freq and website update

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
 Version: 0.5.0.9016
-Date: 2019-01-30
+Date: 2019-02-01
 Title: Antimicrobial Resistance Analysis
 Authors@R: c(
     person(

R/atc_online.R

@@ -79,20 +79,12 @@ atc_online_property <- function(atc_code,
     stop("Packages 'xml2', 'rvest' and 'curl' are required for this function")
   }
 
-  # check active network interface, from https://stackoverflow.com/a/5078002/4575331
-  has_internet <- function(url) {
-    # extract host from given url
-    # https://www.whocc.no/atc_ddd_index/ -> www.whocc.no
-    url <- url %>%
-      gsub("^(http://|https://)", "", .) %>%
-      strsplit('/', fixed = TRUE) %>%
-      unlist() %>%
-      .[1]
-    !is.null(curl::nslookup(url, error = FALSE))
+  if (!all(atc_code %in% AMR::antibiotics)) {
+    atc_code <- as.character(as.atc(atc_code))
   }
-  # check for connection using the ATC of amoxicillin
-  if (!curl::has_internet(url = url)) {
-    message("The URL could not be reached.")
+
+  if (!curl::has_internet()) {
+    message("There appears to be no internet connection.")
     return(rep(NA, length(atc_code)))
   }
 

R/freq.R

@@ -610,7 +610,13 @@ format_header <- function(x, markdown = FALSE, decimal.mark = ".", big.mark = ",
 
   # class and mode
   if (is.null(header$columns)) {
+    if (markdown == TRUE) {
+      header$class <- paste0("`", header$class, "`")
+    }
     if (!header$mode %in% header$class) {
+      if (markdown == TRUE) {
+        header$mode <- paste0("`", header$mode, "`")
+      }
       header$class <- header$class %>% rev() %>% paste(collapse = " > ") %>% paste0(silver(paste0(" (", header$mode, ")")))
     } else {
       header$class <- header$class %>% rev() %>% paste(collapse = " > ")

docs/index.html

@@ -236,15 +236,15 @@
 <h4 class="hasAnchor">
 <a href="#latest-released-version" class="anchor"></a>Latest released version</h4>
 <p>This package is available <a href="https://cran.r-project.org/package=AMR">on the official R network (CRAN)</a>, which has a peer-reviewed submission process. Install this package in R with:</p>
-<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="st">"AMR"</span>)</a></code></pre></div>
+<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="st">"AMR"</span>)</code></pre></div>
 <p>It will be downloaded and installed automatically. For RStudio, click on the menu <em>Tools</em> &gt; <em>Install Packages…</em> and then type in “AMR” and press <kbd>Install</kbd>.</p>
 </div>
 <div id="latest-development-version" class="section level4">
 <h4 class="hasAnchor">
 <a href="#latest-development-version" class="anchor"></a>Latest development version</h4>
 <p>The latest and unpublished development version can be installed with (precaution: may be unstable):</p>
-<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="st">"devtools"</span>)</a>
-<a class="sourceLine" id="cb2-2" data-line-number="2">devtools<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/devtools/topics/reexports">install_gitlab</a></span>(<span class="st">"msberends/AMR"</span>)</a></code></pre></div>
+<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="https://www.rdocumentation.org/packages/utils/topics/install.packages">install.packages</a></span>(<span class="st">"devtools"</span>)
+devtools::<span class="kw">install_gitlab</span>(<span class="st">"msberends/AMR"</span>)</code></pre></div>
 </div>
 </div>
 <div id="get-started" class="section level2">
@@ -284,17 +284,17 @@
 <a href="#overview-of-functions" class="anchor"></a>Overview of functions</h4>
 <p>The <code>AMR</code> package basically does four important things:</p>
 <ol>
-<li>
-<p>It <strong>cleanses existing data</strong> by providing new <em>classes</em> for microoganisms, antibiotics and antimicrobial results (both S/I/R and MIC). With this package, you learn R everything about microbiology that is needed for analysis. These functions all use artificial intelligence to guess results that you would expect:</p>
+<li>It <strong>cleanses existing data</strong> by providing new <em>classes</em> for microoganisms, antibiotics and antimicrobial results (both S/I/R and MIC). With this package, you learn R everything about microbiology that is needed for analysis. These functions all use artificial intelligence to guess results that you would expect:</li>
+</ol>
 <ul>
 <li>Use <code><a href="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 <a href="./articles/benchmarks.html">benchmarks</a>. Moreover, it can group <em>Staphylococci</em> into coagulase negative and positive (CoNS and CoPS, see <a href="./reference/as.mo.html#source">source</a>) and can categorise <em>Streptococci</em> into Lancefield groups (like beta-haemolytic <em>Streptococcus</em> Group B, <a href="./reference/as.mo.html#source">source</a>).</li>
 <li>Use <code><a href="reference/as.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 “&lt;=0.002; S” (combined MIC/RSI) will result in “S”.</li>
 <li>Use <code><a href="reference/as.mic.html">as.mic()</a></code> to cleanse your MIC values. It produces a so-called factor (called <em>ordinal</em> in SPSS) with valid MIC values as levels. A value like “&lt;=0.002; S” (combined MIC/RSI) will result in “&lt;=0.002”.</li>
 <li>Use <code><a href="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>
-</li>
-<li>
-<p>It <strong>enhances existing data</strong> and <strong>adds new data</strong> from data sets included in this package.</p>
+<ol>
+<li>It <strong>enhances existing data</strong> and <strong>adds new data</strong> from data sets included in this package.</li>
+</ol>
 <ul>
 <li>Use <code><a href="reference/eucast_rules.html">eucast_rules()</a></code> to apply <a href="http://www.eucast.org/expert_rules_and_intrinsic_resistance/">EUCAST expert rules to isolates</a>.</li>
 <li>Use <code><a href="reference/first_isolate.html">first_isolate()</a></code> to identify the first isolates of every patient <a href="https://clsi.org/standards/products/microbiology/documents/m39/">using guidelines from the CLSI</a> (Clinical and Laboratory Standards Institute).
@@ -306,9 +306,9 @@
 <li>The <a href="./reference/microorganisms.html">data set <code>microorganisms</code></a> contains the complete taxonomic tree of almost 20,000 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><a href="reference/mo_property.html">mo_genus()</a></code>, <code><a href="reference/mo_property.html">mo_family()</a></code>, <code><a href="reference/mo_property.html">mo_gramstain()</a></code> or even <code><a href="reference/mo_property.html">mo_phylum()</a></code>. As they use <code><a href="reference/as.mo.html">as.mo()</a></code> internally, they also use artificial intelligence. For example, <code><a href="reference/mo_property.html">mo_genus("MRSA")</a></code> and <code><a href="reference/mo_property.html">mo_genus("S. aureus")</a></code> will both return <code>"Staphylococcus"</code>. They also come with support for German, Dutch, Spanish, Italian, French and Portuguese. These functions can be used to add new variables to your data.</li>
 <li>The <a href="./reference/antibiotics.html">data set <code>antibiotics</code></a> contains almost 500 antimicrobial drugs with their ATC code, EARS-Net code, common LIS codes, official name, trivial name and DDD of both oral and parenteral administration. It also contains hundreds of trade names. Use functions like <code><a href="reference/atc_property.html">atc_name()</a></code> and <code><a href="reference/atc_property.html">atc_tradenames()</a></code> to look up values. The <code>atc_*</code> functions use <code><a href="reference/as.atc.html">as.atc()</a></code> internally so they support AI to guess your expected result. For example, <code><a href="reference/atc_property.html">atc_name("Fluclox")</a></code>, <code><a href="reference/atc_property.html">atc_name("Floxapen")</a></code> and <code><a href="reference/atc_property.html">atc_name("J01CF05")</a></code> will all return <code>"Flucloxacillin"</code>. These functions can again be used to add new variables to your data.</li>
 </ul>
-</li>
-<li>
-<p>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</p>
+<ol>
+<li>It <strong>analyses the data</strong> with convenient functions that use well-known methods.</li>
+</ol>
 <ul>
 <li>Calculate the resistance (and even co-resistance) of microbial isolates with the <code><a href="reference/portion.html">portion_R()</a></code>, <code><a href="reference/portion.html">portion_IR()</a></code>, <code><a href="reference/portion.html">portion_I()</a></code>, <code><a href="reference/portion.html">portion_SI()</a></code> and <code><a href="reference/portion.html">portion_S()</a></code> functions. Similarly, the <em>number</em> of isolates can be determined with the <code><a href="reference/count.html">count_R()</a></code>, <code><a href="reference/count.html">count_IR()</a></code>, <code><a href="reference/count.html">count_I()</a></code>, <code><a href="reference/count.html">count_SI()</a></code> and <code><a href="reference/count.html">count_S()</a></code> functions. All these functions can be used with the <code>dplyr</code> package (e.g. in conjunction with <code>summarise()</code>)</li>
 <li>Plot AMR results with <code><a href="reference/ggplot_rsi.html">geom_rsi()</a></code>, a function made for the <code>ggplot2</code> package</li>
@@ -316,9 +316,9 @@
 <li>Conduct descriptive statistics to enhance base R: calculate <code><a href="reference/kurtosis.html">kurtosis()</a></code>, <code><a href="reference/skewness.html">skewness()</a></code> and create frequency tables with <code><a href="reference/freq.html">freq()</a></code>
 </li>
 </ul>
-</li>
-<li>
-<p>It <strong>teaches the user</strong> how to use all the above actions.</p>
+<ol>
+<li>It <strong>teaches the user</strong> how to use all the above actions.</li>
+</ol>
 <ul>
 <li>Aside from this website with many tutorials, the package itself contains extensive help pages with many examples for all functions.</li>
 <li>It also contains an <a href=".reference/septic_patients.html">example data set called <code>septic_patients</code></a>. This data set contains:
@@ -329,8 +329,6 @@
 </ul>
 </li>
 </ul>
-</li>
-</ol>
 </div>
 <div id="partners" class="section level4">
 <h4 class="hasAnchor">

docs/news/index.html

@@ -236,28 +236,13 @@
 <ul>
 <li>
 <strong>BREAKING</strong>: removed deprecated functions, parameters and references to ‘bactid’. Use <code><a href="../reference/as.mo.html">as.mo()</a></code> to identify an MO code.</li>
-<li>Support for data from <a href="https://whonet.org/">WHONET</a> and <a href="https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net">EARS-Net</a> (European Antimicrobial Resistance Surveillance Network):
-<ul>
+<li>Support for data from <a href="https://whonet.org/">WHONET</a> and <a href="https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net">EARS-Net</a> (European Antimicrobial Resistance Surveillance Network):</li>
 <li>Exported files from WHONET can be read and used in this package. For functions like <code><a href="../reference/first_isolate.html">first_isolate()</a></code> and <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>, all parameters will be filled in automatically.</li>
 <li>This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the <code>antibiotics</code> data set now contains a column <code>ears_net</code>.</li>
-</ul>
-</li>
-<li>
-<p>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions:</p>
-<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb1-1" data-line-number="1">ab_property -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_property</a></span>()</a>
-<a class="sourceLine" id="cb1-2" data-line-number="2">ab_name -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_name</a></span>()</a>
-<a class="sourceLine" id="cb1-3" data-line-number="3">ab_official -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_official</a></span>()</a>
-<a class="sourceLine" id="cb1-4" data-line-number="4">ab_trivial_nl -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_trivial_nl</a></span>()</a>
-<a class="sourceLine" id="cb1-5" data-line-number="5">ab_certe -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_certe</a></span>()</a>
-<a class="sourceLine" id="cb1-6" data-line-number="6">ab_umcg -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_umcg</a></span>()</a>
-<a class="sourceLine" id="cb1-7" data-line-number="7">ab_tradenames -&gt;<span class="st"> </span><span class="kw"><a href="../reference/atc_property.html">atc_tradenames</a></span>()</a></code></pre></div>
-These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code> internally. The old <code>atc_property</code> has been renamed <code><a href="../reference/atc_online.html">atc_online_property()</a></code>. This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class <code>atc</code> or must be coerable to this class. Properties of these classes should start with the same class name, analogous to <code><a href="../reference/as.mo.html">as.mo()</a></code> and e.g. <code>mo_genus</code>.</li>
-<li>New website: <a href="https://msberends.gitlab.io/AMR" class="uri">https://msberends.gitlab.io/AMR</a> (built with the great <a href="https://pkgdown.r-lib.org/"><code>pkgdown</code></a>)
-<ul>
+<li>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions: <code>r   ab_property -&gt; atc_property()   ab_name -&gt; atc_name()   ab_official -&gt; atc_official()   ab_trivial_nl -&gt; atc_trivial_nl()   ab_certe -&gt; atc_certe()   ab_umcg -&gt; atc_umcg()   ab_tradenames -&gt; atc_tradenames()</code> These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code> internally. The old <code>atc_property</code> has been renamed <code><a href="../reference/atc_online.html">atc_online_property()</a></code>. This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class <code>atc</code> or must be coerable to this class. Properties of these classes should start with the same class name, analogous to <code><a href="../reference/as.mo.html">as.mo()</a></code> and e.g. <code>mo_genus</code>.</li>
+<li>New website: <a href="https://msberends.gitlab.io/AMR" class="uri">https://msberends.gitlab.io/AMR</a> (built with the great <a href="https://pkgdown.r-lib.org/"><code>pkgdown</code></a>)</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>
-</ul>
-</li>
 <li>New functions <code><a href="../reference/mo_source.html">set_mo_source()</a></code> and <code><a href="../reference/mo_source.html">get_mo_source()</a></code> to use your own predefined MO codes as input for <code><a href="../reference/as.mo.html">as.mo()</a></code> and consequently all <code>mo_*</code> functions</li>
 <li>Support for the upcoming <a href="https://dplyr.tidyverse.org"><code>dplyr</code></a> version 0.8.0</li>
 <li>New function <code><a href="../reference/guess_ab_col.html">guess_ab_col()</a></code> to find an antibiotic column in a table</li>
@@ -265,24 +250,11 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <li>New function <code><a href="../reference/mo_renamed.html">mo_renamed()</a></code> to get a list of all returned values from <code><a href="../reference/as.mo.html">as.mo()</a></code> that have had taxonomic renaming</li>
 <li>New function <code><a href="../reference/age.html">age()</a></code> to calculate the (patients) age in years</li>
 <li>New function <code><a href="../reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.</li>
-<li>
-<p>New function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>:</p>
-<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" data-line-number="1">x &lt;-<span class="st"> </span><span class="kw"><a href="../reference/resistance_predict.html">resistance_predict</a></span>(septic_patients, <span class="dt">col_ab =</span> <span class="st">"amox"</span>)</a>
-<a class="sourceLine" id="cb2-2" data-line-number="2"><span class="kw"><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot</a></span>(x)</a>
-<a class="sourceLine" id="cb2-3" data-line-number="3"><span class="kw"><a href="../reference/resistance_predict.html">ggplot_rsi_predict</a></span>(x)</a></code></pre></div>
+<li>New function <code><a href="../reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>: <code>r   x &lt;- resistance_predict(septic_patients, col_ab = "amox")   plot(x)   ggplot_rsi_predict(x)</code>
 </li>
-<li>
-<p>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
-<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(...)</a>
-<a class="sourceLine" id="cb3-2" data-line-number="2"><span class="co"># or</span></a>
-<a class="sourceLine" id="cb3-3" data-line-number="3"><span class="kw"><a href="../reference/first_isolate.html">filter_first_isolate</a></span>(septic_patients, ...)</a></code></pre></div>
-<p>is equal to:</p>
-<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb4-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span></a>
-<a class="sourceLine" id="cb4-2" data-line-number="2"><span class="st">  </span><span class="kw">mutate</span>(<span class="dt">only_firsts =</span> <span class="kw"><a href="../reference/first_isolate.html">first_isolate</a></span>(septic_patients, ...)) <span class="op">%&gt;%</span></a>
-<a class="sourceLine" id="cb4-3" data-line-number="3"><span class="st">  </span><span class="kw"><a href="https://www.rdocumentation.org/packages/stats/topics/filter">filter</a></span>(only_firsts <span class="op">==</span><span class="st"> </span><span class="ot">TRUE</span>) <span class="op">%&gt;%</span></a>
-<a class="sourceLine" id="cb4-4" data-line-number="4"><span class="st">  </span><span class="kw">select</span>(<span class="op">-</span>only_firsts)</a></code></pre></div>
+<li>Functions <code><a href="../reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="../reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.: <code>r   septic_patients %&gt;% filter_first_isolate(...)   # or   filter_first_isolate(septic_patients, ...)</code> is equal to: <code>r   septic_patients %&gt;% mutate(only_firsts = first_isolate(septic_patients, ...)) %&gt;% filter(only_firsts == TRUE) %&gt;% select(-only_firsts)</code>
 </li>
-<li><p>New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the <em>G</em>-test and more. These are also available (and even easier readable) on our website: <a href="https://msberends.gitlab.io/AMR" class="uri">https://msberends.gitlab.io/AMR</a>.</p></li>
+<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: <a href="https://msberends.gitlab.io/AMR" class="uri">https://msberends.gitlab.io/AMR</a>.</li>
 </ul>
 </div>
 <div id="changed" class="section level4">
@@ -294,16 +266,12 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <li>Functions <code><a href="../reference/AMR-deprecated.html">atc_ddd()</a></code> and <code><a href="../reference/AMR-deprecated.html">atc_groups()</a></code> have been renamed <code><a href="../reference/atc_online.html">atc_online_ddd()</a></code> and <code><a href="../reference/atc_online.html">atc_online_groups()</a></code>. The old functions are deprecated and will be removed in a future version.</li>
 <li>Function <code><a href="../reference/AMR-deprecated.html">guess_mo()</a></code> is now deprecated in favour of <code><a href="../reference/as.mo.html">as.mo()</a></code> and will be removed in future versions</li>
 <li>Function <code><a href="../reference/AMR-deprecated.html">guess_atc()</a></code> is now deprecated in favour of <code><a href="../reference/as.atc.html">as.atc()</a></code> and will be removed in future versions</li>
-<li>Function <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:
-<ul>
+<li>Function <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>:</li>
 <li>Updated EUCAST Clinical breakpoints to <a href="http://www.eucast.org/clinical_breakpoints/">version 9.0 of 1 January 2019</a>
 </li>
 <li>Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately</li>
 <li>Emphasised in manual that penicillin is meant as benzylpenicillin (ATC <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE01">J01CE01</a>)</li>
-</ul>
-</li>
-<li>Improvements for <code><a href="../reference/as.mo.html">as.mo()</a></code>:
-<ul>
+<li>Improvements for <code><a href="../reference/as.mo.html">as.mo()</a></code>:</li>
 <li>Fix for vector containing only empty values</li>
 <li>Finds better results when input is in other languages</li>
 <li>Better handling for subspecies</li>
@@ -314,17 +282,12 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <li>Progress bar will be shown when it takes more than 3 seconds to get results</li>
 <li>Support for formatted console text</li>
 <li>Console will return the percentage of uncoercable input</li>
-</ul>
-</li>
-<li>Function <code><a href="../reference/first_isolate.html">first_isolate()</a></code>:
-<ul>
+<li>Function <code><a href="../reference/first_isolate.html">first_isolate()</a></code>:</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 “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>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>Merged data sets <code>microorganisms.certe</code> and <code>microorganisms.umcg</code> into <code>microorganisms.codes</code>
 </li>
@@ -337,23 +300,22 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 </li>
 <li>Small text updates to summaries of class <code>rsi</code> and <code>mic</code>
 </li>
-<li>Frequency tables (<code><a href="../reference/freq.html">freq()</a></code> function):
-<ul>
+<li>Frequency tables (<code><a href="../reference/freq.html">freq()</a></code> function):</li>
 <li>
 <p>Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:</p>
-<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb5-1" data-line-number="1"><span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span></a>
-<a class="sourceLine" id="cb5-2" data-line-number="2"><span class="co"># OLD WAY</span></a>
-<a class="sourceLine" id="cb5-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span></a>
-<a class="sourceLine" id="cb5-4" data-line-number="4"><span class="st">  </span><span class="kw">mutate</span>(<span class="dt">genus =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo)) <span class="op">%&gt;%</span></a>
-<a class="sourceLine" id="cb5-5" data-line-number="5"><span class="st">  </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus)</a>
-<a class="sourceLine" id="cb5-6" data-line-number="6"><span class="co"># NEW WAY</span></a>
-<a class="sourceLine" id="cb5-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
-<a class="sourceLine" id="cb5-8" data-line-number="8"><span class="st">  </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a>
-<a class="sourceLine" id="cb5-9" data-line-number="9"></a>
-<a class="sourceLine" id="cb5-10" data-line-number="10"><span class="co"># Even supports grouping variables:</span></a>
-<a class="sourceLine" id="cb5-11" data-line-number="11">septic_patients <span class="op">%&gt;%</span></a>
-<a class="sourceLine" id="cb5-12" data-line-number="12"><span class="st">  </span><span class="kw">group_by</span>(gender) <span class="op">%&gt;%</span><span class="st"> </span></a>
-<a class="sourceLine" id="cb5-13" data-line-number="13"><span class="st">  </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</a></code></pre></div>
+<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co"># Determine genus of microorganisms (mo) in `septic_patients` data set:</span>
+<span class="co"># OLD WAY</span>
+septic_patients %&gt;%
+<span class="st">  </span><span class="kw">mutate</span>(<span class="dt">genus =</span> <span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo)) %&gt;%
+<span class="st">  </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(genus)
+<span class="co"># NEW WAY</span>
+septic_patients %&gt;%<span class="st"> </span>
+<span class="st">  </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))
+
+<span class="co"># Even supports grouping variables:</span>
+septic_patients %&gt;%
+<span class="st">  </span><span class="kw">group_by</span>(gender) %&gt;%<span class="st"> </span>
+<span class="st">  </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(<span class="kw"><a href="../reference/mo_property.html">mo_genus</a></span>(mo))</code></pre></div>
 </li>
 <li>Header info is now available as a list, with the <code>header</code> function</li>
 <li>The parameter <code>header</code> is now set to <code>TRUE</code> at default, even for markdown</li>
@@ -366,13 +328,11 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <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 (maximum of 5)</li>
 <li>Fix for using <code>select()</code> on frequency tables</li>
-</ul>
-</li>
 <li>Function <code><a href="../reference/ggplot_rsi.html">scale_y_percent()</a></code> now contains the <code>limits</code> parameter</li>
 <li>Automatic parameter filling for <code><a href="../reference/mdro.html">mdro()</a></code>, <code><a href="../reference/key_antibiotics.html">key_antibiotics()</a></code> and <code><a href="../reference/eucast_rules.html">eucast_rules()</a></code>
 </li>
 <li>Updated examples for resistance prediction (<code><a href="../reference/resistance_predict.html">resistance_predict()</a></code> function)</li>
-<li>Fix for <code><a href="../reference/as.mic.html">as.mic()</a></code> to support more values ending in (several) zeroes</li>
+<li><p>Fix for <code><a href="../reference/as.mic.html">as.mic()</a></code> to support more values ending in (several) zeroes</p></li>
 </ul>
 </div>
 <div id="other" class="section level4">
@@ -409,8 +369,7 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 </li>
 <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:
-<ul>
+<li>Big changes to the <code>eucast_rules</code> function:</li>
 <li>Now also applies rules from the EUCAST ‘Breakpoint tables for bacteria’, version 8.1, 2018, <a href="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>verbose</code> which can be set to <code>TRUE</code> to get very specific messages about which columns and rows were affected</li>
@@ -419,18 +378,11 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <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>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>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>Fewer than 3 characters as input for <code>as.mo</code> will return NA</li>
-<li>
-<p>Function <code>as.mo</code> (and all <code>mo_*</code> wrappers) now supports genus abbreviations with “species” attached</p>
-<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb6-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. species"</span>)        <span class="co"># B_ESCHR</span></a>
-<a class="sourceLine" id="cb6-2" data-line-number="2"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"E. spp."</span>)     <span class="co"># "Escherichia species"</span></a>
-<a class="sourceLine" id="cb6-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S. spp"</span>)            <span class="co"># B_STPHY</span></a>
-<a class="sourceLine" id="cb6-4" data-line-number="4"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. species"</span>)  <span class="co"># "Staphylococcus species"</span></a></code></pre></div>
+<li>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>
 <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>
@@ -439,19 +391,18 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <li>Using <code>portion_*</code> functions now throws a warning when total available isolate is below parameter <code>minimum</code>
 </li>
 <li>Functions <code>as.mo</code>, <code>as.rsi</code>, <code>as.mic</code>, <code>as.atc</code> and <code>freq</code> will not set package name as attribute anymore</li>
-<li>Frequency tables - <code><a href="../reference/freq.html">freq()</a></code>:
-<ul>
+<li>Frequency tables - <code><a href="../reference/freq.html">freq()</a></code>:</li>
 <li>
 <p>Support for grouping variables, test with:</p>
-<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb7-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
-<a class="sourceLine" id="cb7-2" data-line-number="2"><span class="st">  </span><span class="kw">group_by</span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
-<a class="sourceLine" id="cb7-3" data-line-number="3"><span class="st">  </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender)</a></code></pre></div>
+<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">septic_patients %&gt;%<span class="st"> </span>
+<span class="st">  </span><span class="kw">group_by</span>(hospital_id) %&gt;%<span class="st"> </span>
+<span class="st">  </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender)</code></pre></div>
 </li>
 <li>
 <p>Support for (un)selecting columns:</p>
-<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb8-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span></a>
-<a class="sourceLine" id="cb8-2" data-line-number="2"><span class="st">  </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id) <span class="op">%&gt;%</span><span class="st"> </span></a>
-<a class="sourceLine" id="cb8-3" data-line-number="3"><span class="st">  </span><span class="kw">select</span>(<span class="op">-</span>count, <span class="op">-</span>cum_count) <span class="co"># only get item, percent, cum_percent</span></a></code></pre></div>
+<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">septic_patients %&gt;%<span class="st"> </span>
+<span class="st">  </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(hospital_id) %&gt;%<span class="st"> </span>
+<span class="st">  </span><span class="kw">select</span>(-count, -cum_count) <span class="co"># only get item, percent, cum_percent</span></code></pre></div>
 </li>
 <li>Check for <code><a href="https://www.rdocumentation.org/packages/hms/topics/hms">hms::is.hms</a></code>
 </li>
@@ -462,8 +413,6 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <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>title</code> to manually setbthe title of the frequency table</li>
-</ul>
-</li>
 <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>
@@ -475,8 +424,7 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 </li>
 <li>
 <code>ggplot_rsi</code> and <code>scale_y_percent</code> have <code>breaks</code> parameter</li>
-<li>AI improvements for <code>as.mo</code>:
-<ul>
+<li>AI improvements for <code>as.mo</code>:</li>
 <li>
 <code>"CRS"</code> -&gt; <em>Stenotrophomonas maltophilia</em>
 </li>
@@ -489,8 +437,6 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <li>
 <code>"MSSE"</code> -&gt; <em>Staphylococcus epidermidis</em>
 </li>
-</ul>
-</li>
 <li>Fix for <code>join</code> functions</li>
 <li>Speed improvement for <code>is.rsi.eligible</code>, now 15-20 times faster</li>
 <li>In <code>g.test</code>, when <code><a href="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>
@@ -519,8 +465,7 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <a href="#new-2" class="anchor"></a>New</h4>
 <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 <a href="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>:
-<ul>
+<li>New functions based on the existing function <code>mo_property</code>:</li>
 <li>Taxonomic names: <code>mo_phylum</code>, <code>mo_class</code>, <code>mo_order</code>, <code>mo_family</code>, <code>mo_genus</code>, <code>mo_species</code>, <code>mo_subspecies</code>
 </li>
 <li>Semantic names: <code>mo_fullname</code>, <code>mo_shortname</code>
@@ -530,52 +475,22 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <li>Author and year: <code>mo_ref</code>
 </li>
 </ul>
-<p>They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:</p>
-<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb9-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>)</a>
-<a class="sourceLine" id="cb9-2" data-line-number="2"><span class="co"># [1] "Gram negative"</span></a>
-<a class="sourceLine" id="cb9-3" data-line-number="3"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"de"</span>) <span class="co"># German</span></a>
-<a class="sourceLine" id="cb9-4" data-line-number="4"><span class="co"># [1] "Gramnegativ"</span></a>
-<a class="sourceLine" id="cb9-5" data-line-number="5"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"E. coli"</span>, <span class="dt">language =</span> <span class="st">"es"</span>) <span class="co"># Spanish</span></a>
-<a class="sourceLine" id="cb9-6" data-line-number="6"><span class="co"># [1] "Gram negativo"</span></a>
-<a class="sourceLine" id="cb9-7" data-line-number="7"><span class="kw"><a href="../reference/mo_property.html">mo_fullname</a></span>(<span class="st">"S. group A"</span>, <span class="dt">language =</span> <span class="st">"pt"</span>) <span class="co"># Portuguese</span></a>
-<a class="sourceLine" id="cb9-8" data-line-number="8"><span class="co"># [1] "Streptococcus grupo A"</span></a></code></pre></div>
-<p>Furthermore, former taxonomic names will give a note about the current taxonomic name:</p>
-<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb10-1" data-line-number="1"><span class="kw"><a href="../reference/mo_property.html">mo_gramstain</a></span>(<span class="st">"Esc blattae"</span>)</a>
-<a class="sourceLine" id="cb10-2" data-line-number="2"><span class="co"># Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)</span></a>
-<a class="sourceLine" id="cb10-3" data-line-number="3"><span class="co"># [1] "Gram negative"</span></a></code></pre></div>
-</li>
-<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
+<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>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>
 <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>
-</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 %&gt;% mutate_if(is.rsi.eligible, as.rsi)</code>
 </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 Artificial Intelligence (AI):</p>
-<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb11-1" data-line-number="1"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"E. coli"</span>)</a>
-<a class="sourceLine" id="cb11-2" data-line-number="2"><span class="co"># [1] B_ESCHR_COL</span></a>
-<a class="sourceLine" id="cb11-3" data-line-number="3"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"MRSA"</span>)</a>
-<a class="sourceLine" id="cb11-4" data-line-number="4"><span class="co"># [1] B_STPHY_AUR</span></a>
-<a class="sourceLine" id="cb11-5" data-line-number="5"><span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(<span class="st">"S group A"</span>)</a>
-<a class="sourceLine" id="cb11-6" data-line-number="6"><span class="co"># [1] B_STRPTC_GRA</span></a></code></pre></div>
-<p>And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:</p>
-<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb12-1" data-line-number="1">thousands_of_E_colis &lt;-<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/rep">rep</a></span>(<span class="st">"E. coli"</span>, <span class="dv">25000</span>)</a>
-<a class="sourceLine" id="cb12-2" data-line-number="2">microbenchmark<span class="op">::</span><span class="kw"><a href="https://www.rdocumentation.org/packages/microbenchmark/topics/microbenchmark">microbenchmark</a></span>(<span class="kw"><a href="../reference/as.mo.html">as.mo</a></span>(thousands_of_E_colis), <span class="dt">unit =</span> <span class="st">"s"</span>)</a>
-<a class="sourceLine" id="cb12-3" data-line-number="3"><span class="co"># Unit: seconds</span></a>
-<a class="sourceLine" id="cb12-4" data-line-number="4"><span class="co">#         min       median         max  neval</span></a>
-<a class="sourceLine" id="cb12-5" data-line-number="5"><span class="co">#  0.01817717  0.01843957  0.03878077    100</span></a></code></pre></div>
+<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 &lt;- 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>
 <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:
-<ul>
+<li>Renamed all previous references to <code>bactid</code> to <code>mo</code>, like:</li>
 <li>Column names inputs of <code>EUCAST_rules</code>, <code>first_isolate</code> and <code>key_antibiotics</code>
 </li>
 <li>Column names of datasets <code>microorganisms</code> and <code>septic_patients</code>
 </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><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>
@@ -590,14 +505,7 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <a href="#changed-2" class="anchor"></a>Changed</h4>
 <ul>
 <li>Added three antimicrobial agents to the <code>antibiotics</code> data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)</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>
-<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb13-1" data-line-number="1"><span class="kw"><a href="../reference/AMR-deprecated.html">ab_official</a></span>(<span class="st">"Bactroban"</span>)</a>
-<a class="sourceLine" id="cb13-2" data-line-number="2"><span class="co"># [1] "Mupirocin"</span></a>
-<a class="sourceLine" id="cb13-3" data-line-number="3"><span class="kw"><a href="../reference/AMR-deprecated.html">ab_name</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
-<a class="sourceLine" id="cb13-4" data-line-number="4"><span class="co"># [1] "Mupirocin" "Amoxicillin" "Azithromycin" "Flucloxacillin"</span></a>
-<a class="sourceLine" id="cb13-5" data-line-number="5"><span class="kw"><a href="../reference/AMR-deprecated.html">ab_atc</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(<span class="st">"Bactroban"</span>, <span class="st">"Amoxil"</span>, <span class="st">"Zithromax"</span>, <span class="st">"Floxapen"</span>))</a>
-<a class="sourceLine" id="cb13-6" data-line-number="6"><span class="co"># [1] "R01AX06" "J01CA04" "J01FA10" "J01CF05"</span></a></code></pre></div>
+<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>
 <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>
@@ -606,36 +514,9 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <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>
-<li>
-<p>Support for quasiquotation in the functions series <code>count_*</code> and <code>portions_*</code>, and <code>n_rsi</code>. This allows to check for more than 2 vectors or columns.</p>
-<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb14-1" data-line-number="1">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw">select</span>(amox, cipr) <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>()</a>
-<a class="sourceLine" id="cb14-2" data-line-number="2"><span class="co"># which is the same as:</span></a>
-<a class="sourceLine" id="cb14-3" data-line-number="3">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/count.html">count_IR</a></span>(amox, cipr)</a>
-<a class="sourceLine" id="cb14-4" data-line-number="4"></a>
-<a class="sourceLine" id="cb14-5" data-line-number="5">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl)</a>
-<a class="sourceLine" id="cb14-6" data-line-number="6">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl, gent)</a>
-<a class="sourceLine" id="cb14-7" data-line-number="7">septic_patients <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/portion.html">portion_S</a></span>(amcl, gent, pita)</a></code></pre></div>
-</li>
-<li>Edited <code>ggplot_rsi</code> and <code>geom_rsi</code> so they can cope with <code>count_df</code>. The new <code>fun</code> parameter has value <code>portion_df</code> at default, but can be set to <code>count_df</code>.</li>
-<li>Fix for <code>ggplot_rsi</code> when the <code>ggplot2</code> package was not loaded</li>
-<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>
-<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb15-1" data-line-number="1">my_matrix =<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/with">with</a></span>(septic_patients, <span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/matrix">matrix</a></span>(<span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/c">c</a></span>(age, gender), <span class="dt">ncol =</span> <span class="dv">2</span>))</a>
-<a class="sourceLine" id="cb15-2" data-line-number="2"><span class="kw"><a href="../reference/freq.html">freq</a></span>(my_matrix)</a></code></pre></div>
-<p>For lists, subsetting is possible:</p>
-<div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb16-1" data-line-number="1">my_list =<span class="st"> </span><span class="kw"><a href="https://www.rdocumentation.org/packages/base/topics/list">list</a></span>(<span class="dt">age =</span> septic_patients<span class="op">$</span>age, <span class="dt">gender =</span> septic_patients<span class="op">$</span>gender)</a>
-<a class="sourceLine" id="cb16-2" data-line-number="2">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(age)</a>
-<a class="sourceLine" id="cb16-3" data-line-number="3">my_list <span class="op">%&gt;%</span><span class="st"> </span><span class="kw"><a href="../reference/freq.html">freq</a></span>(gender)</a></code></pre></div>
-</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 %&gt;% select(amox, cipr) %&gt;% count_IR() # which is the same as: septic_patients %&gt;% count_IR(amox, cipr)</li>
 </ul>
+<p>septic_patients %&gt;% portion_S(amcl) septic_patients %&gt;% portion_S(amcl, gent) septic_patients %&gt;% 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 %&gt;% freq(age) my_list %&gt;% freq(gender) ```</p>
 </div>
 <div id="other-2" class="section level4">
 <h4 class="hasAnchor">
@@ -654,21 +535,15 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <a href="#new-3" class="anchor"></a>New</h4>
 <ul>
 <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>
+<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>
 <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>
-<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:
-<ul>
+<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>
 <li>Universal: amoxicillin, amoxicillin/clavlanic acid, cefuroxime, piperacillin/tazobactam, ciprofloxacin, trimethoprim/sulfamethoxazole</li>
 <li>Gram-positive: vancomycin, teicoplanin, tetracycline, erythromycin, oxacillin, rifampicin</li>
 <li>Gram-negative: gentamicin, tobramycin, colistin, cefotaxime, ceftazidime, meropenem</li>
-</ul>
-</li>
 <li>Support for <code>ggplot2</code>
-<ul>
+</li>
 <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>New wrapper function <code>ggplot_rsi</code> to apply all above functions on a data set:
@@ -679,32 +554,22 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 </li>
 </ul>
 </li>
-</ul>
-</li>
-<li>Determining bacterial ID:
-<ul>
+<li>Determining bacterial ID:</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>
 <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>
-</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>Function <code>g.test</code> to perform the Χ<sup>2</sup> distributed <a href="https://en.wikipedia.org/wiki/G-test"><em>G</em>-test</a>, which use is the same as <code>chisq.test</code>
 </li>
-<li>
-<del>Function <code>ratio</code> to transform a vector of values to a preset ratio</del>
-<ul>
+<li><del>Function <code>ratio</code> to transform a vector of values to a preset ratio</del></li>
 <li><del>For example: <code><a href="../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>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>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>):
-<ul>
+<li>New for frequency tables (function <code>freq</code>):</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>table</code> to use as input: <code><a href="../reference/freq.html">freq(table(x, y))</a></code>
@@ -719,8 +584,6 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <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><a href="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>
-</li>
-</ul>
 </div>
 <div id="changed-3" class="section level4">
 <h4 class="hasAnchor">
@@ -742,27 +605,21 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 </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>
-<li>Combined MIC/RSI values will now be coerced by the <code>rsi</code> and <code>mic</code> functions:
-<ul>
+<li>Combined MIC/RSI values will now be coerced by the <code>rsi</code> and <code>mic</code> functions:</li>
 <li>
 <code><a href="../reference/as.rsi.html">as.rsi("&lt;=0.002; S")</a></code> will return <code>S</code>
 </li>
 <li>
 <code><a href="../reference/as.mic.html">as.mic("&lt;=0.002; S")</a></code> will return <code>&lt;=0.002</code>
 </li>
-</ul>
-</li>
 <li>Now possible to coerce MIC values with a space between operator and value, i.e. <code><a href="../reference/as.mic.html">as.mic("&lt;= 0.002")</a></code> now works</li>
 <li>Classes <code>rsi</code> and <code>mic</code> do not add the attribute <code>package.version</code> anymore</li>
 <li>Added <code>"groups"</code> option for <code><a href="../reference/atc_property.html">atc_property(..., property)</a></code>. It will return a vector of the ATC hierarchy as defined by the <a href="https://www.whocc.no/atc/structure_and_principles/">WHO</a>. The new function <code>atc_groups</code> is a convenient wrapper around this.</li>
 <li>Build-in host check for <code>atc_property</code> as it requires the host set by <code>url</code> to be responsive</li>
 <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> (<a href="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>)
-<ul>
+<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>So <code>yourdata %&gt;% select(genus, species) %&gt;% as.bactid()</code> now also works</li>
-</ul>
-</li>
 <li>Other small fixes</li>
 </ul>
 </div>
@@ -770,14 +627,11 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <h4 class="hasAnchor">
 <a href="#other-3" class="anchor"></a>Other</h4>
 <ul>
-<li>Added integration tests (check if everything works as expected) for all releases of R 3.1 and higher
-<ul>
+<li>Added integration tests (check if everything works as expected) for all releases of R 3.1 and higher</li>
 <li>Linux and macOS: <a href="https://travis-ci.org/msberends/AMR" class="uri">https://travis-ci.org/msberends/AMR</a>
 </li>
 <li>Windows: <a href="https://ci.appveyor.com/project/msberends/amr" class="uri">https://ci.appveyor.com/project/msberends/amr</a>
 </li>
-</ul>
-</li>
 <li>Added thesis advisors to DESCRIPTION file</li>
 </ul>
 </div>
@@ -792,17 +646,14 @@ These functions use <code><a href="../reference/as.atc.html">as.atc()</a></code>
 <ul>
 <li>Full support for Windows, Linux and macOS</li>
 <li>Full support for old R versions, only R-3.0.0 (April 2013) or later is needed (needed packages may have other dependencies)</li>
-<li>Function <code>n_rsi</code> to count cases where antibiotic test results were available, to be used in conjunction with <code><a href="https://www.rdocumentation.org/packages/dplyr/topics/summarise">dplyr::summarise</a></code>, see ?rsi</li>
+<li>Function <code>n_rsi</code> to count cases where antibiotic test results were available, to be used in conjunction with <code><a href="https://dplyr.tidyverse.org/reference/summarise.html">dplyr::summarise</a></code>, see ?rsi</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>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.
-<ul>
+<li>Function <code>MDRO</code> to <strong>determine Multi Drug Resistant Organisms (MDRO)</strong> with support for country-specific guidelines.</li>
 <li>
 <a href="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>
-</ul>
-</li>
 <li>New algorithm to determine weighted isolates, can now be <code>"points"</code> or <code>"keyantibiotics"</code>, see <code><a href="../reference/first_isolate.html">?first_isolate</a></code>
 </li>
 <li>New print format for <code>tibble</code>s and <code>data.table</code>s</li>

docs/pkgdown.yml

@@ -1,4 +1,4 @@
-pandoc: 2.3.1
+pandoc: 1.17.2
 pkgdown: 1.3.0
 pkgdown_sha: ~
 articles:

vignettes/AMR.Rmd

@@ -25,7 +25,7 @@ knitr::opts_chunk$set(
 
 **Note:** values on this page will change with every website update since they are based on randomly created values and the page was written in [RMarkdown](https://rmarkdown.rstudio.com/). However, the methodology remains unchanged. This page was generated on `r format(Sys.Date(), "%d %B %Y")`.
 
-## Introduction
+# Introduction
 
 For this tutorial, we will create fake demonstration data to work with. 
 
@@ -54,12 +54,12 @@ library(AMR)
 # install.packages(c("tidyverse", "AMR"))
 ```
 
-## Creation of data
+# Creation of data
 We will create some fake example data to use for analysis. For antimicrobial resistance analysis, we need at least: a patient ID, name or code of a microorganism, a date and antimicrobial results (an antibiogram). It could also include a specimen type (e.g. to filter on blood or urine), the ward type (e.g. to filter on ICUs). 
 
 With additional columns (like a hospital name, the patients gender of even [well-defined] clinical properties) you can do a comparative analysis, as this tutorial will demonstrate too.
 
-#### Patients
+## Patients
 To start with patients, we need a unique list of patients. 
 
 ```{r create patients}
@@ -76,7 +76,7 @@ patients_table <- data.frame(patient_id = patients,
 
 The first 135 patient IDs are now male, the other 125 are female.
 
-#### Dates
+## Dates
 Let's pretend that our data consists of blood cultures isolates from 1 January 2010 until 1 January 2018. 
 
 ```{r create dates}
@@ -93,7 +93,7 @@ bacteria <- c("Escherichia coli", "Staphylococcus aureus",
               "Streptococcus pneumoniae", "Klebsiella pneumoniae")
 ```
 
-#### Other variables
+## Other variables
 For completeness, we can also add the hospital where the patients was admitted and we need to define valid antibmicrobial results for our randomisation:
 
 ```{r create other}
@@ -101,7 +101,7 @@ hospitals <- c("Hospital A", "Hospital B", "Hospital C", "Hospital D")
 ab_interpretations <- c("S", "I", "R")
 ```
 
-#### Put everything together
+## Put everything together
 
 Using the `sample()` function, we can randomly select items from all objects we defined earlier. To let our fake data reflect reality a bit, we will also approximately define the probabilities of bacteria and the antibiotic results with the `prob` parameter.
 
@@ -134,7 +134,7 @@ knitr::kable(head(data), align = "c")
 
 Now, let's start the cleaning and the analysis!
 
-## Cleaning the data
+# Cleaning the data
 Use the frequency table function `freq()` to look specifically for unique values in any variable. For example, for the `gender` variable:
 
 ```{r freq gender 1, eval = FALSE}
@@ -168,7 +168,7 @@ Because the amoxicillin (column `amox`) and amoxicillin/clavulanic acid (column
 data <- eucast_rules(data, col_mo = "bacteria")
 ```
 
-## Adding new variables
+# Adding new variables
 Now that we have the microbial ID, we can add some taxonomic properties:
 
 ```{r new taxo}
@@ -178,7 +178,7 @@ data <- data %>%
          species = mo_species(bacteria))
 ```
 
-### First isolates
+## First isolates
 We also need to know which isolates we can *actually* use for analysis.
 
 To conduct an analysis of antimicrobial resistance, you must [only include the first isolate of every patient per episode](https://www.ncbi.nlm.nih.gov/pubmed/17304462) (Hindler *et al.*, Clin Infect Dis. 2007). If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following weeks (yes, some countries like the Netherlands have these blood drawing policies). The resistance percentage of oxacillin of all \emph{S. aureus} isolates would be overestimated, because you included this MRSA more than once. It would clearly be [selection bias](https://en.wikipedia.org/wiki/Selection_bias).
@@ -194,7 +194,7 @@ data <- data %>%
   mutate(first = first_isolate(.))
 ```
 
-So only `r AMR:::percent(sum(data$first) / nrow(data))` is suitable for resistance analysis! We can now filter on is with the `filter()` function, also from the `dplyr` package:
+So only `r AMR:::percent(sum(data$first) / nrow(data))` is suitable for resistance analysis! We can now filter on it with the `filter()` function, also from the `dplyr` package:
 
 ```{r 1st isolate filter}
 data_1st <- data %>% 
@@ -207,7 +207,7 @@ data_1st <- data %>%
   filter_first_isolate()
 ```
 
-### First *weighted* isolates
+## First *weighted* isolates
 We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Imagine this data, sorted on date:
 
 ```{r, echo = FALSE, message = FALSE, warning = FALSE, results = 'asis'}
@@ -226,7 +226,7 @@ weighted_df %>%
   knitr::kable(align = "c")
 ```
 
-Only `r sum(weighted_df$first)` isolates are marked as 'first' according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and show be included too. This is why we weigh isolates, based on their antibiogram. The `key_antibiotics()` function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.
+Only `r sum(weighted_df$first)` isolates are marked as 'first' according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The `key_antibiotics()` function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.
 
 If a column exists with a name like 'key(...)ab' the `first_isolate()` function will automatically use it and determine the first weighted isolates. Mind the NOTEs in below output: 
 
@@ -252,7 +252,7 @@ weighted_df2 %>%
   knitr::kable(align = "c")
 ```
 
-Instead of `r sum(weighted_df$first)`, now `r sum(weighted_df2$first_weighted)` isolates are flagged. In total, `r AMR:::percent(sum(data$first_weighted) / nrow(data))` of all isolates are marked 'first weighted' - `r AMR:::percent((sum(data$first_weighted) / nrow(data)) -- (sum(data$first) / nrow(data)))` more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.
+Instead of `r sum(weighted_df$first)`, now `r sum(weighted_df2$first_weighted)` isolates are flagged. In total, `r AMR:::percent(sum(data$first_weighted) / nrow(data))` of all isolates are marked 'first weighted' - `r AMR:::percent((sum(data$first_weighted) / nrow(data)) - (sum(data$first) / nrow(data)))` more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.
 
 As with `filter_first_isolate()`, there's a shortcut for this new algorithm too:
 ```{r 1st isolate filter 3, results = 'hide', message = FALSE, warning = FALSE}
@@ -280,8 +280,9 @@ knitr::kable(head(data_1st), align = "c")
 
 Time for the analysis!
 
-## Analysing the data
+# Analysing the data
 You might want to start by getting an idea of how the data is distributed. It's an important start, because it also decides how you will continue your analysis. 
+
 ## Dispersion of species
 To just get an idea how the species are distributed, create a frequency table with our `freq()` function. We created the `genus` and `species` column earlier based on the microbial ID. With `paste()`, we can concatenate them together.
 
@@ -301,7 +302,7 @@ data_1st %>%
   freq(genus, species, header = TRUE)
 ```
 
-### Resistance percentages
+## Resistance percentages
 
 The functions `portion_R`, `portion_RI`, `portion_I`, `portion_IS` and `portion_S` can be used to determine the portion of a specific antimicrobial outcome. They can be used on their own:
 
@@ -371,7 +372,7 @@ data_1st %>%
   geom_col(position = "dodge2")
 ```
 
-### Plots
+## Plots
 To show results in plots, most R users would nowadays use the `ggplot2` package. This package lets you create plots in layers. You can read more about it [on their website](https://ggplot2.tidyverse.org/). A quick example would look like these syntaxes:
 
 ```{r plot 2, eval = FALSE}
@@ -433,7 +434,7 @@ data_1st %>%
   coord_flip()
 ```
 
-### Using an independence test to compare resistance
+## Independence test
 
 The next example uses the included `septic_patients`, which is an anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found in septic patients in 4 different hospitals in the Netherlands, between 2001 and 2017. It is true, genuine data. This `data.frame` can be used to practice AMR analysis.