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<img src="../logo.svg" class="logo" alt=""><h1>How to conduct principal component analysis (PCA) for AMR</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/vignettes/PCA.Rmd" class="external-link"><code>vignettes/PCA.Rmd</code></a></small>
<div class="d-none name"><code>PCA.Rmd</code></div>
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<p><strong>NOTE: This page will be updated soon, as the pca() function
is currently being developed.</strong></p>
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<div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2>
</div>
<div class="section level2">
<h2 id="transforming">Transforming<a class="anchor" aria-label="anchor" href="#transforming"></a>
</h2>
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<p>For PCA, we need to transform our AMR data first. This is what the
<code>example_isolates</code> data set in this package looks like:</p>
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<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span></span>
<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
<span><span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span></span>
<span><span class="co"># Rows: 2,000</span></span>
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<span><span class="co"># Columns: 46</span></span>
<span><span class="co"># $ date <span style="color: #949494; font-style: italic;">&lt;date&gt;</span> 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002-01-13, 2…</span></span>
<span><span class="co"># $ patient <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "A77334", "A77334", "067927", "067927", "067927", "067927", "4…</span></span>
<span><span class="co"># $ age <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> 65, 65, 45, 45, 45, 45, 78, 78, 45, 79, 67, 67, 71, 71, 75, 50…</span></span>
<span><span class="co"># $ gender <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "F", "F", "F", "F", "F", "F", "M", "M", "F", "F", "M", "M", "M…</span></span>
<span><span class="co"># $ ward <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "Clinical", "Clinical", "ICU", "ICU", "ICU", "ICU", "Clinical"…</span></span>
<span><span class="co"># $ mo <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> "B_ESCHR_COLI", "B_ESCHR_COLI", "B_STPHY_EPDR", "B_STPHY_EPDR",…</span></span>
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<span><span class="co"># $ PEN <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, S,…</span></span>
<span><span class="co"># $ OXA <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ FLC <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, R, R, R, R, S, S, R, S, S, S, NA, NA, NA, NA, NA, R, R…</span></span>
<span><span class="co"># $ AMX <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, R, R, NA, NA, NA, NA, NA, NA, R, NA, N…</span></span>
<span><span class="co"># $ AMC <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> I, I, NA, NA, NA, NA, S, S, NA, NA, S, S, I, I, R, I, I, NA, N…</span></span>
<span><span class="co"># $ AMP <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, R, R, NA, NA, NA, NA, NA, NA, R, NA, N…</span></span>
<span><span class="co"># $ TZP <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ CZO <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, NA,…</span></span>
<span><span class="co"># $ FEP <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ CXM <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> I, I, R, R, R, R, S, S, R, S, S, S, S, S, NA, S, S, R, R, S, S…</span></span>
<span><span class="co"># $ FOX <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, NA,…</span></span>
<span><span class="co"># $ CTX <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S…</span></span>
<span><span class="co"># $ CAZ <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, S, S, R, R, …</span></span>
<span><span class="co"># $ CRO <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S…</span></span>
<span><span class="co"># $ GEN <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ TOB <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, S, S, NA, NA, NA…</span></span>
<span><span class="co"># $ AMK <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ KAN <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ TMP <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, S, S, R, R, R, R, S, S, NA, NA, S, S, S, S, S, R, R, R, …</span></span>
<span><span class="co"># $ SXT <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, S, S, NA, NA, NA, NA, S, S, NA, NA, S, S, S, S, S, NA, N…</span></span>
<span><span class="co"># $ NIT <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R,…</span></span>
<span><span class="co"># $ FOS <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ LNZ <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N…</span></span>
<span><span class="co"># $ CIP <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, NA, S, S…</span></span>
<span><span class="co"># $ MFX <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ VAN <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, S, S, S, S, S, S, S, S, NA, NA, R, R, R, R, R, S, S, S, …</span></span>
<span><span class="co"># $ TEC <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N…</span></span>
<span><span class="co"># $ TCY <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, S, S, S, S, S, S, S, I, S, S, NA, NA, I, R, R, S, I, R, …</span></span>
<span><span class="co"># $ TGC <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R, R, S, NA…</span></span>
<span><span class="co"># $ DOX <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R, R, S, NA…</span></span>
<span><span class="co"># $ ERY <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R, R, R, S,…</span></span>
<span><span class="co"># $ CLI <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, NA, NA, NA, R, NA, NA, NA, NA, NA, NA, R, R, R, R, R, NA…</span></span>
<span><span class="co"># $ AZM <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R, R, R, S,…</span></span>
<span><span class="co"># $ IPM <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, S, S…</span></span>
<span><span class="co"># $ MEM <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ MTR <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ CHL <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ COL <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, R, R, R, …</span></span>
<span><span class="co"># $ MUP <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…</span></span>
<span><span class="co"># $ RIF <span style="color: #949494; font-style: italic;">&lt;sir&gt;</span> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R, R, R, N…</span></span></code></pre></div>
2022-10-29 14:24:08 +02:00
<p>Now to transform this to a data set with only resistance percentages
per taxonomic order and genus:</p>
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<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
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<code class="sourceCode R"><span><span class="va">resistance_data</span> <span class="op">&lt;-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span></span>
<span> order <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_order</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span>, <span class="co"># group on anything, like order</span></span>
<span> genus <span class="op">=</span> <span class="fu"><a href="../reference/mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span></span>
<span> <span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="co"># and genus as we do here</span></span>
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<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise_all.html" class="external-link">summarise_if</a></span><span class="op">(</span><span class="va">is.sir</span>, <span class="va">resistance</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> <span class="co"># then get resistance of all drugs</span></span>
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<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span></span>
<span> <span class="va">order</span>, <span class="va">genus</span>, <span class="va">AMC</span>, <span class="va">CXM</span>, <span class="va">CTX</span>,</span>
<span> <span class="va">CAZ</span>, <span class="va">GEN</span>, <span class="va">TOB</span>, <span class="va">TMP</span>, <span class="va">SXT</span></span>
<span> <span class="op">)</span> <span class="co"># and select only relevant columns</span></span>
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<span></span>
<span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span></span>
<span><span class="co"># <span style="color: #949494;"># A tibble: 6 × 10</span></span></span>
<span><span class="co"># <span style="color: #949494;"># Groups: order [5]</span></span></span>
<span><span class="co"># order genus AMC CXM CTX CAZ GEN TOB TMP SXT</span></span>
<span><span class="co"># <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
<span><span class="co"># <span style="color: #BCBCBC;">1</span> (unknown order) (unknown ge… <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span></span>
<span><span class="co"># <span style="color: #BCBCBC;">2</span> Actinomycetales Schaalia <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span></span>
<span><span class="co"># <span style="color: #BCBCBC;">3</span> Bacteroidales Bacteroides <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span></span>
<span><span class="co"># <span style="color: #BCBCBC;">4</span> Campylobacterales Campylobact… <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span></span>
<span><span class="co"># <span style="color: #BCBCBC;">5</span> Caryophanales Gemella <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span></span>
<span><span class="co"># <span style="color: #BCBCBC;">6</span> Caryophanales Listeria <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span></span></span></code></pre></div>
</div>
<div class="section level2">
<h2 id="perform-principal-component-analysis">Perform principal component analysis<a class="anchor" aria-label="anchor" href="#perform-principal-component-analysis"></a>
</h2>
2022-10-29 14:24:08 +02:00
<p>The new <code><a href="../reference/pca.html">pca()</a></code> function will automatically filter on rows
that contain numeric values in all selected variables, so we now only
need to do:</p>
2022-08-21 16:59:35 +02:00
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">pca_result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span></span>
<span><span class="co"># Columns selected for PCA: "AMC", "CAZ", "CTX", "CXM", "GEN", "SXT", "TMP"</span></span>
<span><span class="co"># and "TOB". Total observations available: 7.</span></span></code></pre></div>
2022-10-29 14:24:08 +02:00
<p>The result can be reviewed with the good old <code><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary()</a></code>
function:</p>
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<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></span>
<span><span class="co"># Groups (n=4, named as 'order'):</span></span>
<span><span class="co"># [1] "Caryophanales" "Enterobacterales" "Lactobacillales" "Pseudomonadales"</span></span>
<span><span class="co"># Importance of components:</span></span>
<span><span class="co"># PC1 PC2 PC3 PC4 PC5 PC6 PC7</span></span>
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<span><span class="co"># Standard deviation 2.1539 1.6807 0.6138 0.33879 0.20808 0.03140 9.577e-17</span></span>
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<span><span class="co"># Proportion of Variance 0.5799 0.3531 0.0471 0.01435 0.00541 0.00012 0.000e+00</span></span>
<span><span class="co"># Cumulative Proportion 0.5799 0.9330 0.9801 0.99446 0.99988 1.00000 1.000e+00</span></span></code></pre></div>
<pre><code><span><span class="co"># Groups (n=4, named as 'order'):</span></span>
<span><span class="co"># [1] "Caryophanales" "Enterobacterales" "Lactobacillales" "Pseudomonadales"</span></span></code></pre>
2022-10-29 14:24:08 +02:00
<p>Good news. The first two components explain a total of 93.3% of the
variance (see the PC1 and PC2 values of the <em>Proportion of
Variance</em>. We can create a so-called biplot with the base R
<code><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot()</a></code> function, to see which antimicrobial resistance
per drug explain the difference per microorganism.</p>
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</div>
<div class="section level2">
<h2 id="plotting-the-results">Plotting the results<a class="anchor" aria-label="anchor" href="#plotting-the-results"></a>
</h2>
<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></span></code></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-5-1.png" width="750"></p>
2022-10-29 14:24:08 +02:00
<p>But we cant see the explanation of the points. Perhaps this works
better with our new <code><a href="../reference/ggplot_pca.html">ggplot_pca()</a></code> function, that
automatically adds the right labels and even groups:</p>
2022-08-21 16:59:35 +02:00
<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span><span class="op">)</span></span></code></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-6-1.png" width="750"></p>
<p>You can also print an ellipse per group, and edit the appearance:</p>
<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="../reference/ggplot_pca.html">ggplot_pca</a></span><span class="op">(</span><span class="va">pca_result</span>, ellipse <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span> <span class="op">+</span></span>
<span> <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>title <span class="op">=</span> <span class="st">"An AMR/PCA biplot!"</span><span class="op">)</span></span></code></pre></div>
<p><img src="PCA_files/figure-html/unnamed-chunk-7-1.png" width="750"></p>
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