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The latest and unpublished development version can be installed with (precaution: may be unstable):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