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@@ -91,7 +91,7 @@
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website update since they are based on randomly created values and the
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page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
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Markdown</a>. However, the methodology remains unchanged. This page was
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generated on 01 September 2025.</p>
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generated on 03 September 2025.</p>
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<div class="section level2">
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<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
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</h2>
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@@ -147,21 +147,21 @@ make the structure of your data generally look like this:</p>
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</tr></thead>
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<tbody>
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<tr class="odd">
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<td align="center">2025-09-01</td>
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<td align="center">2025-09-03</td>
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<td align="center">abcd</td>
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<td align="center">Escherichia coli</td>
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<td align="center">S</td>
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<td align="center">S</td>
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</tr>
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<tr class="even">
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<td align="center">2025-09-01</td>
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<td align="center">2025-09-03</td>
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<td align="center">abcd</td>
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<td align="center">Escherichia coli</td>
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<td align="center">S</td>
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<td align="center">R</td>
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</tr>
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<tr class="odd">
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<td align="center">2025-09-01</td>
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<td align="center">2025-09-03</td>
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<td align="center">efgh</td>
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<td align="center">Escherichia coli</td>
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<td align="center">R</td>
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<main id="main" class="col-md-9"><div class="page-header">
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<img src="../logo.svg" class="logo" alt=""><h1>Download data sets for download / own use</h1>
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<h4 data-toc-skip class="date">01 September 2025</h4>
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<h4 data-toc-skip class="date">03 September 2025</h4>
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<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
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<div class="d-none name"><code>datasets.Rmd</code></div>
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@@ -115,7 +115,7 @@ column names:<br><em>mo</em>, <em>fullname</em>, <em>status</em>, <em>kingdom</e
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<em>snomed</em>.</p>
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<p>This data set is in R available as <code>microorganisms</code>, after
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you load the <code>AMR</code> package.</p>
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<p>It was last updated on 1 September 2025 15:00:00 UTC. Find more info
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<p>It was last updated on 3 September 2025 09:50:16 UTC. Find more info
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about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/microorganisms.html">data set
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here</a>.</p>
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<p><strong>Direct download links:</strong></p>
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@@ -424,7 +424,7 @@ column names:<br><em>ab</em>, <em>cid</em>, <em>name</em>, <em>group</em>, <em>a
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<em>iv_ddd</em>, <em>iv_units</em>, and <em>loinc</em>.</p>
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<p>This data set is in R available as <code>antimicrobials</code>, after
|
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you load the <code>AMR</code> package.</p>
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<p>It was last updated on 1 September 2025 15:00:00 UTC. Find more info
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<p>It was last updated on 3 September 2025 09:50:16 UTC. Find more info
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about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/antimicrobials.html">data set
|
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here</a>.</p>
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<p><strong>Direct download links:</strong></p>
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@@ -602,7 +602,7 @@ column names:<br><em>guideline</em>, <em>type</em>, <em>host</em>, <em>method</e
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<em>breakpoint_R</em>, <em>uti</em>, and <em>is_SDD</em>.</p>
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<p>This data set is in R available as <code>clinical_breakpoints</code>,
|
||||
after you load the <code>AMR</code> package.</p>
|
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<p>It was last updated on 1 September 2025 15:00:00 UTC. Find more info
|
||||
<p>It was last updated on 3 September 2025 09:50:16 UTC. Find more info
|
||||
about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/clinical_breakpoints.html">data
|
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set here</a>.</p>
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<p><strong>Direct download links:</strong></p>
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@@ -790,7 +790,7 @@ column names:<br><em>mo_group</em>, <em>mo</em>, <em>mo_group_name</em>, and
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<p>This data set is in R available as
|
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<code>microorganisms.groups</code>, after you load the <code>AMR</code>
|
||||
package.</p>
|
||||
<p>It was last updated on 1 September 2025 15:00:00 UTC. Find more info
|
||||
<p>It was last updated on 3 September 2025 09:50:16 UTC. Find more info
|
||||
about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/microorganisms.groups.html">data
|
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set here</a>.</p>
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<p><strong>Direct download links:</strong></p>
|
||||
@@ -880,7 +880,7 @@ Resistance<a class="anchor" aria-label="anchor" href="#intrinsic_resistant-intri
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column names:<br><em>mo</em> and <em>ab</em>.</p>
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<p>This data set is in R available as <code>intrinsic_resistant</code>,
|
||||
after you load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 1 September 2025 15:00:00 UTC. Find more info
|
||||
<p>It was last updated on 3 September 2025 09:50:16 UTC. Find more info
|
||||
about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/intrinsic_resistant.html">data set
|
||||
here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
@@ -1156,7 +1156,7 @@ column names:<br><em>ab</em>, <em>name</em>, <em>type</em>, <em>dose</em>,
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<em>original_txt</em>, and <em>eucast_version</em>.</p>
|
||||
<p>This data set is in R available as <code>dosage</code>, after you
|
||||
load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 1 September 2025 15:00:00 UTC. Find more info
|
||||
<p>It was last updated on 3 September 2025 09:50:16 UTC. Find more info
|
||||
about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/dosage.html">data set
|
||||
here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
@@ -1294,7 +1294,7 @@ column names:<br><em>date</em>, <em>patient</em>, <em>age</em>, <em>gender</em>,
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<em>MUP</em>, and <em>RIF</em>.</p>
|
||||
<p>This data set is in R available as <code>example_isolates</code>,
|
||||
after you load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 1 September 2025 15:00:00 UTC. Find more info
|
||||
<p>It was last updated on 3 September 2025 09:50:16 UTC. Find more info
|
||||
about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/example_isolates.html">data set
|
||||
here</a>.</p>
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<p><strong>Example content</strong></p>
|
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@@ -1700,7 +1700,7 @@ column names:<br><em>patient_id</em>, <em>hospital</em>, <em>date</em>,
|
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<p>This data set is in R available as
|
||||
<code>example_isolates_unclean</code>, after you load the
|
||||
<code>AMR</code> package.</p>
|
||||
<p>It was last updated on 1 September 2025 15:00:00 UTC. Find more info
|
||||
<p>It was last updated on 3 September 2025 09:50:16 UTC. Find more info
|
||||
about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/example_isolates_unclean.html">data
|
||||
set here</a>.</p>
|
||||
<p><strong>Example content</strong></p>
|
||||
@@ -1798,7 +1798,7 @@ set here</a>.</p>
|
||||
column names:<br><em>code</em> and <em>mo</em>.</p>
|
||||
<p>This data set is in R available as <code>microorganisms.codes</code>,
|
||||
after you load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 1 September 2025 15:00:00 UTC. Find more info
|
||||
<p>It was last updated on 3 September 2025 09:50:16 UTC. Find more info
|
||||
about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/microorganisms.codes.html">data
|
||||
set here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
@@ -1870,7 +1870,7 @@ column names:<br><em>av</em>, <em>name</em>, <em>atc</em>, <em>cid</em>,
|
||||
<em>loinc</em>.</p>
|
||||
<p>This data set is in R available as <code>antivirals</code>, after you
|
||||
load the <code>AMR</code> package.</p>
|
||||
<p>It was last updated on 1 September 2025 15:00:00 UTC. Find more info
|
||||
<p>It was last updated on 3 September 2025 09:50:16 UTC. Find more info
|
||||
about the contents, (scientific) source, and structure of this <a href="https://amr-for-r.org/reference/antimicrobials.html">data set
|
||||
here</a>.</p>
|
||||
<p><strong>Direct download links:</strong></p>
|
||||
|
||||
Regular → Executable
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@@ -10,7 +10,7 @@ articles:
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PCA: PCA.html
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WHONET: WHONET.html
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||||
WISCA: WISCA.html
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||||
last_built: 2025-09-01T15:03Z
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||||
last_built: 2025-09-03T09:52Z
|
||||
urls:
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||||
reference: https://amr-for-r.org/reference
|
||||
article: https://amr-for-r.org/articles
|
||||
+10
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@@ -112,16 +112,16 @@
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||||
<span class="r-in"><span></span></span>
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||||
<span class="r-in"><span><span class="va">df</span></span></span>
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<span class="r-out co"><span class="r-pr">#></span> birth_date age age_exact age_at_y2k</span>
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||||
<span class="r-out co"><span class="r-pr">#></span> 1 1980-02-27 45 45.50959 19</span>
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<span class="r-out co"><span class="r-pr">#></span> 2 1953-07-26 72 72.10137 46</span>
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||||
<span class="r-out co"><span class="r-pr">#></span> 3 1949-09-02 75 75.99726 50</span>
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||||
<span class="r-out co"><span class="r-pr">#></span> 4 1986-08-03 39 39.07945 13</span>
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||||
<span class="r-out co"><span class="r-pr">#></span> 5 1932-11-19 92 92.78356 67</span>
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||||
<span class="r-out co"><span class="r-pr">#></span> 6 1949-03-30 76 76.42466 50</span>
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||||
<span class="r-out co"><span class="r-pr">#></span> 7 1996-06-23 29 29.19178 3</span>
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||||
<span class="r-out co"><span class="r-pr">#></span> 8 1963-09-16 61 61.95890 36</span>
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||||
<span class="r-out co"><span class="r-pr">#></span> 9 1952-05-16 73 73.29589 47</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 1952-11-14 72 72.79726 47</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 1980-02-27 45 45.51507 19</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 1953-07-26 72 72.10685 46</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 1949-09-02 76 76.00274 50</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 1986-08-03 39 39.08493 13</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 1932-11-19 92 92.78904 67</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 1949-03-30 76 76.43014 50</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 1996-06-23 29 29.19726 3</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 1963-09-16 61 61.96438 36</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 1952-05-16 73 73.30137 47</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 1952-11-14 72 72.80274 47</span>
|
||||
</code></pre></div>
|
||||
</div>
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</main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
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|
||||
@@ -179,7 +179,7 @@ may affect the computations for subsequent operations.</p></dd>
|
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<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">broom </span> 1.0.9 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">rsample </span> 1.3.1</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">dials </span> 1.4.1 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tibble </span> 3.3.0</span>
|
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<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">infer </span> 1.0.9 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tidyr </span> 1.3.1</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">modeldata </span> 1.5.1 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tune </span> 1.3.0</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">modeldata </span> 1.5.1 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">tune </span> 2.0.0</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">parsnip </span> 1.3.3 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">workflows </span> 1.3.0</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">purrr </span> 1.1.0 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">workflowsets</span> 1.1.1</span>
|
||||
<span class="r-msg co"><span class="r-pr">#></span> <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">recipes </span> 1.3.1 <span style="color: #00BB00;">✔</span> <span style="color: #0000BB;">yardstick </span> 1.3.2</span>
|
||||
|
||||
@@ -415,10 +415,10 @@ Breakpoints are currently implemented from EUCAST 2011-2025 and CLSI 2011-2025,
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 4 × 18</span></span>
|
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<span class="r-out co"><span class="r-pr">#></span> datetime index method ab_given mo_given host_given input_given</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><dttm></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> 2025-09-01 <span style="color: #949494;">15:04:18</span> 1 MIC amoxicillin Escherich… human 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> 2025-09-01 <span style="color: #949494;">15:04:19</span> 1 MIC cipro Escherich… human 0.256 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> 2025-09-01 <span style="color: #949494;">15:04:19</span> 1 DISK tobra Escherich… human 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">4</span> 2025-09-01 <span style="color: #949494;">15:04:19</span> 1 DISK genta Escherich… human 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> 2025-09-03 <span style="color: #949494;">09:53:11</span> 1 MIC amoxicillin Escherich… human 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> 2025-09-03 <span style="color: #949494;">09:53:11</span> 1 MIC cipro Escherich… human 0.256 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> 2025-09-03 <span style="color: #949494;">09:53:11</span> 1 DISK tobra Escherich… human 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">4</span> 2025-09-03 <span style="color: #949494;">09:53:12</span> 1 DISK genta Escherich… human 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 11 more variables: ab <ab>, mo <mo>, host <chr>, input <chr>,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># outcome <sir>, notes <chr>, guideline <chr>, ref_table <chr>, uti <lgl>,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># breakpoint_S_R <chr>, site <chr></span></span>
|
||||
|
||||
+1
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@@ -1 +1 @@
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[{"path":"https://amr-for-r.org/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Conduct AMR data analysis","text":"Conducting AMR data analysis unfortunately requires -depth knowledge different scientific fields, makes hard right. least, requires: Good questions (always start !) reliable data thorough understanding (clinical) epidemiology, understand clinical epidemiological relevance possible bias results thorough understanding (clinical) microbiology/infectious diseases, understand microorganisms causal infections implications pharmaceutical treatment, well understanding intrinsic acquired microbial resistance Experience data analysis microbiological tests results, understand determination limitations MIC values interpretations SIR values Availability biological taxonomy microorganisms probably normalisation factors pharmaceuticals, defined daily doses (DDD) Available (inter-)national guidelines, profound methods apply course, instantly provide knowledge experience. AMR package, aimed providing (1) tools simplify antimicrobial resistance data cleaning, transformation analysis, (2) methods easily incorporate international guidelines (3) scientifically reliable reference data, including requirements mentioned . AMR package enables standardised reproducible AMR data analysis, application evidence-based rules, determination first isolates, translation various codes microorganisms antimicrobial agents, determination (multi-drug) resistant microorganisms, calculation antimicrobial resistance, prevalence future trends.","code":""},{"path":"https://amr-for-r.org/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"Conduct AMR data analysis","text":"tutorial, create fake demonstration data work . can skip Cleaning data already data ready. start analysis, try make structure data generally look like :","code":""},{"path":"https://amr-for-r.org/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"Conduct AMR data analysis","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2 RStudio. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. also use cleaner package, can used cleaning data creating frequency tables. AMR package contains data set example_isolates_unclean, might look data users extracted laboratory systems: AMR data analysis, like microorganism column contain valid, --date taxonomy, antibiotic columns cleaned SIR values well.","code":"library(dplyr) library(ggplot2) library(AMR) # (if not yet installed, install with:) # install.packages(c(\"dplyr\", \"ggplot2\", \"AMR\")) example_isolates_unclean #> # A tibble: 3,000 × 8 #> patient_id hospital date bacteria AMX AMC CIP GEN #> <chr> <chr> <date> <chr> <chr> <chr> <chr> <chr> #> 1 J3 A 2012-11-21 E. coli R I S S #> 2 R7 A 2018-04-03 K. pneumoniae R I S S #> 3 P3 A 2014-09-19 E. coli R S S S #> 4 P10 A 2015-12-10 E. coli S I S S #> 5 B7 A 2015-03-02 E. coli S S S S #> 6 W3 A 2018-03-31 S. aureus R S R S #> 7 J8 A 2016-06-14 E. coli R S S S #> 8 M3 A 2015-10-25 E. coli R S S S #> 9 J3 A 2019-06-19 E. coli S S S S #> 10 G6 A 2015-04-27 S. aureus S S S S #> # ℹ 2,990 more rows # we will use 'our_data' as the data set name for this tutorial our_data <- example_isolates_unclean"},{"path":"https://amr-for-r.org/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"Conduct AMR data analysis","text":".mo(), users can transform arbitrary microorganism names codes current taxonomy. AMR package contains --date taxonomic data. specific, currently included data retrieved 24 Jun 2024. codes AMR packages come .mo() short, still human readable. importantly, .mo() supports kinds input: first character codes denote taxonomic kingdom, Bacteria (B), Fungi (F), Protozoa (P). AMR package also contain functions directly retrieve taxonomic properties, name, genus, species, family, order, even Gram-stain. start mo_ use .mo() internally, still arbitrary user input can used: Now can thus clean data: Apparently, uncertainty translation taxonomic codes. Let’s check : ’s good.","code":"as.mo(\"Klebsiella pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"K. pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"KLEPNE\") #> Class 'mo' #> [1] Line truncated
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[{"path":"https://amr-for-r.org/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Conduct AMR data analysis","text":"Conducting AMR data analysis unfortunately requires -depth knowledge different scientific fields, makes hard right. least, requires: Good questions (always start !) reliable data thorough understanding (clinical) epidemiology, understand clinical epidemiological relevance possible bias results thorough understanding (clinical) microbiology/infectious diseases, understand microorganisms causal infections implications pharmaceutical treatment, well understanding intrinsic acquired microbial resistance Experience data analysis microbiological tests results, understand determination limitations MIC values interpretations SIR values Availability biological taxonomy microorganisms probably normalisation factors pharmaceuticals, defined daily doses (DDD) Available (inter-)national guidelines, profound methods apply course, instantly provide knowledge experience. AMR package, aimed providing (1) tools simplify antimicrobial resistance data cleaning, transformation analysis, (2) methods easily incorporate international guidelines (3) scientifically reliable reference data, including requirements mentioned . AMR package enables standardised reproducible AMR data analysis, application evidence-based rules, determination first isolates, translation various codes microorganisms antimicrobial agents, determination (multi-drug) resistant microorganisms, calculation antimicrobial resistance, prevalence future trends.","code":""},{"path":"https://amr-for-r.org/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"Conduct AMR data analysis","text":"tutorial, create fake demonstration data work . can skip Cleaning data already data ready. start analysis, try make structure data generally look like :","code":""},{"path":"https://amr-for-r.org/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"Conduct AMR data analysis","text":"many uses R, need additional packages AMR data analysis. package works closely together tidyverse packages dplyr ggplot2 RStudio. tidyverse tremendously improves way conduct data science - allows natural way writing syntaxes creating beautiful plots R. also use cleaner package, can used cleaning data creating frequency tables. AMR package contains data set example_isolates_unclean, might look data users extracted laboratory systems: AMR data analysis, like microorganism column contain valid, --date taxonomy, antibiotic columns cleaned SIR values well.","code":"library(dplyr) library(ggplot2) library(AMR) # (if not yet installed, install with:) # install.packages(c(\"dplyr\", \"ggplot2\", \"AMR\")) example_isolates_unclean #> # A tibble: 3,000 × 8 #> patient_id hospital date bacteria AMX AMC CIP GEN #> <chr> <chr> <date> <chr> <chr> <chr> <chr> <chr> #> 1 J3 A 2012-11-21 E. coli R I S S #> 2 R7 A 2018-04-03 K. pneumoniae R I S S #> 3 P3 A 2014-09-19 E. coli R S S S #> 4 P10 A 2015-12-10 E. coli S I S S #> 5 B7 A 2015-03-02 E. coli S S S S #> 6 W3 A 2018-03-31 S. aureus R S R S #> 7 J8 A 2016-06-14 E. coli R S S S #> 8 M3 A 2015-10-25 E. coli R S S S #> 9 J3 A 2019-06-19 E. coli S S S S #> 10 G6 A 2015-04-27 S. aureus S S S S #> # ℹ 2,990 more rows # we will use 'our_data' as the data set name for this tutorial our_data <- example_isolates_unclean"},{"path":"https://amr-for-r.org/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"Conduct AMR data analysis","text":".mo(), users can transform arbitrary microorganism names codes current taxonomy. AMR package contains --date taxonomic data. specific, currently included data retrieved 24 Jun 2024. codes AMR packages come .mo() short, still human readable. importantly, .mo() supports kinds input: first character codes denote taxonomic kingdom, Bacteria (B), Fungi (F), Protozoa (P). AMR package also contain functions directly retrieve taxonomic properties, name, genus, species, family, order, even Gram-stain. start mo_ use .mo() internally, still arbitrary user input can used: Now can thus clean data: Apparently, uncertainty translation taxonomic codes. Let’s check : ’s good.","code":"as.mo(\"Klebsiella pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"K. pneumoniae\") #> Class 'mo' #> [1] B_KLBSL_PNMN as.mo(\"KLEPNE\") #> Class 'mo' #> [1] Line truncated
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Block a user