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<h1>PCA Biplot with <code>ggplot2</code></h1>
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<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/ggplot_pca.R" class="external-link"><code>R/ggplot_pca.R</code></a></small>
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<div class="hidden name"><code>ggplot_pca.Rd</code></div>
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</div>
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<div class="ref-description">
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<p>Produces a <code>ggplot2</code> variant of a so-called <a href="https://en.wikipedia.org/wiki/Biplot" class="external-link">biplot</a> for PCA (principal component analysis), but is more flexible and more appealing than the base <span style="R">R</span> <code><a href="https://rdrr.io/r/stats/biplot.html" class="external-link">biplot()</a></code> function.</p>
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</div>
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<div id="ref-usage">
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<div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">ggplot_pca</span><span class="op">(</span>
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<span class="va">x</span>,
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choices <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">2</span>,
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scale <span class="op">=</span> <span class="fl">1</span>,
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pc.biplot <span class="op">=</span> <span class="cn">TRUE</span>,
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labels <span class="op">=</span> <span class="cn">NULL</span>,
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labels_textsize <span class="op">=</span> <span class="fl">3</span>,
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labels_text_placement <span class="op">=</span> <span class="fl">1.5</span>,
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groups <span class="op">=</span> <span class="cn">NULL</span>,
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ellipse <span class="op">=</span> <span class="cn">TRUE</span>,
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ellipse_prob <span class="op">=</span> <span class="fl">0.68</span>,
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ellipse_size <span class="op">=</span> <span class="fl">0.5</span>,
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ellipse_alpha <span class="op">=</span> <span class="fl">0.5</span>,
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points_size <span class="op">=</span> <span class="fl">2</span>,
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points_alpha <span class="op">=</span> <span class="fl">0.25</span>,
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arrows <span class="op">=</span> <span class="cn">TRUE</span>,
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arrows_colour <span class="op">=</span> <span class="st">"darkblue"</span>,
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arrows_size <span class="op">=</span> <span class="fl">0.5</span>,
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arrows_textsize <span class="op">=</span> <span class="fl">3</span>,
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arrows_textangled <span class="op">=</span> <span class="cn">TRUE</span>,
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arrows_alpha <span class="op">=</span> <span class="fl">0.75</span>,
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base_textsize <span class="op">=</span> <span class="fl">10</span>,
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<span class="va">...</span>
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<span class="op">)</span></code></pre></div>
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</div>
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<div id="source">
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<h2>Source</h2>
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<p>The <code>ggplot_pca()</code> function is based on the <code>ggbiplot()</code> function from the <code>ggbiplot</code> package by Vince Vu, as found on GitHub: <a href="https://github.com/vqv/ggbiplot" class="external-link">https://github.com/vqv/ggbiplot</a> (retrieved: 2 March 2020, their latest commit: <a href="https://github.com/vqv/ggbiplot/commit/7325e880485bea4c07465a0304c470608fffb5d9" class="external-link"><code>7325e88</code></a>; 12 February 2015).</p>
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<p>As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were:</p><ol><li><p>Rewritten code to remove the dependency on packages <code>plyr</code>, <code>scales</code> and <code>grid</code></p></li>
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<li><p>Parametrised more options, like arrow and ellipse settings</p></li>
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<li><p>Hardened all input possibilities by defining the exact type of user input for every argument</p></li>
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<li><p>Added total amount of explained variance as a caption in the plot</p></li>
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<li><p>Cleaned all syntax based on the <code>lintr</code> package, fixed grammatical errors and added integrity checks</p></li>
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<li><p>Updated documentation</p></li>
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</ol></div>
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<div id="arguments">
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<h2>Arguments</h2>
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<dl><dt>x</dt>
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<dd><p>an object returned by <code><a href="pca.html">pca()</a></code>, <code><a href="https://rdrr.io/r/stats/prcomp.html" class="external-link">prcomp()</a></code> or <code><a href="https://rdrr.io/r/stats/princomp.html" class="external-link">princomp()</a></code></p></dd>
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<dt>choices</dt>
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<dd><p>length 2 vector specifying the components to plot. Only the default
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is a biplot in the strict sense.</p></dd>
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<dt>scale</dt>
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<dd><p>The variables are scaled by <code>lambda ^ scale</code> and the
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observations are scaled by <code>lambda ^ (1-scale)</code> where
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<code>lambda</code> are the singular values as computed by
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<code><a href="https://rdrr.io/r/stats/princomp.html" class="external-link">princomp</a></code>. Normally <code>0 <= scale <= 1</code>, and a warning
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will be issued if the specified <code>scale</code> is outside this range.</p></dd>
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<dt>pc.biplot</dt>
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<dd><p>If true, use what Gabriel (1971) refers to as a "principal component
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biplot", with <code>lambda = 1</code> and observations scaled up by sqrt(n) and
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variables scaled down by sqrt(n). Then inner products between
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variables approximate covariances and distances between observations
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approximate Mahalanobis distance.</p></dd>
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<dt>labels</dt>
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<dd><p>an optional vector of labels for the observations. If set, the labels will be placed below their respective points. When using the <code><a href="pca.html">pca()</a></code> function as input for <code>x</code>, this will be determined automatically based on the attribute <code>non_numeric_cols</code>, see <code><a href="pca.html">pca()</a></code>.</p></dd>
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<dt>labels_textsize</dt>
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<dd><p>the size of the text used for the labels</p></dd>
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<dt>labels_text_placement</dt>
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<dd><p>adjustment factor the placement of the variable names (<code>>=1</code> means further away from the arrow head)</p></dd>
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<dt>groups</dt>
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<dd><p>an optional vector of groups for the labels, with the same length as <code>labels</code>. If set, the points and labels will be coloured according to these groups. When using the <code><a href="pca.html">pca()</a></code> function as input for <code>x</code>, this will be determined automatically based on the attribute <code>non_numeric_cols</code>, see <code><a href="pca.html">pca()</a></code>.</p></dd>
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<dt>ellipse</dt>
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<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether a normal data ellipse should be drawn for each group (set with <code>groups</code>)</p></dd>
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<dt>ellipse_prob</dt>
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<dd><p>statistical size of the ellipse in normal probability</p></dd>
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<dt>ellipse_size</dt>
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<dd><p>the size of the ellipse line</p></dd>
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<dt>ellipse_alpha</dt>
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<dd><p>the alpha (transparency) of the ellipse line</p></dd>
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<dt>points_size</dt>
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<dd><p>the size of the points</p></dd>
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<dt>points_alpha</dt>
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<dd><p>the alpha (transparency) of the points</p></dd>
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<dt>arrows</dt>
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<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> to indicate whether arrows should be drawn</p></dd>
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<dt>arrows_colour</dt>
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<dd><p>the colour of the arrow and their text</p></dd>
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<dt>arrows_size</dt>
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<dd><p>the size (thickness) of the arrow lines</p></dd>
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<dt>arrows_textsize</dt>
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<dd><p>the size of the text at the end of the arrows</p></dd>
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<dt>arrows_textangled</dt>
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<dd><p>a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> whether the text at the end of the arrows should be angled</p></dd>
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<dt>arrows_alpha</dt>
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<dd><p>the alpha (transparency) of the arrows and their text</p></dd>
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<dt>base_textsize</dt>
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<dd><p>the text size for all plot elements except the labels and arrows</p></dd>
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<dt>...</dt>
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<dd><p>arguments passed on to functions</p></dd>
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</dl></div>
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<div id="details">
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<h2>Details</h2>
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<p>The colours for labels and points can be changed by adding another scale layer for colour, such as <code><a href="https://ggplot2.tidyverse.org/reference/scale_viridis.html" class="external-link">scale_colour_viridis_d()</a></code> and <code><a href="https://ggplot2.tidyverse.org/reference/scale_brewer.html" class="external-link">scale_colour_brewer()</a></code>.</p>
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</div>
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<div id="stable-lifecycle">
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<h2>Stable Lifecycle</h2>
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<p><img src="figures/lifecycle_stable.svg" style='margin-bottom:"5"'><br>
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The <a href="lifecycle.html">lifecycle</a> of this function is <strong>stable</strong>. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.</p>
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<p>If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.</p>
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</div>
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<div id="ref-examples">
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<h2>Examples</h2>
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<div class="sourceCode"><pre class="sourceCode r"><code><span class="co"># `example_isolates` is a data set available in the AMR package.</span>
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<span class="co"># See ?example_isolates.</span>
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<span class="co"># See ?pca for more info about Principal Component Analysis (PCA).</span>
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<span class="co"># \donttest{</span>
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<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
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<span class="va">pca_model</span> <span class="op"><-</span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
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<span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu"><a href="mo_property.html">mo_genus</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span> <span class="op">==</span> <span class="st">"Staphylococcus"</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
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<span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span>species <span class="op">=</span> <span class="fu"><a href="mo_property.html">mo_shortname</a></span><span class="op">(</span><span class="va">mo</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span>
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<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.rsi</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">%>%</a></span>
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<span class="fu"><a href="pca.html">pca</a></span><span class="op">(</span><span class="va">FLC</span>, <span class="va">AMC</span>, <span class="va">CXM</span>, <span class="va">GEN</span>, <span class="va">TOB</span>, <span class="va">TMP</span>, <span class="va">SXT</span>, <span class="va">CIP</span>, <span class="va">TEC</span>, <span class="va">TCY</span>, <span class="va">ERY</span><span class="op">)</span>
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<span class="co"># old (base R)</span>
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<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_model</span><span class="op">)</span>
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<span class="co"># new </span>
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<span class="fu">ggplot_pca</span><span class="op">(</span><span class="va">pca_model</span><span class="op">)</span>
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<span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://ggplot2.tidyverse.org" class="external-link">"ggplot2"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span>
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<span class="fu">ggplot_pca</span><span class="op">(</span><span class="va">pca_model</span><span class="op">)</span> <span class="op">+</span>
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<span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_viridis.html" class="external-link">scale_colour_viridis_d</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span>
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<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">"Title here"</span><span class="op">)</span>
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<span class="op">}</span>
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<span class="op">}</span>
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<span class="co"># }</span>
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</code></pre></div>
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</div>
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<nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2>
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<p></p><p>Developed by Matthijs S. Berends, Christian F. Luz, Dennis Souverein,
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<p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
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