></code> or even <code><ahref="reference/mo_property.html">mo_phylum()</a></code>. As they use <code><ahref="reference/as.mo.html">as.mo()</a></code> internally, they also use artificial intelligence. For example, <code><ahref="reference/mo_property.html">mo_genus("MRSA")</a></code> and <code><ahref="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 data set <code>antibiotics</code> contains the ATC code, LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains a total of 298 trade names. Use functions like <code><ahref="reference/ab_property.html">ab_name()</a></code> and <code><ahref="reference/ab_property.html">ab_tradenames()</a></code> to look up values. The <code>ab_*</code> functions use <code><ahref="reference/as.atc.html">as.atc()</a></code> internally so they support AI to guess your expected result. For example, <code><ahref="reference/ab_property.html">ab_name("Fluclox")</a></code>, <code><ahref="reference/ab_property.html">ab_name("Floxapen")</a></code> and <code><ahref="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>
<li>The data set <code>antibiotics</code> contains the ATC code, LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains a total of 298 trade names. Use functions like <code><ahref="reference/ab_property.html">ab_name()</a></code> and <code><ahref="reference/ab_property.html">ab_tradenames()</a></code> to look up values. The <code>ab_*</code> functions use <code><ahref="reference/as.atc.html">as.atc()</a></code> internally so they support AI to guess your expected result. For example, <code><ahref="reference/ab_property.html">ab_name("Fluclox")</a></code>, <code><ahref="reference/ab_property.html">ab_name("Floxapen")</a></code> and <code><ahref="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>
</ul>
<ol>
</li>
<li>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</li>
<li>
</ol>
<p>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</p>
<ul>
<ul>
<li>Calculate the resistance (and even co-resistance) of microbial isolates with the <code><ahref="reference/portion.html">portion_R()</a></code>, <code><ahref="reference/portion.html">portion_IR()</a></code>, <code><ahref="reference/portion.html">portion_I()</a></code>, <code><ahref="reference/portion.html">portion_SI()</a></code> and <code><ahref="reference/portion.html">portion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><ahref="reference/count.html">count_R()</a></code>, <code><ahref="reference/count.html">count_IR()</a></code>, <code><ahref="reference/count.html">count_I()</a></code>, <code><ahref="reference/count.html">count_SI()</a></code> and <code><ahref="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>Calculate the resistance (and even co-resistance) of microbial isolates with the <code><ahref="reference/portion.html">portion_R()</a></code>, <code><ahref="reference/portion.html">portion_IR()</a></code>, <code><ahref="reference/portion.html">portion_I()</a></code>, <code><ahref="reference/portion.html">portion_SI()</a></code> and <code><ahref="reference/portion.html">portion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><ahref="reference/count.html">count_R()</a></code>, <code><ahref="reference/count.html">count_IR()</a></code>, <code><ahref="reference/count.html">count_I()</a></code>, <code><ahref="reference/count.html">count_SI()</a></code> and <code><ahref="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><ahref="reference/ggplot_rsi.html">geom_rsi()</a></code>, a function made for the <code>ggplot2</code> package</li>
<li>Plot AMR results with <code><ahref="reference/ggplot_rsi.html">geom_rsi()</a></code>, a function made for the <code>ggplot2</code> package</li>
@ -277,9 +277,9 @@
<li>Conduct descriptive statistics to enhance base R: calculate <code><ahref="reference/kurtosis.html">kurtosis()</a></code>, <code><ahref="reference/skewness.html">skewness()</a></code> and create frequency tables with <code><ahref="reference/freq.html">freq()</a></code>
<li>Conduct descriptive statistics to enhance base R: calculate <code><ahref="reference/kurtosis.html">kurtosis()</a></code>, <code><ahref="reference/skewness.html">skewness()</a></code> and create frequency tables with <code><ahref="reference/freq.html">freq()</a></code>
</li>
</li>
</ul>
</ul>
<ol>
</li>
<li>It <strong>teaches the user</strong> how to use all the above actions.</li>
<li>
</ol>
<p>It <strong>teaches the user</strong> how to use all the above actions.</p>
<ul>
<ul>
<li>The package contains extensive help pages with many examples.</li>
<li>The package contains extensive help pages with many examples.</li>
<li>It also contains an example data set called <code>septic_patients</code>. This data set contains:
<li>It also contains an example data set called <code>septic_patients</code>. This data set contains:
<strong>BREAKING</strong>: removed deprecated functions, parameters and references to ‘bactid’. Use <code><ahref="../reference/as.mo.html">as.mo()</a></code> to identify an MO code.</li>
<strong>BREAKING</strong>: removed deprecated functions, parameters and references to ‘bactid’. Use <code><ahref="../reference/as.mo.html">as.mo()</a></code> to identify an MO code.</li>
<li>New website: <ahref="https://msberends.gitlab.io/AMR"class="uri">https://msberends.gitlab.io/AMR</a> (built with the great <ahref="https://pkgdown.r-lib.org/"><code>pkgdown</code></a>)</li>
<li>New website: <ahref="https://msberends.gitlab.io/AMR"class="uri">https://msberends.gitlab.io/AMR</a> (built with the great <ahref="https://pkgdown.r-lib.org/"><code>pkgdown</code></a>)
<ul>
<li>Contains the complete manual of this package and all of its functions with an explanation of their parameters</li>
<li>Contains the complete manual of this package and all of its functions with an explanation of their parameters</li>
<li>Contains a comprehensive tutorial about how to conduct antimicrobial resistance analysis</li>
<li>Contains a comprehensive tutorial about how to conduct antimicrobial resistance analysis</li>
</ul>
</li>
<li>Support for the upcoming <ahref="https://dplyr.tidyverse.org"><code>dplyr</code></a> version 0.8.0</li>
<li>Support for the upcoming <ahref="https://dplyr.tidyverse.org"><code>dplyr</code></a> version 0.8.0</li>
<li>Function <code><ahref="../reference/guess_ab_col.html">guess_ab_col()</a></code> to find an antibiotic column in a table</li>
<li>Function <code><ahref="../reference/guess_ab_col.html">guess_ab_col()</a></code> to find an antibiotic column in a table</li>
<li>Function <code><ahref="../reference/mo_failures.html">mo_failures()</a></code> to review values that could not be coerced to a valid MO code, using <code><ahref="../reference/as.mo.html">as.mo()</a></code>. This latter function will now only show a maximum of 25 uncoerced values.</li>
<li>Function <code><ahref="../reference/mo_failures.html">mo_failures()</a></code> to review values that could not be coerced to a valid MO code, using <code><ahref="../reference/as.mo.html">as.mo()</a></code>. This latter function will now only show a maximum of 25 uncoerced values.</li>
<li>Function <code><ahref="../reference/mo_renamed.html">mo_renamed()</a></code> to get a list of all returned values from <code><ahref="../reference/as.mo.html">as.mo()</a></code> that have had taxonomic renaming</li>
<li>Function <code><ahref="../reference/mo_renamed.html">mo_renamed()</a></code> to get a list of all returned values from <code><ahref="../reference/as.mo.html">as.mo()</a></code> that have had taxonomic renaming</li>
<li>Function <code><ahref="../reference/age.html">age()</a></code> to calculate the (patients) age in years</li>
<li>Function <code><ahref="../reference/age.html">age()</a></code> to calculate the (patients) age in years</li>
<li>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.</li>
<li>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.</li>
<li>Function <code><ahref="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><ahref="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> function can now be used for resistance prediction calculated with <code><ahref="../reference/resistance_predict.html">resistance_predict()</a></code>: <code>r x <- resistance_predict(septic_patients, col_ab = "amox") plot(x) ggplot_rsi_predict(x)</code>
<li>
<p>Function <code><ahref="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><ahref="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> function can now be used for resistance prediction calculated with <code><ahref="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
<li>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.: <code>r septic_patients %>% filter_first_isolate(...) # or filter_first_isolate(septic_patients, ...)</code> is equal to: <code>r septic_patients %>% mutate(only_firsts = first_isolate(septic_patients, ...)) %>% filter(only_firsts == TRUE) %>% select(-only_firsts)</code>
<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>
<li>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: <ahref="https://msberends.gitlab.io/AMR"class="uri">https://msberends.gitlab.io/AMR</a>.</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: <ahref="https://msberends.gitlab.io/AMR"class="uri">https://msberends.gitlab.io/AMR</a>.</p></li>
<li>Updated EUCAST Clinical breakpoints to <ahref="http://www.eucast.org/clinical_breakpoints/">version 9.0 of 1 January 2019</a>
<li>Updated EUCAST Clinical breakpoints to <ahref="http://www.eucast.org/clinical_breakpoints/">version 9.0 of 1 January 2019</a>
</li>
</li>
<li>Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately</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 <ahref="https://www.whocc.no/atc_ddd_index/?code=J01CE01">J01CE01</a>)</li>
<li>Emphasised in manual that penicillin is meant as benzylpenicillin (ATC <ahref="https://www.whocc.no/atc_ddd_index/?code=J01CE01">J01CE01</a>)</li>
</ul>
</li>
<li>Function <code><ahref="../reference/AMR-deprecated.html">guess_mo()</a></code> is now deprecated in favour of <code><ahref="../reference/as.mo.html">as.mo()</a></code> and will be removed in future versions</li>
<li>Function <code><ahref="../reference/AMR-deprecated.html">guess_mo()</a></code> is now deprecated in favour of <code><ahref="../reference/as.mo.html">as.mo()</a></code> and will be removed in future versions</li>
<li>Improvements for <code><ahref="../reference/as.mo.html">as.mo()</a></code>:</li>
<li>Improvements for <code><ahref="../reference/as.mo.html">as.mo()</a></code>:
<ul>
<li>Fix for vector containing only empty values</li>
<li>Fix for vector containing only empty values</li>
<li>Finds better results when input is in other languages</li>
<li>Finds better results when input is in other languages</li>
<li>Better handling for subspecies</li>
<li>Better handling for subspecies</li>
@ -265,12 +285,17 @@
<li>Manual now contains more info about the algorithms</li>
<li>Manual now contains more info about the algorithms</li>
<li>Progress bar will be shown when it takes more than 3 seconds to get results</li>
<li>Progress bar will be shown when it takes more than 3 seconds to get results</li>
<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>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>
<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>
<li>Will now use a column named like “key(…)ab” or “key(…)antibiotics” for the key antibiotics (parameter <code>col_keyantibiotics()</code>), when this parameter was left blank</li>
<li>Will now use a column named like “key(…)ab” or “key(…)antibiotics” for the key antibiotics (parameter <code>col_keyantibiotics()</code>), when this parameter was left blank</li>
<li>Removed parameter <code>output_logical</code>, the function will now always return a logical value</li>
<li>Removed parameter <code>output_logical</code>, the function will now always return a logical value</li>
<li>Renamed parameter <code>filter_specimen</code> to <code>specimen_group</code>, although using <code>filter_specimen</code> will still work</li>
<li>Renamed parameter <code>filter_specimen</code> to <code>specimen_group</code>, although using <code>filter_specimen</code> will still work</li>
</ul>
</li>
<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>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>Function <code><ahref="../reference/mo_property.html">mo_taxonomy()</a></code> now contains the kingdom too</li>
<li>Function <code><ahref="../reference/mo_property.html">mo_taxonomy()</a></code> now contains the kingdom too</li>
<li>Reduce false positives for <code><ahref="../reference/as.rsi.html">is.rsi.eligible()</a></code>
<li>Reduce false positives for <code><ahref="../reference/as.rsi.html">is.rsi.eligible()</a></code>
@ -279,7 +304,8 @@
</li>
</li>
<li>Small text updates to summaries of class <code>rsi</code> and <code>mic</code>
<li>Small text updates to summaries of class <code>rsi</code> and <code>mic</code>
<li>Header info is now available as a list, with the <code>header</code> function</li>
<li>Header info is now available as a list, with the <code>header</code> function</li>
<li>Added header info for class <code>mo</code> to show unique count of families, genera and species</li>
<li>Added header info for class <code>mo</code> to show unique count of families, genera and species</li>
<li>Now honours the <code>decimal.mark</code> setting, which just like <code>format</code> defaults to <code><ahref="https://www.rdocumentation.org/packages/base/topics/options">getOption("OutDec")</a></code>
<li>Now honours the <code>decimal.mark</code> setting, which just like <code>format</code> defaults to <code><ahref="https://www.rdocumentation.org/packages/base/topics/options">getOption("OutDec")</a></code>
@ -289,6 +315,8 @@
</li>
</li>
<li>New parameter <code>droplevels</code> to exclude empty factor levels when input is a factor</li>
<li>New parameter <code>droplevels</code> to exclude empty factor levels when input is a factor</li>
<li>Factor levels will be in header when present in input data</li>
<li>Factor levels will be in header when present in input data</li>
</ul>
</li>
<li>Function <code><ahref="../reference/ggplot_rsi.html">scale_y_percent()</a></code> now contains the <code>limits</code> parameter</li>
<li>Function <code><ahref="../reference/ggplot_rsi.html">scale_y_percent()</a></code> now contains the <code>limits</code> parameter</li>
<li>Automatic parameter filling for <code><ahref="../reference/mdro.html">mdro()</a></code>, <code><ahref="../reference/key_antibiotics.html">key_antibiotics()</a></code> and <code><ahref="../reference/eucast_rules.html">eucast_rules()</a></code>
<li>Automatic parameter filling for <code><ahref="../reference/mdro.html">mdro()</a></code>, <code><ahref="../reference/key_antibiotics.html">key_antibiotics()</a></code> and <code><ahref="../reference/eucast_rules.html">eucast_rules()</a></code>
</li>
</li>
@ -330,7 +358,8 @@
</li>
</li>
<li>
<li>
<code>EUCAST_rules</code> was renamed to <code>eucast_rules</code>, the old function still exists as a deprecated function</li>
<code>EUCAST_rules</code> was renamed to <code>eucast_rules</code>, the old function still exists as a deprecated function</li>
<li>Big changes to the <code>eucast_rules</code> function:</li>
<li>Big changes to the <code>eucast_rules</code> function:
<ul>
<li>Now also applies rules from the EUCAST ‘Breakpoint tables for bacteria’, version 8.1, 2018, <ahref="http://www.eucast.org/clinical_breakpoints/"class="uri">http://www.eucast.org/clinical_breakpoints/</a> (see Source of the function)</li>
<li>Now also applies rules from the EUCAST ‘Breakpoint tables for bacteria’, version 8.1, 2018, <ahref="http://www.eucast.org/clinical_breakpoints/"class="uri">http://www.eucast.org/clinical_breakpoints/</a> (see Source of the function)</li>
<li>New parameter <code>rules</code> to specify which rules should be applied (expert rules, breakpoints, others or all)</li>
<li>New parameter <code>rules</code> to specify which rules should be applied (expert rules, breakpoints, others or all)</li>
<li>New parameter <code>verbose</code> which can be set to <code>TRUE</code> to get very specific messages about which columns and rows were affected</li>
<li>New parameter <code>verbose</code> which can be set to <code>TRUE</code> to get very specific messages about which columns and rows were affected</li>
@ -339,11 +368,18 @@
<li>Data set <code>septic_patients</code> now reflects these changes</li>
<li>Data set <code>septic_patients</code> now reflects these changes</li>
<li>Added parameter <code>pipe</code> for piperacillin (J01CA12), also to the <code>mdro</code> function</li>
<li>Added parameter <code>pipe</code> for piperacillin (J01CA12), also to the <code>mdro</code> function</li>
<li>Small fixes to EUCAST clinical breakpoint rules</li>
<li>Small fixes to EUCAST clinical breakpoint rules</li>
</ul>
</li>
<li>Added column <code>kingdom</code> to the microorganisms data set, and function <code>mo_kingdom</code> to look up values</li>
<li>Added column <code>kingdom</code> to the microorganisms data set, and function <code>mo_kingdom</code> to look up values</li>
<li>Tremendous speed improvement for <code>as.mo</code> (and subsequently all <code>mo_*</code> functions), as empty values wil be ignored <em>a priori</em>
<li>Tremendous speed improvement for <code>as.mo</code> (and subsequently all <code>mo_*</code> functions), as empty values wil be ignored <em>a priori</em>
</li>
</li>
<li>Fewer than 3 characters as input for <code>as.mo</code> will return NA</li>
<li>Fewer than 3 characters as input for <code>as.mo</code> will return NA</li>
<li>Function <code>as.mo</code> (and all <code>mo_*</code> wrappers) now supports genus abbreviations with “species” attached <code>r as.mo("E. species") # B_ESCHR mo_fullname("E. spp.") # "Escherichia species" as.mo("S. spp") # B_STPHY mo_fullname("S. species") # "Staphylococcus species"</code>
<li>
<p>Function <code>as.mo</code> (and all <code>mo_*</code> wrappers) now supports genus abbreviations with “species” attached</p>
<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>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>Fix for <code>portion_*(..., as_percent = TRUE)</code> when minimal number of isolates would not be met</li>
@ -352,18 +388,19 @@
<li>Using <code>portion_*</code> functions now throws a warning when total available isolate is below parameter <code>minimum</code>
<li>Using <code>portion_*</code> functions now throws a warning when total available isolate is below parameter <code>minimum</code>
</li>
</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>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>
<spanclass="st"></span><spanclass="kw">select</span>(-count, -cum_count) <spanclass="co"># only get item, percent, cum_percent</span></code></pre></div>
<aclass="sourceLine"id="cb6-3"data-line-number="3"><spanclass="st"></span><spanclass="kw">select</span>(<spanclass="op">-</span>count, <spanclass="op">-</span>cum_count) <spanclass="co"># only get item, percent, cum_percent</span></a></code></pre></div>
</li>
</li>
<li>Check for <code><ahref="https://www.rdocumentation.org/packages/hms/topics/hms">hms::is.hms</a></code>
<li>Check for <code><ahref="https://www.rdocumentation.org/packages/hms/topics/hms">hms::is.hms</a></code>
</li>
</li>
@ -374,6 +411,8 @@
<li>New parameter <code>na</code>, to choose which character to print for empty values</li>
<li>New parameter <code>na</code>, to choose which character to print for empty values</li>
<li>New parameter <code>header</code> to turn the header info off (default when <code>markdown = TRUE</code>)</li>
<li>New parameter <code>header</code> to turn the header info off (default when <code>markdown = TRUE</code>)</li>
<li>New parameter <code>title</code> to manually setbthe title of the frequency table</li>
<li>New parameter <code>title</code> to manually setbthe title of the frequency table</li>
</ul>
</li>
<li>
<li>
<code>first_isolate</code> now tries to find columns to use as input when parameters are left blank</li>
<code>first_isolate</code> now tries to find columns to use as input when parameters are left blank</li>
<li>Improvements for MDRO algorithm (function <code>mdro</code>)</li>
<li>Improvements for MDRO algorithm (function <code>mdro</code>)</li>
@ -385,7 +424,8 @@
</li>
</li>
<li>
<li>
<code>ggplot_rsi</code> and <code>scale_y_percent</code> have <code>breaks</code> parameter</li>
<code>ggplot_rsi</code> and <code>scale_y_percent</code> have <code>breaks</code> parameter</li>
<li>Speed improvement for <code>is.rsi.eligible</code>, now 15-20 times faster</li>
<li>Speed improvement for <code>is.rsi.eligible</code>, now 15-20 times faster</li>
<li>In <code>g.test</code>, when <code><ahref="https://www.rdocumentation.org/packages/base/topics/sum">sum(x)</a></code> is below 1000 or any of the expected values is below 5, Fisher’s Exact Test will be suggested</li>
<li>In <code>g.test</code>, when <code><ahref="https://www.rdocumentation.org/packages/base/topics/sum">sum(x)</a></code> is below 1000 or any of the expected values is below 5, Fisher’s Exact Test will be suggested</li>
@ -426,7 +468,8 @@
<ahref="#new-2"class="anchor"></a>New</h4>
<ahref="#new-2"class="anchor"></a>New</h4>
<ul>
<ul>
<li>The data set <code>microorganisms</code> now contains <strong>all microbial taxonomic data from ITIS</strong> (kingdoms Bacteria, Fungi and Protozoa), the Integrated Taxonomy Information System, available via <ahref="https://itis.gov"class="uri">https://itis.gov</a>. The data set now contains more than 18,000 microorganisms with all known bacteria, fungi and protozoa according ITIS with genus, species, subspecies, family, order, class, phylum and subkingdom. The new data set <code>microorganisms.old</code> contains all previously known taxonomic names from those kingdoms.</li>
<li>The data set <code>microorganisms</code> now contains <strong>all microbial taxonomic data from ITIS</strong> (kingdoms Bacteria, Fungi and Protozoa), the Integrated Taxonomy Information System, available via <ahref="https://itis.gov"class="uri">https://itis.gov</a>. The data set now contains more than 18,000 microorganisms with all known bacteria, fungi and protozoa according ITIS with genus, species, subspecies, family, order, class, phylum and subkingdom. The new data set <code>microorganisms.old</code> contains all previously known taxonomic names from those kingdoms.</li>
<li>New functions based on the existing function <code>mo_property</code>:</li>
<li>New functions based on the existing function <code>mo_property</code>:
<p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese: <code>r mo_gramstain("E. coli") # [1] "Gram negative" mo_gramstain("E. coli", language = "de") # German # [1] "Gramnegativ" mo_gramstain("E. coli", language = "es") # Spanish # [1] "Gram negativo" mo_fullname("S. group A", language = "pt") # Portuguese # [1] "Streptococcus grupo A"</code></p>
<p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
<p>Furthermore, former taxonomic names will give a note about the current taxonomic name: <code>r mo_gramstain("Esc blattae") # Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010) # [1] "Gram negative"</code></p>
<li>Functions <code>count_R</code>, <code>count_IR</code>, <code>count_I</code>, <code>count_SI</code> and <code>count_S</code> to selectively count resistant or susceptible isolates
<ul>
<ul>
<li>Functions <code>count_R</code>, <code>count_IR</code>, <code>count_I</code>, <code>count_SI</code> and <code>count_S</code> to selectively count resistant or susceptible isolates</li>
<li>Extra function <code>count_df</code> (which works like <code>portion_df</code>) to get all counts of S, I and R of a data set with antibiotic columns, with support for grouped variables</li>
<li>Extra function <code>count_df</code> (which works like <code>portion_df</code>) to get all counts of S, I and R of a data set with antibiotic columns, with support for grouped variables</li>
</ul>
</li>
<li>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>
<li>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>
</li>
</li>
<li>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 Artificial Intelligence (AI): <code>r as.mo("E. coli") # [1] B_ESCHR_COL as.mo("MRSA") # [1] B_STPHY_AUR as.mo("S group A") # [1] B_STRPTC_GRA</code> 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: <code>r thousands_of_E_colis <- rep("E. coli", 25000) microbenchmark::microbenchmark(as.mo(thousands_of_E_colis), unit = "s") # Unit: seconds # min median max neval # 0.01817717 0.01843957 0.03878077 100</code>
<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 Artificial Intelligence (AI):</p>
<aclass="sourceLine"id="cb9-5"data-line-number="5"><spanclass="kw"><ahref="../reference/as.mo.html">as.mo</a></span>(<spanclass="st">"S group A"</span>)</a>
<li>Added parameter <code>reference_df</code> for <code>as.mo</code>, so users can supply their own microbial IDs, name or codes as a reference table</li>
<li>Added parameter <code>reference_df</code> for <code>as.mo</code>, so users can supply their own microbial IDs, name or codes as a reference table</li>
<li>Renamed all previous references to <code>bactid</code> to <code>mo</code>, like:</li>
<li>Renamed all previous references to <code>bactid</code> to <code>mo</code>, like:
<ul>
<li>Column names inputs of <code>EUCAST_rules</code>, <code>first_isolate</code> and <code>key_antibiotics</code>
<li>Column names inputs of <code>EUCAST_rules</code>, <code>first_isolate</code> and <code>key_antibiotics</code>
</li>
</li>
<li>Column names of datasets <code>microorganisms</code> and <code>septic_patients</code>
<li>Column names of datasets <code>microorganisms</code> and <code>septic_patients</code>
</li>
</li>
<li>All old syntaxes will still work with this version, but will throw warnings</li>
<li>All old syntaxes will still work with this version, but will throw warnings</li>
</ul>
</li>
<li>Function <code>labels_rsi_count</code> to print datalabels on a RSI <code>ggplot2</code> model</li>
<li>Function <code>labels_rsi_count</code> to print datalabels on a RSI <code>ggplot2</code> model</li>
<li><p>Functions <code>as.atc</code> and <code>is.atc</code> to transform/look up antibiotic ATC codes as defined by the WHO. The existing function <code>guess_atc</code> is now an alias of <code>as.atc</code>.</p></li>
<li><p>Functions <code>as.atc</code> and <code>is.atc</code> to transform/look up antibiotic ATC codes as defined by the WHO. The existing function <code>guess_atc</code> is now an alias of <code>as.atc</code>.</p></li>
<li>Function <code>ab_property</code> and its aliases: <code>ab_name</code>, <code>ab_tradenames</code>, <code>ab_certe</code>, <code>ab_umcg</code> and <code>ab_trivial_nl</code>
<li>Function <code>ab_property</code> and its aliases: <code>ab_name</code>, <code>ab_tradenames</code>, <code>ab_certe</code>, <code>ab_umcg</code> and <code>ab_trivial_nl</code>
<li>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</li>
<li>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</li>
<li>Added 163 trade names to the <code>antibiotics</code> data set, it now contains 298 different trade names in total, e.g.: <code>r ab_official("Bactroban") # [1] "Mupirocin" ab_name(c("Bactroban", "Amoxil", "Zithromax", "Floxapen")) # [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin" ab_atc(c("Bactroban", "Amoxil", "Zithromax", "Floxapen")) # [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"</code>
<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>
<li>For <code>first_isolate</code>, rows will be ignored when there’s no species available</li>
<li>For <code>first_isolate</code>, rows will be ignored when there’s no species available</li>
<li>Function <code>ratio</code> is now deprecated and will be removed in a future release, as it is not really the scope of this package</li>
<li>Function <code>ratio</code> is now deprecated and will be removed in a future release, as it is not really the scope of this package</li>
@ -475,9 +555,36 @@
<li>Added <code>prevalence</code> column to the <code>microorganisms</code> data set</li>
<li>Added <code>prevalence</code> column to the <code>microorganisms</code> data set</li>
<li>Added parameters <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code>
<li>Added parameters <code>minimum</code> and <code>as_percent</code> to <code>portion_df</code>
</li>
</li>
<li>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. ```r septic_patients %>% select(amox, cipr) %>% count_IR() # which is the same as: septic_patients %>% count_IR(amox, cipr)</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>
<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>
<li>Added datalabels function <code>labels_rsi_count</code> to <code>ggplot_rsi</code>
</li>
<li>Added possibility to set any parameter to <code>geom_rsi</code> (and <code>ggplot_rsi</code>) so you can set your own preferences</li>
<li>Fix for joins, where predefined suffices would not be honoured</li>
<li>Added parameter <code>quote</code> to the <code>freq</code> function</li>
<li>Added generic function <code>diff</code> for frequency tables</li>
<li>Added longest en shortest character length in the frequency table (<code>freq</code>) header of class <code>character</code>
</li>
<li>
<p>Support for types (classes) list and matrix for <code>freq</code></p>
<p>septic_patients %>% portion_S(amcl) septic_patients %>% portion_S(amcl, gent) septic_patients %>% portion_S(amcl, gent, pita) <code>* Edited `ggplot_rsi` and `geom_rsi` so they can cope with `count_df`. The new `fun` parameter has value `portion_df` at default, but can be set to `count_df`. * Fix for `ggplot_rsi` when the `ggplot2` package was not loaded * Added datalabels function `labels_rsi_count` to `ggplot_rsi` * Added possibility to set any parameter to `geom_rsi` (and `ggplot_rsi`) so you can set your own preferences * Fix for joins, where predefined suffices would not be honoured * Added parameter `quote` to the `freq` function * Added generic function `diff` for frequency tables * Added longest en shortest character length in the frequency table (`freq`) header of class `character` * Support for types (classes) list and matrix for `freq`</code>r my_matrix = with(septic_patients, matrix(c(age, gender), ncol = 2)) freq(my_matrix) <code>For lists, subsetting is possible:</code>r my_list = list(age = septic_patients$age, gender = septic_patients$gender) my_list %>% freq(age) my_list %>% freq(gender) ```</p>
</div>
</div>
<divid="other-2"class="section level4">
<divid="other-2"class="section level4">
<h4class="hasAnchor">
<h4class="hasAnchor">
@ -496,15 +603,21 @@
<ahref="#new-3"class="anchor"></a>New</h4>
<ahref="#new-3"class="anchor"></a>New</h4>
<ul>
<ul>
<li>
<li>
<strong>BREAKING</strong>: <code>rsi_df</code> was removed in favour of new functions <code>portion_R</code>, <code>portion_IR</code>, <code>portion_I</code>, <code>portion_SI</code> and <code>portion_S</code> to selectively calculate resistance or susceptibility. These functions are 20 to 30 times faster than the old <code>rsi</code> function. The old function still works, but is deprecated.</li>
<strong>BREAKING</strong>: <code>rsi_df</code> was removed in favour of new functions <code>portion_R</code>, <code>portion_IR</code>, <code>portion_I</code>, <code>portion_SI</code> and <code>portion_S</code> to selectively calculate resistance or susceptibility. These functions are 20 to 30 times faster than the old <code>rsi</code> function. The old function still works, but is deprecated.
<ul>
<li>New function <code>portion_df</code> to get all portions of S, I and R of a data set with antibiotic columns, with support for grouped variables</li>
<li>New function <code>portion_df</code> to get all portions of S, I and R of a data set with antibiotic columns, with support for grouped variables</li>
</ul>
</li>
<li>
<li>
<strong>BREAKING</strong>: the methodology for determining first weighted isolates was changed. The antibiotics that are compared between isolates (call <em>key antibiotics</em>) to include more first isolates (afterwards called first <em>weighted</em> isolates) are now as follows:</li>
<strong>BREAKING</strong>: the methodology for determining first weighted isolates was changed. The antibiotics that are compared between isolates (call <em>key antibiotics</em>) to include more first isolates (afterwards called first <em>weighted</em> isolates) are now as follows:
<li>New functions <code>geom_rsi</code>, <code>facet_rsi</code>, <code>scale_y_percent</code>, <code>scale_rsi_colours</code> and <code>theme_rsi</code>
<li>New functions <code>geom_rsi</code>, <code>facet_rsi</code>, <code>scale_y_percent</code>, <code>scale_rsi_colours</code> and <code>theme_rsi</code>
</li>
</li>
<li>New wrapper function <code>ggplot_rsi</code> to apply all above functions on a data set:
<li>New wrapper function <code>ggplot_rsi</code> to apply all above functions on a data set:
@ -515,22 +628,32 @@
</li>
</li>
</ul>
</ul>
</li>
</li>
<li>Determining bacterial ID:</li>
</ul>
</li>
<li>Determining bacterial ID:
<ul>
<li>New functions <code>as.bactid</code> and <code>is.bactid</code> to transform/ look up microbial ID’s.</li>
<li>New functions <code>as.bactid</code> and <code>is.bactid</code> to transform/ look up microbial ID’s.</li>
<li>The existing function <code>guess_bactid</code> is now an alias of <code>as.bactid</code>
<li>The existing function <code>guess_bactid</code> is now an alias of <code>as.bactid</code>
</li>
</li>
<li>New Becker classification for <em>Staphylococcus</em> to categorise them into Coagulase Negative <em>Staphylococci</em> (CoNS) and Coagulase Positve <em>Staphylococci</em> (CoPS)</li>
<li>New Becker classification for <em>Staphylococcus</em> to categorise them into Coagulase Negative <em>Staphylococci</em> (CoNS) and Coagulase Positve <em>Staphylococci</em> (CoPS)</li>
<li>New Lancefield classification for <em>Streptococcus</em> to categorise them into Lancefield groups</li>
<li>New Lancefield classification for <em>Streptococcus</em> to categorise them into Lancefield groups</li>
</ul>
</li>
<li>For convience, new descriptive statistical functions <code>kurtosis</code> and <code>skewness</code> that are lacking in base R - they are generic functions and have support for vectors, data.frames and matrices</li>
<li>For convience, new descriptive statistical functions <code>kurtosis</code> and <code>skewness</code> that are lacking in base R - they are generic functions and have support for vectors, data.frames and matrices</li>
<li>Function <code>g.test</code> to perform the Χ<sup>2</sup> distributed <ahref="https://en.wikipedia.org/wiki/G-test"><em>G</em>-test</a>, which use is the same as <code>chisq.test</code>
<li>Function <code>g.test</code> to perform the Χ<sup>2</sup> distributed <ahref="https://en.wikipedia.org/wiki/G-test"><em>G</em>-test</a>, which use is the same as <code>chisq.test</code>
</li>
</li>
<li><del>Function <code>ratio</code> to transform a vector of values to a preset ratio</del></li>
<li>
<del>Function <code>ratio</code> to transform a vector of values to a preset ratio</del>
<ul>
<li><del>For example: <code><ahref="../reference/AMR-deprecated.html">ratio(c(10, 500, 10), ratio = "1:2:1")</a></code> would return <code>130, 260, 130</code></del></li>
<li><del>For example: <code><ahref="../reference/AMR-deprecated.html">ratio(c(10, 500, 10), ratio = "1:2:1")</a></code> would return <code>130, 260, 130</code></del></li>
</ul>
</li>
<li>Support for Addins menu in RStudio to quickly insert <code>%in%</code> or <code>%like%</code> (and give them keyboard shortcuts), or to view the datasets that come with this package</li>
<li>Support for Addins menu in RStudio to quickly insert <code>%in%</code> or <code>%like%</code> (and give them keyboard shortcuts), or to view the datasets that come with this package</li>
<li>Function <code>p.symbol</code> to transform p values to their related symbols: <code>0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code>
<li>Function <code>p.symbol</code> to transform p values to their related symbols: <code>0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1</code>
</li>
</li>
<li>Functions <code>clipboard_import</code> and <code>clipboard_export</code> as helper functions to quickly copy and paste from/to software like Excel and SPSS. These functions use the <code>clipr</code> package, but are a little altered to also support headless Linux servers (so you can use it in RStudio Server)</li>
<li>Functions <code>clipboard_import</code> and <code>clipboard_export</code> as helper functions to quickly copy and paste from/to software like Excel and SPSS. These functions use the <code>clipr</code> package, but are a little altered to also support headless Linux servers (so you can use it in RStudio Server)</li>
<li>New for frequency tables (function <code>freq</code>):</li>
<li>New for frequency tables (function <code>freq</code>):
<ul>
<li>A vignette to explain its usage</li>
<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>rsi</code> (antimicrobial resistance) to use as input</li>
<li>Support for <code>table</code> to use as input: <code><ahref="../reference/freq.html">freq(table(x, y))</a></code>
<li>Support for <code>table</code> to use as input: <code><ahref="../reference/freq.html">freq(table(x, y))</a></code>
@ -545,6 +668,8 @@
<li>Header of frequency tables now also show Mean Absolute Deviaton (MAD) and Interquartile Range (IQR)</li>
<li>Header of frequency tables now also show Mean Absolute Deviaton (MAD) and Interquartile Range (IQR)</li>
<li>Possibility to globally set the default for the amount of items to print, with <code><ahref="https://www.rdocumentation.org/packages/base/topics/options">options(max.print.freq = n)</a></code> where <em>n</em> is your preset value</li>
<li>Possibility to globally set the default for the amount of items to print, with <code><ahref="https://www.rdocumentation.org/packages/base/topics/options">options(max.print.freq = n)</a></code> where <em>n</em> is your preset value</li>
</ul>
</ul>
</li>
</ul>
</div>
</div>
<divid="changed-3"class="section level4">
<divid="changed-3"class="section level4">
<h4class="hasAnchor">
<h4class="hasAnchor">
@ -566,21 +691,27 @@
</li>
</li>
<li>Small improvements to the <code>microorganisms</code> dataset (especially for <em>Salmonella</em>) and the column <code>bactid</code> now has the new class <code>"bactid"</code>
<li>Small improvements to the <code>microorganisms</code> dataset (especially for <em>Salmonella</em>) and the column <code>bactid</code> now has the new class <code>"bactid"</code>
</li>
</li>
<li>Combined MIC/RSI values will now be coerced by the <code>rsi</code> and <code>mic</code> functions:</li>
<li>Combined MIC/RSI values will now be coerced by the <code>rsi</code> and <code>mic</code> functions:
<ul>
<li>
<li>
<code><ahref="../reference/as.rsi.html">as.rsi("<=0.002; S")</a></code> will return <code>S</code>
<code><ahref="../reference/as.rsi.html">as.rsi("<=0.002; S")</a></code> will return <code>S</code>
</li>
</li>
<li>
<li>
<code><ahref="../reference/as.mic.html">as.mic("<=0.002; S")</a></code> will return <code><=0.002</code>
<code><ahref="../reference/as.mic.html">as.mic("<=0.002; S")</a></code> will return <code><=0.002</code>
</li>
</li>
</ul>
</li>
<li>Now possible to coerce MIC values with a space between operator and value, i.e. <code><ahref="../reference/as.mic.html">as.mic("<= 0.002")</a></code> now works</li>
<li>Now possible to coerce MIC values with a space between operator and value, i.e. <code><ahref="../reference/as.mic.html">as.mic("<= 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>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><ahref="../reference/atc_property.html">atc_property(..., property)</a></code>. It will return a vector of the ATC hierarchy as defined by the <ahref="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>Added <code>"groups"</code> option for <code><ahref="../reference/atc_property.html">atc_property(..., property)</a></code>. It will return a vector of the ATC hierarchy as defined by the <ahref="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>
<li>Build-in host check for <code>atc_property</code> as it requires the host set by <code>url</code> to be responsive</li>
<li>Improved <code>first_isolate</code> algorithm to exclude isolates where bacteria ID or genus is unavailable</li>
<li>Improved <code>first_isolate</code> algorithm to exclude isolates where bacteria ID or genus is unavailable</li>
<li>Fix for warning <em>hybrid evaluation forced for row_number</em> (<ahref="https://github.com/tidyverse/dplyr/commit/924b62"><code>924b62</code></a>) from the <code>dplyr</code> package v0.7.5 and above</li>
<li>Fix for warning <em>hybrid evaluation forced for row_number</em> (<ahref="https://github.com/tidyverse/dplyr/commit/924b62"><code>924b62</code></a>) from the <code>dplyr</code> package v0.7.5 and above</li>
<li>Support for empty values and for 1 or 2 columns as input for <code>guess_bactid</code> (now called <code>as.bactid</code>)</li>
<li>Support for empty values and for 1 or 2 columns as input for <code>guess_bactid</code> (now called <code>as.bactid</code>)
<ul>
<li>So <code>yourdata %>% select(genus, species) %>% as.bactid()</code> now also works</li>
<li>So <code>yourdata %>% select(genus, species) %>% as.bactid()</code> now also works</li>
</ul>
</li>
<li>Other small fixes</li>
<li>Other small fixes</li>
</ul>
</ul>
</div>
</div>
@ -588,11 +719,14 @@
<h4class="hasAnchor">
<h4class="hasAnchor">
<ahref="#other-3"class="anchor"></a>Other</h4>
<ahref="#other-3"class="anchor"></a>Other</h4>
<ul>
<ul>
<li>Added integration tests (check if everything works as expected) for all releases of R 3.1 and higher</li>
<li>Added integration tests (check if everything works as expected) for all releases of R 3.1 and higher
<ul>
<li>Linux and macOS: <ahref="https://travis-ci.org/msberends/AMR"class="uri">https://travis-ci.org/msberends/AMR</a>
<li>Linux and macOS: <ahref="https://travis-ci.org/msberends/AMR"class="uri">https://travis-ci.org/msberends/AMR</a>
<li>Added thesis advisors to DESCRIPTION file</li>
<li>Added thesis advisors to DESCRIPTION file</li>
</ul>
</ul>
</div>
</div>
@ -611,10 +745,13 @@
<li>Function <code>guess_bactid</code> to <strong>determine the ID</strong> of a microorganism based on genus/species or known abbreviations like MRSA</li>
<li>Function <code>guess_bactid</code> to <strong>determine the ID</strong> of a microorganism based on genus/species or known abbreviations like MRSA</li>
<li>Function <code>guess_atc</code> to <strong>determine the ATC</strong> of an antibiotic based on name, trade name, or known abbreviations</li>
<li>Function <code>guess_atc</code> to <strong>determine the ATC</strong> of an antibiotic based on name, trade name, or known abbreviations</li>
<li>Function <code>freq</code> to create <strong>frequency tables</strong>, with additional info in a header</li>
<li>Function <code>freq</code> to create <strong>frequency tables</strong>, with additional info in a header</li>
<li>Function <code>MDRO</code> to <strong>determine Multi Drug Resistant Organisms (MDRO)</strong> with support for country-specific guidelines.</li>
<li>Function <code>MDRO</code> to <strong>determine Multi Drug Resistant Organisms (MDRO)</strong> with support for country-specific guidelines.
<ul>
<li>
<li>
<ahref="http://www.eucast.org/expert_rules_and_intrinsic_resistance">Exceptional resistances defined by EUCAST</a> are also supported instead of countries alone</li>
<ahref="http://www.eucast.org/expert_rules_and_intrinsic_resistance">Exceptional resistances defined by EUCAST</a> are also supported instead of countries alone</li>
<li>Functions <code>BRMO</code> and <code>MRGN</code> are wrappers for Dutch and German guidelines, respectively</li>
<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><ahref="../reference/first_isolate.html">?first_isolate</a></code>
<li>New algorithm to determine weighted isolates, can now be <code>"points"</code> or <code>"keyantibiotics"</code>, see <code><ahref="../reference/first_isolate.html">?first_isolate</a></code>
</li>
</li>
<li>New print format for <code>tibble</code>s and <code>data.table</code>s</li>
<li>New print format for <code>tibble</code>s and <code>data.table</code>s</li>
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