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<a class="navbar-brand me-2" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
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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 12 June 2024.</p>
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generated on 13 June 2024.</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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@@ -261,21 +261,21 @@ 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">2024-06-12</td>
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<td align="center">2024-06-13</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">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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<td align="center">2024-06-12</td>
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<td align="center">2024-06-13</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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<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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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>Data sets for download / own use</h1>
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<h4 data-toc-skip class="date">12 June 2024</h4>
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<h4 data-toc-skip class="date">13 June 2024</h4>
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<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/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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@@ -2176,12 +2176,12 @@ which are used in the <code>clinical_breakpoints</code> data set.</p>
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<h2 id="microorganisms-codes-common-laboratory-codes">
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<code>microorganisms.codes</code>: Common Laboratory Codes<a class="anchor" aria-label="anchor" href="#microorganisms-codes-common-laboratory-codes"></a>
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</h2>
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<p>A data set with 4 957 rows and 2 columns, containing the following
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<p>A data set with 4 958 rows and 2 columns, containing the following
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column names:<br><em>code</em> and <em>mo</em>.</p>
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<p>This data set is in R available as <code>microorganisms.codes</code>,
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after you load the <code>AMR</code> package.</p>
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<p>It was last updated on 8 July 2023 15:30:05 UTC. Find more info about
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the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.codes.html">here</a>.</p>
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<p>It was last updated on 13 June 2024 05:37:53 UTC. Find more info
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about the structure of this data set <a href="https://msberends.github.io/AMR/reference/microorganisms.codes.html">here</a>.</p>
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<p><strong>Direct download links:</strong></p>
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<ul>
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<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.codes.rds" class="external-link">original
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@@ -2194,10 +2194,10 @@ text file</a> (0.1 MB)<br>
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Excel workbook</a> (91 kB)<br>
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</li>
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<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.codes.feather" class="external-link">Apache
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Feather file</a> (85 kB)<br>
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Feather file</a> (0.1 MB)<br>
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</li>
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<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.codes.parquet" class="external-link">Apache
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Parquet file</a> (57 kB)<br>
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Parquet file</a> (0 kB)<br>
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</li>
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<li>Download as <a href="https://github.com/msberends/AMR/raw/main/data-raw/../data-raw/microorganisms.codes.xpt" class="external-link">SAS
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transport (XPT) file</a> (0 kB)<br>
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<li>Provides the <strong>full microbiological taxonomy</strong> and extensive info on <strong>all antimicrobial drugs</strong>
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</li>
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<li>Applies all recent <strong>CLSI</strong> and <strong>EUCAST</strong> clinical and veterinary breakpoints for MICs and disk zones</li>
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<li>Corrects for duplicate isolates using 4 methods, <strong>calculates</strong> and <strong>predicts</strong> AMR per antibiotic class</li>
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<li>Corrects for duplicate isolates, <strong>calculates</strong> and <strong>predicts</strong> AMR per antibiotic class</li>
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<li>Integrates with <strong>WHONET</strong>, ATC, <strong>EARS-Net</strong>, PubChem, <strong>LOINC</strong>, <strong>SNOMED CT</strong>, and <strong>NCBI</strong>
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</li>
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<li>100% free of costs and dependencies, highly suitable for places with <strong>limited resources</strong>
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</li>
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<li>
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<strong>Easy to use</strong> and <strong>easy to learn</strong>, with a <strong>community</strong> of contributors from around the globe</li>
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</ul>
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<div style="display: flex; font-size: 0.8em;">
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<p style="text-align:left; width: 50%;">
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<div class="section level4">
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<h4 id="latest-development-version">Latest development version<a class="anchor" aria-label="anchor" href="#latest-development-version"></a>
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</h4>
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<p><a href="https://codecov.io/gh/msberends/AMR?branch=main" class="external-link"><img src="https://github.com/msberends/AMR/workflows/check-old/badge.svg?branch=main" alt="check-recent"></a> <a href="https://codecov.io/gh/msberends/AMR?branch=main" class="external-link"><img src="https://github.com/msberends/AMR/workflows/check-recent/badge.svg?branch=main" alt="check-recent"></a> <a href="https://www.codefactor.io/repository/github/msberends/amr" class="external-link"><img src="https://www.codefactor.io/repository/github/msberends/amr/badge" alt="CodeFactor"></a> <a href="https://codecov.io/gh/msberends/AMR?branch=main" class="external-link"><img src="https://codecov.io/gh/msberends/AMR/branch/main/graph/badge.svg" alt="Codecov"></a></p>
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<p><a href="https://github.com/msberends/AMR/actions/workflows/check-old.yaml?query=branch%3Amain" class="external-link"><img src="https://github.com/msberends/AMR/actions/workflows/check-old.yaml/badge.svg?branch=main" alt="check-old"></a> <a href="https://github.com/msberends/AMR/actions/workflows/check-recent.yaml?query=branch%3Amain" class="external-link"><img src="https://github.com/msberends/AMR/actions/workflows/check-recent.yaml/badge.svg?branch=main" alt="check-recent"></a> <a href="https://www.codefactor.io/repository/github/msberends/amr" class="external-link"><img src="https://www.codefactor.io/repository/github/msberends/amr/badge" alt="CodeFactor"></a> <a href="https://codecov.io/gh/msberends/AMR?branch=main" class="external-link"><img src="https://codecov.io/gh/msberends/AMR/branch/main/graph/badge.svg" alt="Codecov"></a></p>
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<p>Please read our <a href="https://github.com/msberends/AMR/wiki/Developer-Guideline" class="external-link">Developer Guideline here</a>.</p>
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<p>The latest and unpublished development version can be installed from GitHub in two ways:</p>
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</div>
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<div class="section level2">
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<h2 class="pkg-version" data-toc-text="2.1.1.9046" id="amr-2119046">AMR 2.1.1.9046<a class="anchor" aria-label="anchor" href="#amr-2119046"></a></h2>
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<h2 class="pkg-version" data-toc-text="2.1.1.9047" id="amr-2119047">AMR 2.1.1.9047<a class="anchor" aria-label="anchor" href="#amr-2119047"></a></h2>
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<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!)</em></p>
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<div class="section level5">
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<h5 id="a-new-milestone-one-health-support--human--veterinary--environmental-2-1-1-9046">A New Milestone: One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-one-health-support--human--veterinary--environmental-2-1-1-9046"></a></h5>
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<h5 id="a-new-milestone-one-health-support--human--veterinary--environmental-2-1-1-9047">A New Milestone: One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-one-health-support--human--veterinary--environmental-2-1-1-9047"></a></h5>
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<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</a>, Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.</p>
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</div>
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<div class="section level3">
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<h3 id="breaking-2-1-1-9046">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9046"></a></h3>
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<h3 id="breaking-2-1-1-9047">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9047"></a></h3>
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<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 over a year ago</li>
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</ul></div>
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<div class="section level3">
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<h3 id="new-2-1-1-9046">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9046"></a></h3>
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<h3 id="new-2-1-1-9047">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9047"></a></h3>
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<ul><li>One Health implementation
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<ul><li>Function <code><a href="../reference/as.sir.html">as.sir()</a></code> now has extensive support for animal 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>
|
||||
<li>The <code>clinical_breakpoints</code> data set contains all these breakpoints, and can be downloaded on our <a href="https://msberends.github.io/AMR/articles/datasets.html">download page</a>.</li>
|
||||
@@ -187,7 +187,7 @@
|
||||
<li>Function <code><a href="../reference/mo_property.html">mo_group_members()</a></code> to retrieve the member microorganisms of a microorganism group. For example, <code>mo_group_members("Strep group C")</code> returns a vector of all microorganisms that are in that group.</li>
|
||||
</ul></div>
|
||||
<div class="section level3">
|
||||
<h3 id="changed-2-1-1-9046">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9046"></a></h3>
|
||||
<h3 id="changed-2-1-1-9047">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9047"></a></h3>
|
||||
<ul><li>For SIR interpretation, 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>Extended the antibiotic selectors with <code><a href="../reference/antibiotic_class_selectors.html">nitrofurans()</a></code> and <code><a href="../reference/antibiotic_class_selectors.html">rifamycins()</a></code>
|
||||
</li>
|
||||
@@ -215,7 +215,7 @@
|
||||
<li>Intermediate log2 levels used for MIC plotting are now more common values instead of following a strict dilution range</li>
|
||||
</ul></div>
|
||||
<div class="section level3">
|
||||
<h3 id="other-2-1-1-9046">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9046"></a></h3>
|
||||
<h3 id="other-2-1-1-9047">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9047"></a></h3>
|
||||
<ul><li>Added Jordan Stull, Matthew Saab, and Javier Sanchez as contributors, to thank them for their valuable input</li>
|
||||
</ul></div>
|
||||
</div>
|
||||
|
||||
+1
-1
@@ -11,7 +11,7 @@ articles:
|
||||
resistance_predict: resistance_predict.html
|
||||
welcome_to_AMR: welcome_to_AMR.html
|
||||
WHONET: WHONET.html
|
||||
last_built: 2024-06-12T12:40Z
|
||||
last_built: 2024-06-13T05:41Z
|
||||
urls:
|
||||
reference: https://msberends.github.io/AMR/reference
|
||||
article: https://msberends.github.io/AMR/articles
|
||||
|
||||
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|
||||
|
||||
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|
||||
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||||
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9046</small>
|
||||
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9047</small>
|
||||
|
||||
|
||||
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|
||||
|
||||
+1
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@@ -24,7 +24,7 @@ The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish,
|
||||
|
||||
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|
||||
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|
||||
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|
||||
|
||||
|
||||
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
|
||||
|
||||
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|
||||
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||||
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||||
|
||||
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|
||||
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|
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|
||||
|
||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9047</small>
|
||||
|
||||
|
||||
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
|
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|
||||
@@ -10,7 +10,7 @@
|
||||
|
||||
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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||||
|
||||
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9046</small>
|
||||
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9047</small>
|
||||
|
||||
|
||||
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|
||||
|
||||
@@ -10,7 +10,7 @@
|
||||
|
||||
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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||||
|
||||
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9046</small>
|
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|
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||||
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@@ -10,7 +10,7 @@
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||||
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||||
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@@ -10,7 +10,7 @@
|
||||
|
||||
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|
||||
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||||
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|
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|
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+11
-11
@@ -10,7 +10,7 @@
|
||||
|
||||
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
|
||||
|
||||
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||||
@@ -222,16 +222,16 @@
|
||||
<span class="r-in"><span></span></span>
|
||||
<span class="r-in"><span><span class="va">df</span></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> birth_date age age_exact age_at_y2k</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 1965-12-05 58 58.51913 34</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 1980-03-01 44 44.28142 19</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 1949-11-01 74 74.61202 50</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 1947-02-14 77 77.32514 52</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 1940-02-19 84 84.31148 59</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 1988-01-10 36 36.42077 11</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 1997-08-27 26 26.79235 2</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 1978-01-26 46 46.37705 21</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 1972-06-17 51 51.98634 27</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 1986-08-10 37 37.83880 13</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 1 1965-12-05 58 58.52186 34</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 2 1980-03-01 44 44.28415 19</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 3 1949-11-01 74 74.61475 50</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 4 1947-02-14 77 77.32787 52</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 5 1940-02-19 84 84.31421 59</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 6 1988-01-10 36 36.42350 11</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 7 1997-08-27 26 26.79508 2</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 8 1978-01-26 46 46.37978 21</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 9 1972-06-17 51 51.98907 27</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> 10 1986-08-10 37 37.84153 13</span>
|
||||
</code></pre></div>
|
||||
</div>
|
||||
</main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
|
||||
|
||||
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||||
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||||
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@@ -12,7 +12,7 @@ In short, if you have a column name that resembles an antimicrobial drug, it wil
|
||||
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+14
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@@ -24,7 +24,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
|
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@@ -603,19 +603,19 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 13 × 14</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> datetime index ab_user mo_user ab mo input</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;"><ab></span> <span style="color: #949494; font-style: italic;"><mo></span> <span style="color: #949494; font-style: italic;"><dbl></span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> 2024-06-12 <span style="color: #949494;">12:41:28</span> 1 TOB Escherich… TOB B_[ORD]_ENTRBCTR 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> 2024-06-12 <span style="color: #949494;">12:41:28</span> 1 GEN Escherich… GEN B_[ORD]_ENTRBCTR 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> 2024-06-12 <span style="color: #949494;">12:41:28</span> 1 CIP Escherich… CIP B_[ORD]_ENTRBCTR 0.256</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> 2024-06-12 <span style="color: #949494;">12:41:27</span> 1 AMP Escherich… AMP B_[ORD]_ENTRBCTR 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> 2024-06-12 <span style="color: #949494;">12:41:23</span> 1 AMX B_STRPT_P… AMX B_STRPT_PNMN 0.01 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 2024-06-12 <span style="color: #949494;">12:41:23</span> 2 AMX B_STRPT_P… AMX B_STRPT_PNMN 2 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> 2024-06-12 <span style="color: #949494;">12:41:23</span> 3 AMX B_STRPT_P… AMX B_STRPT_PNMN 4 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> 2024-06-12 <span style="color: #949494;">12:41:23</span> 4 AMX B_STRPT_P… AMX B_STRPT_PNMN 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 2024-06-12 <span style="color: #949494;">12:41:23</span> 1 AMX B_STRPT_P… AMX B_STRPT_PNMN 2 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> 2024-06-12 <span style="color: #949494;">12:41:23</span> 1 TOB Escherich… TOB B_[ORD]_ENTRBCTR 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">11</span> 2024-06-12 <span style="color: #949494;">12:41:23</span> 1 GEN Escherich… GEN B_[ORD]_ENTRBCTR 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">12</span> 2024-06-12 <span style="color: #949494;">12:41:22</span> 1 AMP Escherich… AMP B_[ORD]_ENTRBCTR 20 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">13</span> 2024-06-12 <span style="color: #949494;">12:41:22</span> 1 ampicillin Strep pneu AMP B_STRPT_PNMN 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> 2024-06-13 <span style="color: #949494;">05:41:56</span> 1 TOB Escherich… TOB B_[ORD]_ENTRBCTR 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> 2024-06-13 <span style="color: #949494;">05:41:56</span> 1 GEN Escherich… GEN B_[ORD]_ENTRBCTR 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> 2024-06-13 <span style="color: #949494;">05:41:55</span> 1 CIP Escherich… CIP B_[ORD]_ENTRBCTR 0.256</span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> 2024-06-13 <span style="color: #949494;">05:41:55</span> 1 AMP Escherich… AMP B_[ORD]_ENTRBCTR 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> 2024-06-13 <span style="color: #949494;">05:41:51</span> 1 AMX B_STRPT_P… AMX B_STRPT_PNMN 0.01 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 2024-06-13 <span style="color: #949494;">05:41:51</span> 2 AMX B_STRPT_P… AMX B_STRPT_PNMN 2 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> 2024-06-13 <span style="color: #949494;">05:41:51</span> 3 AMX B_STRPT_P… AMX B_STRPT_PNMN 4 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> 2024-06-13 <span style="color: #949494;">05:41:51</span> 4 AMX B_STRPT_P… AMX B_STRPT_PNMN 8 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 2024-06-13 <span style="color: #949494;">05:41:51</span> 1 AMX B_STRPT_P… AMX B_STRPT_PNMN 2 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> 2024-06-13 <span style="color: #949494;">05:41:51</span> 1 TOB Escherich… TOB B_[ORD]_ENTRBCTR 16 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">11</span> 2024-06-13 <span style="color: #949494;">05:41:51</span> 1 GEN Escherich… GEN B_[ORD]_ENTRBCTR 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">12</span> 2024-06-13 <span style="color: #949494;">05:41:50</span> 1 AMP Escherich… AMP B_[ORD]_ENTRBCTR 20 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">13</span> 2024-06-13 <span style="color: #949494;">05:41:50</span> 1 ampicillin Strep pneu AMP B_STRPT_PNMN 18 </span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 7 more variables: outcome <sir>, method <chr>, breakpoint_S_R <chr>,</span></span>
|
||||
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># guideline <chr>, host <chr>, ref_table <chr>, uti <lgl></span></span>
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||||
<code><a href="microorganisms.codes.html">microorganisms.codes</a></code>
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</dt>
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||||
<dd>Data Set with 4 957 Common Microorganism Codes</dd>
|
||||
<dd>Data Set with 4 958 Common Microorganism Codes</dd>
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</nav><div class="container template-reference-topic">
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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>Data Set with 4 957 Common Microorganism Codes</h1>
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||||
<img src="../logo.svg" class="logo" alt=""><h1>Data Set with 4 958 Common Microorganism Codes</h1>
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<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/data.R" class="external-link"><code>R/data.R</code></a></small>
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<div class="d-none name"><code>microorganisms.codes.Rd</code></div>
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<div class="section level2">
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<h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2>
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<p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 4 957 observations and 2 variables:</p><ul><li><p><code>code</code><br> Commonly used code of a microorganism. <em>This is a unique identifier.</em></p></li>
|
||||
<p>A <a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a> with 4 958 observations and 2 variables:</p><ul><li><p><code>code</code><br> Commonly used code of a microorganism. <em>This is a unique identifier.</em></p></li>
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<li><p><code>mo</code><br> ID of the microorganism in the <a href="microorganisms.html">microorganisms</a> data set</p></li>
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<div class="section level2">
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<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
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<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="va">microorganisms.codes</span></span></span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 4,957 × 2</span></span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 4,958 × 2</span></span>
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<span class="r-out co"><span class="r-pr">#></span> code mo </span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><mo></span> </span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> 1011 B_GRAMP </span>
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@@ -198,7 +198,7 @@
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> 1100 B_STRPT </span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 1101 B_STRPT_VIRI </span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> 1102 B_STRPT_HAEM </span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 4,947 more rows</span></span>
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<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># ℹ 4,948 more rows</span></span>
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<span class="r-in"><span></span></span>
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<span class="r-in"><span><span class="co"># 'ECO' or 'eco' is the WHONET code for E. coli:</span></span></span>
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<span class="r-in"><span><span class="va">microorganisms.codes</span><span class="op">[</span><span class="va">microorganisms.codes</span><span class="op">$</span><span class="va">code</span> <span class="op">==</span> <span class="st">"ECO"</span>, <span class="op">]</span></span></span>
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@@ -12,7 +12,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p
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@@ -12,7 +12,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
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[{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"How to 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://msberends.github.io/AMR/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"How to 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://msberends.github.io/AMR/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"How to 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://msberends.github.io/AMR/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"How to 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 11 Dec 2022. 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\") #> ClaLine truncated
|
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[{"path":"https://msberends.github.io/AMR/articles/AMR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"How to 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://msberends.github.io/AMR/articles/AMR.html","id":"preparation","dir":"Articles","previous_headings":"","what":"Preparation","title":"How to 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://msberends.github.io/AMR/articles/AMR.html","id":"needed-r-packages","dir":"Articles","previous_headings":"Preparation","what":"Needed R packages","title":"How to 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://msberends.github.io/AMR/articles/AMR.html","id":"taxonomy-of-microorganisms","dir":"Articles","previous_headings":"Preparation","what":"Taxonomy of microorganisms","title":"How to 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 11 Dec 2022. 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\") #> ClaLine truncated
|
||||
Reference in new issue
Block a user