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<a class="navbar-brand me-2" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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<a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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@ -142,7 +142,7 @@ package.</p>
<span><span class="co">#&gt; <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">dplyr</span>::<span style="color: #00BB00;">filter()</span> masks <span style="color: #0000BB;">stats</span>::filter()</span></span>
<span><span class="co">#&gt; <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">dplyr</span>::<span style="color: #00BB00;">lag()</span> masks <span style="color: #0000BB;">stats</span>::lag()</span></span>
<span><span class="co">#&gt; <span style="color: #BB0000;">✖</span> <span style="color: #0000BB;">recipes</span>::<span style="color: #00BB00;">step()</span> masks <span style="color: #0000BB;">stats</span>::step()</span></span>
<span><span class="co">#&gt; <span style="color: #0000BB;">•</span> Use suppressPackageStartupMessages() to eliminate package startup messages</span></span>
<span><span class="co">#&gt; <span style="color: #0000BB;">•</span> Use <span style="color: #00BB00;">tidymodels_prefer()</span> to resolve common conflicts.</span></span>
<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span> <span class="co"># For AMR data analysis</span></span>
<span></span>
<span><span class="co"># Load the example_isolates dataset</span></span>

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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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@ -31,7 +31,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9134</small>
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2
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@ -31,7 +31,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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articles/welcome_to_AMR.html
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@ -31,7 +31,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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authors.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
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2
index.html
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@ -34,7 +34,7 @@
<a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9134</small>
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news/index.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9134</small>
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@ -48,18 +48,18 @@
</div>
<div class="section level2">
<h2 class="pkg-version" data-toc-text="2.1.1.9133" id="amr-2119133">AMR 2.1.1.9133<a class="anchor" aria-label="anchor" href="#amr-2119133"></a></h2>
<h2 class="pkg-version" data-toc-text="2.1.1.9134" id="amr-2119134">AMR 2.1.1.9134<a class="anchor" aria-label="anchor" href="#amr-2119134"></a></h2>
<p><em>(this beta version will eventually become v3.0. We’re happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using <a href="https://msberends.github.io/AMR/#latest-development-version">the instructions here</a>.)</em></p>
<div class="section level5">
<h5 id="a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9133">A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9133"></a></h5>
<h5 id="a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9134">A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9134"></a></h5>
<p>This package now supports not only tools for AMR data analysis in clinical settings, but also for veterinary and environmental microbiology. This was made possible through a collaboration with the <a href="https://www.upei.ca/avc" class="external-link">University of Prince Edward Island’s Atlantic Veterinary College</a>, Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.</p>
</div>
<div class="section level3">
<h3 id="breaking-2-1-1-9133">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9133"></a></h3>
<h3 id="breaking-2-1-1-9134">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9134"></a></h3>
<ul><li>Removed all functions and references that used the deprecated <code>rsi</code> class, which were all replaced with their <code>sir</code> equivalents two years ago</li>
</ul></div>
<div class="section level3">
<h3 id="new-2-1-1-9133">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9133"></a></h3>
<h3 id="new-2-1-1-9134">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9134"></a></h3>
<ul><li>
<strong>One Health implementation</strong>
<ul><li>Function <code><a href="../reference/as.sir.html">as.sir()</a></code> now has extensive support for veterinary breakpoints from CLSI. Use <code>breakpoint_type = "animal"</code> and set the <code>host</code> argument to a variable that contains animal species names.</li>
@ -109,7 +109,7 @@
</ul></li>
</ul></div>
<div class="section level3">
<h3 id="changed-2-1-1-9133">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9133"></a></h3>
<h3 id="changed-2-1-1-9134">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9134"></a></h3>
<ul><li>SIR interpretation
<ul><li>It is now possible to use column names for argument <code>ab</code>, <code>mo</code>, and <code>uti</code>: <code>as.sir(..., ab = "column1", mo = "column2", uti = "column3")</code>. This greatly improves the flexibility for users.</li>
<li>Users can now set their own criteria (using regular expressions) as to what should be considered S, I, R, SDD, and NI.</li>
@ -172,7 +172,7 @@
</ul></li>
</ul></div>
<div class="section level3">
<h3 id="other-2-1-1-9133">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9133"></a></h3>
<h3 id="other-2-1-1-9134">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9134"></a></h3>
<ul><li>Added Dr. Larisse Bolton as contributor for her fantastic implementation of WISCA in a mathematically solid way</li>
<li>Added Matthew Saab, Dr. Jordan Stull, and Prof. Javier Sanchez as contributors for their tremendous input on veterinary breakpoints and interpretations</li>
<li>Greatly improved <code>vctrs</code> integration, a Tidyverse package working in the background for many Tidyverse functions. For users, this means that functions such as <code>dplyr</code>’s <code><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/rowwise.html" class="external-link">rowwise()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/c_across.html" class="external-link">c_across()</a></code> are now supported for e.g. columns of class <code>mic</code>. Despite this, this <code>AMR</code> package is still zero-dependent on any other package, including <code>dplyr</code> and <code>vctrs</code>.</li>
@ -180,7 +180,7 @@
<li>Stopped support for SAS (<code>.xpt</code>) files, since their file structure and extremely inefficient and requires more disk space than GitHub allows in a single commit.</li>
</ul></div>
<div class="section level3">
<h3 id="older-versions-2-1-1-9133">Older Versions<a class="anchor" aria-label="anchor" href="#older-versions-2-1-1-9133"></a></h3>
<h3 id="older-versions-2-1-1-9134">Older Versions<a class="anchor" aria-label="anchor" href="#older-versions-2-1-1-9134"></a></h3>
<p>This changelog only contains changes from AMR v3.0 (February 2025) and later.</p>
<ul><li>For prior v2 versions, please see <a href="https://github.com/msberends/AMR/blob/v2.1.1/NEWS.md" class="external-link">our v2 archive</a>.</li>
<li>For prior v1 versions, please see <a href="https://github.com/msberends/AMR/blob/v1.8.2/NEWS.md" class="external-link">our v1 archive</a>.</li>

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pkgdown.yml
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@ -12,7 +12,7 @@ articles:
resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html
WHONET: WHONET.html
last_built: 2025-01-27T21:47Z
last_built: 2025-01-27T22:15Z
urls:
reference: https://msberends.github.io/AMR/reference
article: https://msberends.github.io/AMR/articles

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reference/AMR-deprecated.html
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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reference/AMR-options.html
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reference/AMR.html
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@ -21,7 +21,7 @@ The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish,
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/WHOCC.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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reference/ab_from_text.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/ab_property.html
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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/add_custom_antimicrobials.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/add_custom_microorganisms.html
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reference/age.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/antibiogram.html
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@ -9,7 +9,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
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@ -294,8 +294,8 @@ Adhering to previously described approaches (see Source) and especially the Baye
<h3 id="plotting">Plotting<a class="anchor" aria-label="anchor" href="#plotting"></a></h3>
<p>All types of antibiograms as listed above can be plotted (using <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">ggplot2::autoplot()</a></code> or base <span style="R">R</span>'s <code><a href="plot.html">plot()</a></code> and <code><a href="https://rdrr.io/r/graphics/barplot.html" class="external-link">barplot()</a></code>).</p>
<p>THe outcome of <code>antibiogram()</code> can also be used directly in R Markdown / Quarto (i.e., <code>knitr</code>) for reports. In this case, <code><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">knitr::kable()</a></code> will be applied automatically and microorganism names will even be printed in italics at default (see argument <code>italicise</code>).</p>
<p>All types of antibiograms as listed above can be plotted (using <code><a href="https://ggplot2.tidyverse.org/reference/autoplot.html" class="external-link">ggplot2::autoplot()</a></code> or base <span style="R">R</span>'s <code><a href="plot.html">plot()</a></code> and <code><a href="https://rdrr.io/r/graphics/barplot.html" class="external-link">barplot()</a></code>). As mentioned above, the numeric values of an antibiogram are stored in a long format as the <a href="https://rdrr.io/r/base/attributes.html" class="external-link">attribute</a> <code>long_numeric</code>. You can retrieve them using <code>attributes(x)$long_numeric</code>, where <code>x</code> is the outcome of <code>antibiogram()</code> or <code>wisca()</code>.</p>
<p>The outcome of <code>antibiogram()</code> can also be used directly in R Markdown / Quarto (i.e., <code>knitr</code>) for reports. In this case, <code><a href="https://rdrr.io/pkg/knitr/man/kable.html" class="external-link">knitr::kable()</a></code> will be applied automatically and microorganism names will even be printed in italics at default (see argument <code>italicise</code>).</p>
<p>You can also use functions from specific 'table reporting' packages to transform the output of <code>antibiogram()</code> to your needs, e.g. with <code>flextable::as_flextable()</code> or <code>gt::gt()</code>.</p>
</div>
@ -305,7 +305,7 @@ Adhering to previously described approaches (see Source) and especially the Baye
<p>WISCA, as outlined by Barbieri <em>et al.</em> (<a href="https://doi.org/10.1186/s13756-021-00939-2" class="external-link">doi:10.1186/s13756-021-00939-2</a>
<p>WISCA, as outlined by Bielicki <em>et al.</em> (<a href="https://doi.org/10.1093/jac/dkv397" class="external-link">doi:10.1093/jac/dkv397</a>
), stands for Weighted-Incidence Syndromic Combination Antibiogram, which estimates the probability of adequate empirical antimicrobial regimen coverage for specific infection syndromes. This method leverages a Bayesian hierarchical logistic regression framework with random effects for pathogens and regimens, enabling robust estimates in the presence of sparse data.</p>
<p>The Bayesian model assumes conjugate priors for parameter estimation. For example, the coverage probability \(\theta\) for a given antimicrobial regimen is modelled using a Beta distribution as a prior:</p>
<p>$$\theta \sim \text{Beta}(\alpha_0, \beta_0)$$</p>
@ -313,13 +313,17 @@ Adhering to previously described approaches (see Source) and especially the Baye
<p>$$y \sim \text{Binomial}(n, \theta)$$</p>
<p>Posterior parameter estimates are obtained by combining the prior and likelihood using Bayes' theorem. The posterior distribution of \(\theta\) is also a Beta distribution:</p>
<p>$$\theta | y \sim \text{Beta}(\alpha_0 + y, \beta_0 + n - y)$$</p>
<p>Pathogen incidence, representing the proportion of infections caused by different pathogens, is modelled using a Dirichlet distribution, which is the natural conjugate prior for multinomial outcomes. The Dirichlet distribution is parameterised by a vector of concentration parameters \(\alpha\), where each \(\alpha_i\) corresponds to a specific pathogen. The prior is typically chosen to be uniform (\(\alpha_i = 1\)), reflecting an assumption of equal prior probability across pathogens.</p>
<p>The posterior distribution of pathogen incidence is then given by:</p>
<p>$$\text{Dirichlet}(\alpha_1 + n_1, \alpha_2 + n_2, \dots, \alpha_K + n_K)$$</p>
<p>where \(n_i\) is the number of infections caused by pathogen \(i\) observed in the data. For practical implementation, pathogen incidences are sampled from their posterior using normalised Gamma-distributed random variables:</p>
<p>$$x_i \sim \text{Gamma}(\alpha_i + n_i, 1)$$
$$p_i = \frac{x_i}{\sum_{j=1}^K x_j}$$</p>
<p>where \(x_i\) represents unnormalised pathogen counts, and \(p_i\) is the normalised proportion for pathogen \(i\).</p>
<p>For hierarchical modelling, pathogen-level effects (e.g., differences in resistance patterns) and regimen-level effects are modelled using Gaussian priors on log-odds. This hierarchical structure ensures partial pooling of estimates across groups, improving stability in strata with small sample sizes. The model is implemented using Hamiltonian Monte Carlo (HMC) sampling.</p>
<p>Stratified results can be provided based on covariates such as age, sex, and clinical complexity (e.g., prior antimicrobial treatments or renal/urological comorbidities) using <code>dplyr</code>'s <code><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a></code> as a pre-processing step before running <code>wisca()</code>. In this case, posterior odds ratios (ORs) are derived to quantify the effect of these covariates on coverage probabilities:</p>
<p>$$\text{OR}_{\text{covariate}} = \frac{\exp(\beta_{\text{covariate}})}{\exp(\beta_0)}$$</p>
<p>By combining empirical data with prior knowledge, WISCA overcomes the limitations
of traditional combination antibiograms, offering disease-specific, patient-stratified
estimates with robust uncertainty quantification. This tool is invaluable for antimicrobial
stewardship programs and empirical treatment guideline refinement.</p>
<p>By combining empirical data with prior knowledge, WISCA overcomes the limitations of traditional combination antibiograms, offering disease-specific, patient-stratified estimates with robust uncertainty quantification. This tool is invaluable for antimicrobial stewardship programs and empirical treatment guideline refinement.</p>
</div>
<div class="section level2">
<h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a></h2>

2
reference/antibiotics.html
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@ -7,7 +7,7 @@
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reference/antimicrobial_class_selectors.html
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@ -17,7 +17,7 @@ my_data_with_all_these_columns %&amp;gt;%
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reference/as.sir.html
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@ -21,7 +21,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
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@ -757,16 +757,16 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 57 × 16</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> datetime index ab_given mo_given host_given ab mo </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">*</span> <span style="color: #949494; font-style: italic;">&lt;dttm&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;ab&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2025-01-27 <span style="color: #949494;">21:48:11</span> 4 AMX B_STRPT… human AMX B_STRPT_PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2025-01-27 <span style="color: #949494;">21:48:18</span> 4 genta Escheri… human GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2025-01-27 <span style="color: #949494;">21:48:18</span> 4 genta Escheri… human GEN B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2025-01-27 <span style="color: #949494;">21:48:19</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2025-01-27 <span style="color: #949494;">21:48:19</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2025-01-27 <span style="color: #949494;">21:48:11</span> 3 AMX B_STRPT… human AMX B_STRPT_PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2025-01-27 <span style="color: #949494;">21:48:18</span> 3 tobra Escheri… human TOB B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2025-01-27 <span style="color: #949494;">21:48:18</span> 3 tobra Escheri… human TOB B_[ORD]_ENTRBCTR</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2025-01-27 <span style="color: #949494;">21:48:19</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2025-01-27 <span style="color: #949494;">21:48:19</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 4 genta Escheri… cattle GEN B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 3 tobra Escheri… horses TOB B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 2 cipro Escheri… dogs CIP B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 2 cipro Escheri… dogs CIP B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2025-01-27 <span style="color: #949494;">22:16:01</span> 2 nitrofu… E. coli human NIT B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2025-01-27 <span style="color: #949494;">22:16:02</span> 2 nitrofu… E. coli human NIT B_ESCHR_COLI </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 1 tobra bacteria human TOB B_[KNG]_BACTERIA</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2025-01-27 <span style="color: #949494;">22:16:00</span> 1 genta bacteria human GEN B_[KNG]_BACTERIA</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 47 more rows</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 9 more variables: host &lt;chr&gt;, method &lt;chr&gt;, input &lt;dbl&gt;, outcome &lt;sir&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># notes &lt;chr&gt;, guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;,</span></span>

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@ -21,7 +21,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
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@ -9,7 +9,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
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@ -9,7 +9,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
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2
reference/example_isolates.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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2
reference/example_isolates_unclean.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/export_ncbi_biosample.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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2
reference/first_isolate.html
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@ -9,7 +9,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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2
reference/g.test.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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reference/get_episode.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/ggplot_pca.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/ggplot_sir.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/guess_ab_col.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/index.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/intrinsic_resistant.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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reference/italicise_taxonomy.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/join.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/key_antimicrobials.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/kurtosis.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/like.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/mdro.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/mean_amr_distance.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/microorganisms.codes.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/microorganisms.groups.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9134</small>
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2
reference/microorganisms.html
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@ -9,7 +9,7 @@ This data set is carefully crafted, yet made 100% reproducible from public and a
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<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9134</small>
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2
reference/mo_matching_score.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9134</small>
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2
reference/mo_property.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9134</small>
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2
reference/mo_source.html
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@ -9,7 +9,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/pca.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9134</small>
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2
reference/plot.html
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@ -9,7 +9,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/proportion.html
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@ -9,7 +9,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/random.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9134</small>
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2
reference/resistance_predict.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/skewness.html
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@ -9,7 +9,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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2
reference/top_n_microorganisms.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9133</small>
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2
reference/translate.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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search.json
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