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Fix compositional heatmap
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RiboRings committed Jul 9, 2024
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36 changes: 11 additions & 25 deletions docs/compositional_heatmap.html
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<link href="site_libs/quarto-html/light-border.css" rel="stylesheet">
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<title>Compositional Heatmaps</title>
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<h2>Why relative abundances?</h2>
<p>Microbiome data is compositional. Relative abundance helps us draw less biased comparisons between samples.</p>
<div class="cell">
<details class="code-fold">
<details>
<summary>Show code</summary>
<div class="sourceCode cell-code" id="cb5"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1"></a><span class="co"># Import packages</span></span>
<span id="cb5-2"><a href="#cb5-2"></a><span class="fu">library</span>(miaViz)</span>
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</details>

</div>
<img data-src="compositional_heatmap_files/figure-revealjs/fig-abund-1.png" width="960" class="r-stretch quarto-figure-center"><p class="caption">
Figure&nbsp;1: Sample composition by counts (left) or relative abundance (right).
</p></section>
<img data-src="compositional_heatmap_files/figure-revealjs/fig-abund-1.png" width="960" class="r-stretch quarto-figure-center"><p class="caption">Figure&nbsp;1: Sample composition by counts (left) or relative abundance (right).</p></section>
<section id="example-1.2" class="slide level2">
<h2>Example 1.2</h2>
<p>To reduce data skewness, we further transform the relative abundance assay with the <strong>Centered-Log Ratio</strong> (CLR), which is defined as follows:</p>
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<span id="cb8-3"><a href="#cb8-3"></a>clrz_hm</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>

</div>
<img data-src="compositional_heatmap_files/figure-revealjs/fig-compheat-1.png" width="960" class="r-stretch quarto-figure-center"><p class="caption">
Figure&nbsp;2: Heatmap of CLR-Z assay where columns correspond to samples and rows to taxa agglomerated by order.
</p></section>
<img data-src="compositional_heatmap_files/figure-revealjs/fig-compheat-1.png" width="960" class="r-stretch quarto-figure-center"><p class="caption">Figure&nbsp;2: Heatmap of CLR-Z assay where columns correspond to samples and rows to taxa agglomerated by order.</p></section>
<section id="why-clr-z-transformation" class="slide level2">
<h2>Why clr-z transformation?</h2>
<p>A CLR-z transformation improves comparability in two steps:</p>
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<li>Find <strong>Z score</strong> to standardise features <strong>row-wise</strong></li>
</ol>

<img data-src="compositional_heatmap_files/figure-revealjs/fig-comparison-1.png" width="960" class="r-stretch quarto-figure-center"><p class="caption">
Figure&nbsp;3: Visual comparison between counts, relative abundance, clr and clr-z assays (from left to right).
</p></section>
<img data-src="compositional_heatmap_files/figure-revealjs/fig-comparison-1.png" width="960" class="r-stretch quarto-figure-center"><p class="caption">Figure&nbsp;3: Visual comparison between counts, relative abundance, clr and clr-z assays (from left to right).</p></section>
<section id="exercise-1" class="slide level2">
<h2>Exercise 1</h2>
<ul>
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6 changes: 3 additions & 3 deletions docs/search.json
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"href": "compositional_heatmap.html#why-relative-abundances",
"title": "Compositional Heatmaps",
"section": "Why relative abundances?",
"text": "Why relative abundances?\nMicrobiome data is compositional. Relative abundance helps us draw less biased comparisons between samples.\n\n\nShow code\n# Import packages\nlibrary(miaViz)\nlibrary(patchwork)\n\n# Plot composition by counts\ncounts_bar &lt;- plotAbundance(tse_order, rank = \"Phylum\", use_relative = FALSE) +\n ylab(\"Counts\")\n\n# Plot composition by relative abundance\nrelab_bar &lt;- plotAbundance(tse_order, rank = \"Phylum\") +\n ylab(\"Relative Abundance\")\n\n# Combine plots\n(counts_bar | relab_bar) +\n plot_layout(guides = \"collect\")\n\n\n\n\nFigure 1: Sample composition by counts (left) or relative abundance (right)."
"text": "Why relative abundances?\nMicrobiome data is compositional. Relative abundance helps us draw less biased comparisons between samples.\n\n\nShow code\n# Import packages\nlibrary(miaViz)\nlibrary(patchwork)\n\n# Plot composition by counts\ncounts_bar &lt;- plotAbundance(tse_order, rank = \"Phylum\", use_relative = FALSE) +\n ylab(\"Counts\")\n\n# Plot composition by relative abundance\nrelab_bar &lt;- plotAbundance(tse_order, rank = \"Phylum\") +\n ylab(\"Relative Abundance\")\n\n# Combine plots\n(counts_bar | relab_bar) +\n plot_layout(guides = \"collect\")\n\n\n\nFigure 1: Sample composition by counts (left) or relative abundance (right)."
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"text": "Example 1.3\nFinally, we visualise the clr-z assay with ComplexHeatmap.\n\n# Visualise clr-z assay with a heatmap\nclrz_hm &lt;- Heatmap(assay(tse_order, \"clr_z\"), name = \"clr-z\")\nclrz_hm\n\n\n\nFigure 2: Heatmap of CLR-Z assay where columns correspond to samples and rows to taxa agglomerated by order."
"text": "Example 1.3\nFinally, we visualise the clr-z assay with ComplexHeatmap.\n\n# Visualise clr-z assay with a heatmap\nclrz_hm &lt;- Heatmap(assay(tse_order, \"clr_z\"), name = \"clr-z\")\nclrz_hm\n\n\nFigure 2: Heatmap of CLR-Z assay where columns correspond to samples and rows to taxa agglomerated by order."
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"text": "Why clr-z transformation?\nA CLR-z transformation improves comparability in two steps:\n\nApply CLR transform to center features column-wise\nFind Z score to standardise features row-wise\n\n\n\nFigure 3: Visual comparison between counts, relative abundance, clr and clr-z assays (from left to right)."
"text": "Why clr-z transformation?\nA CLR-z transformation improves comparability in two steps:\n\nApply CLR transform to center features column-wise\nFind Z score to standardise features row-wise\n\n\nFigure 3: Visual comparison between counts, relative abundance, clr and clr-z assays (from left to right)."
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