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<h1>The <code>AMR</code> Package</h1>
<div class="hidden name"><code>AMR.Rd</code></div>
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<div class="ref-description">
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<p>Welcome to the <code>AMR</code> package.</p>
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<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
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<p><code>AMR</code> is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data.</p>
<p>We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology &amp; Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation.</p>
<p>This package can be used for:</p><ul>
<li><p>Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the Catalogue of Life</p></li>
<li><p>Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines</p></li>
<li><p>Determining first isolates to be used for AMR analysis</p></li>
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<li><p>Calculating antimicrobial resistance</p></li>
<li><p>Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)</p></li>
<li><p>Calculating (empirical) susceptibility of both mono therapy and combination therapies</p></li>
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<li><p>Predicting future antimicrobial resistance using regression models</p></li>
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<li><p>Getting properties for any microorganism (like Gram stain, species, genus or family)</p></li>
<li><p>Getting properties for any antibiotic (like name, EARS-Net code, ATC code, PubChem code, defined daily dose or trade name)</p></li>
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<li><p>Plotting antimicrobial resistance</p></li>
<li><p>Applying EUCAST expert rules</p></li>
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</ul>
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<h2 class="hasAnchor" id="read-more-on-our-website-"><a class="anchor" href="#read-more-on-our-website-"></a>Read more on our website!</h2>
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<p>On our website <a href='https://msberends.gitlab.io/AMR'>https://msberends.gitlab.io/AMR</a> you can find <a href='https://msberends.gitlab.io/AMR/articles/AMR.html'>a tutorial</a> about how to conduct AMR analysis, the <a href='https://msberends.gitlab.io/AMR/reference'>complete documentation of all functions</a> (which reads a lot easier than here in R) and <a href='https://msberends.gitlab.io/AMR/articles/WHONET.html'>an example analysis using WHONET data</a>.</p>
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<h2 class="hasAnchor" id="contact-us"><a class="anchor" href="#contact-us"></a>Contact us</h2>
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<p>For suggestions, comments or questions, please contact us at:</p>
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<p>Matthijs S. Berends <br />
m.s.berends [at] umcg [dot] nl <br />
Department of Medical Microbiology, University of Groningen <br />
University Medical Center Groningen <br />
Post Office Box 30001 <br />
2019-11-10 15:50:18 +01:00
9700 RB Groningen
The Netherlands</p>
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<p>If you have found a bug, please file a new issue at: <br />
<a href='https://gitlab.com/msberends/AMR/issues'>https://gitlab.com/msberends/AMR/issues</a></p>
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<li><a href="#details">Details</a></li>
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<li><a href="#read-more-on-our-website-">Read more on our website!</a></li>
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<li><a href="#contact-us">Contact us</a></li>
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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>, <a href='https://www.rug.nl/staff/c.j.albers/'>Casper J. Albers</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>.</p>
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