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    <h1>Performs ordination/dimensionality reduction for a species incidence matrix, depending on the species selected in the feature.columns parameter.</h1>
    <small class="dont-index">Source: <a href="https://github.com/alexyermanos/Platypus/tree/masterR/VDJ_ordination.R" class="external-link"><code>R/VDJ_ordination.R</code></a></small>
    <div class="hidden name"><code>VDJ_ordination.Rd</code></div>
    </div>

    <div class="ref-description">
    <p>Performs ordination/dimensionality reduction for a species incidence matrix, depending on the species selected in the feature.columns parameter.</p>
    </div>

    <div id="ref-usage">
    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">VDJ_ordination</span><span class="op">(</span></span>
<span>  <span class="va">VDJ</span>,</span>
<span>  <span class="va">feature.columns</span>,</span>
<span>  <span class="va">grouping.column</span>,</span>
<span>  <span class="va">method</span>,</span>
<span>  <span class="va">reduction.level</span>,</span>
<span>  <span class="va">VDJ.VJ.1chain</span>,</span>
<span>  <span class="va">umap.n.neighbours</span>,</span>
<span>  <span class="va">tsne.perplexity</span></span>
<span><span class="op">)</span></span></code></pre></div>
    </div>

    <div id="arguments">
    <h2>Arguments</h2>
    <dl><dt>VDJ</dt>
<dd><p>VDJ dataframe output from the VDJ_GEX_matrix function.</p></dd>


<dt>feature.columns</dt>
<dd><p>Character vector. One or more column names from the VDJ to indicate the unique species for the incidence/count matrix. if more than one column is provided (e.g. c("VDJ_cdr3s_aa","VJ_cdr3s_aa")) these columns will be pasted together before metric calculation.</p></dd>


<dt>grouping.column</dt>
<dd><p>Character. Column name of a column to group the ordination by. This could be "sample_id" to reduce across each sample. Indicative of 'sites' in a typical community data matrix/incidence matrix used in community ecology analyses (species by sites).</p></dd>


<dt>method</dt>
<dd><p>Character. The ordination method; choose from either: PCA - 'pca', t-SNE - 'tsne', UMAP - 'umap', PCOA/MDS - 'mds', DCA - 'dca'.</p></dd>


<dt>reduction.level</dt>
<dd><p>Character. Whether to reduce across groups ('groups'), features/sequences ('features'), or both ('both').</p></dd>


<dt>VDJ.VJ.1chain</dt>
<dd><p>Boolean defaults to TRUE. Whether to filter out aberrant cells (more than 1 VDJ or VJ chain).</p></dd>


<dt>umap.n.neighbours</dt>
<dd><p>Integer. Control the t-SNE perplexity when method = 'tsne'.</p></dd>


<dt>tsne.perplexity</dt>
<dd><p>Integrer. Defaults to 1</p></dd>

</dl></div>
    <div id="value">
    <h2>Value</h2>
    

<p>Returns a ggplot with the ordination analysis performer across features, groups, or both</p>
    </div>

    <div id="ref-examples">
    <h2>Examples</h2>
    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co">#PCA dimensionality reduction across samples for CDRH3</span></span></span>
<span class="r-in"><span><span class="va">plot</span> <span class="op">&lt;-</span> <span class="fu">VDJ_ordination</span><span class="op">(</span>VDJ <span class="op">=</span> <span class="fu">Platypus</span><span class="fu">::</span><span class="va"><a href="small_vgm.html">small_vgm</a></span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span>,</span></span>
<span class="r-in"><span>,feature.columns <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"VDJ_cdr3s_aa"</span><span class="op">)</span>, grouping.column <span class="op">=</span> <span class="st">"sample_id"</span></span></span>
<span class="r-in"><span>,method <span class="op">=</span> <span class="st">"pca"</span>, reduction.level <span class="op">=</span> <span class="st">'groups'</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
</code></pre></div>
    </div>
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