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docs/devel/index.html

@@ -554,7 +554,7 @@ <h1 class="title">Orchestrating Microbiome Analysis</h1>
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-<p><strong>Package:</strong> OMA<br><strong>Authors:<br></strong> - Leo Lahti [aut]<br> - Tuomas Borman [aut, cre]<br> - Felix GM Ernst [aut]<br> - and others (see the full list of contributors) [ctb]<br><strong>Compiled:</strong> 2024-08-05<br><strong>Package version:</strong> 0.98.25<br><strong>R version:</strong> R version 4.4.1 (2024-06-14)<br><strong>BioC version:</strong> 3.20<br><strong>License:</strong> CC BY-NC-SA 4.0<br></p>
+<p><strong>Package:</strong> OMA<br><strong>Authors:<br></strong> - Leo Lahti [aut]<br> - Tuomas Borman [aut, cre]<br> - Felix GM Ernst [aut]<br> - and others (see the full list of contributors) [ctb]<br><strong>Compiled:</strong> 2024-08-10<br><strong>Package version:</strong> 0.98.25<br><strong>R version:</strong> R version 4.4.1 (2024-06-14)<br><strong>BioC version:</strong> 3.20<br><strong>License:</strong> CC BY-NC-SA 4.0<br></p>
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docs/devel/pages/acknowledgments.html

@@ -609,16 +609,26 @@ <h1 class="title">
 <li><p><em>Noah de Gunst</em></p></li>
 <li><p><em>Axel Dagnaud</em></p></li>
 <li><p><em>Ely Seraidarian</em></p></li>
-</ul>
-<p>-<em>Théotime Pralas</em></p>
-<p>-<em>Muluh Muluh</em></p>
-<p>-<em>Jiya Chaudhary</em></p>
-<p>-<em>Elina Chiesa</em></p>
-<p>-<em>Pande Erawijantari</em></p>
-<p>-<em>Shadman Ishraq</em></p>
-<p>-<em>Sam Hillman</em></p>
-<p>-<em>Matteo Calgaro</em></p>
-<ul>
+<li><p><em>Théotime Pralas</em></p></li>
+<li><p><em>Geraldson Muluh</em></p></li>
+<li><p><em>Jiya Chaudhary</em></p></li>
+<li><p><em>Elina Chiesa</em></p></li>
+<li><p><em>Pande Erawijantari</em></p></li>
+<li><p><em>Shadman Ishraq</em></p></li>
+<li><p><em>Sam Hillman</em></p></li>
+<li><p><em>Matteo Calgaro</em></p></li>
+<li><p><em>Basil Courbayre Dussau</em></p></li>
+<li><p><em>Yang Cao</em></p></li>
+<li><p><em>Eineje Ameh</em></p></li>
+<li><p><em>Domenick J. Braccia</em></p></li>
+<li><p><em>Renuka Potbhare</em></p></li>
+<li><p><em>Hervé Pagès</em></p></li>
+<li><p><em>Moritz E. Beber</em></p></li>
+<li><p><em>Nitesh Turaga</em></p></li>
+<li><p><em>Vivian Ikeh</em></p></li>
+<li><p><em>Yu Gao</em></p></li>
+<li><p><em>Daniel Garza</em></p></li>
+<li><p><em>Karoline Faust</em></p></li>
 <li><p><em>Jacques Serizay</em> converted the <em>OMA</em> book to the <code>BiocBook</code> format. This allows the <em>OMA</em> book to be built and distributed by Bioconductor.</p></li>
 <li><p><em>Himel Mallick, PhD, FASA</em>, principal investigator and tenure-track faculty at Cornell University’s Department of Population Health Sciences and an adjunct faculty of Statistics and Data Science at Bowers College of Computing and Information Science. He contributed to the chapters on meta-analyses, microbe set enrichment analysis (MSEA) and multi-omics prediction and classification.</p></li>
 <li><p><em>Yihan Liu</em>, assisted Dr.&nbsp;Mallick in writing the chapters on meta-anlayses, MSEA and multi-omics prediction and classification.</p></li>

docs/devel/pages/alpha_diversity.html

@@ -632,7 +632,10 @@ <h1 class="title"><span id="sec-community-diversity" class="quarto-section-ident
 A, Chao, and Lee SM. 1992. <span>“Estimating the Number of Classes via Sample Coverage.”</span> <em>Journal of the American Statistical Association</em> 87 (417): 210–17. https://doi.org/<a href="https://doi.org/10.1080/01621459.1992.10475194">https://doi.org/10.1080/01621459.1992.10475194</a>.
 </div><div id="ref-Chao1984" class="csl-entry" role="listitem">
 A, Chao. 1984. <span>“Non-Parametric Estimation of the Number of Classes in a Population.”</span> <em>Scandinavian Journal of Statistics</em> 11 (4): 265–70. <a href="https://www.jstor.org/stable/4615964">https://www.jstor.org/stable/4615964</a>.
-</div></div><p><strong>Evenness</strong> focuses on the distribution of species abundances, and it can thus complement the number of species. Pielou’s evenness is a commonly used index, obtained by normalizing Shannon diversity by (the natural logarithm of) observed richness.</p>
+</div><div id="ref-Deng2024" class="csl-entry" role="listitem">
+Deng, Yongcui, Alexander K Umbach, and Josh D Neufeld. 2024. <span>“Nonparametric Richness Estimators <span>Chao1</span> and <span>ACE</span> Must Not Be Used with Amplicon Sequence Variant Data.”</span> <em><span>The ISME Journal</span></em> 18 (1): wrae106. <a href="https://doi.org/10.1093/ismejo/wrae106">https://doi.org/10.1093/ismejo/wrae106</a>.
+</div></div><p>Nonparametric richness estimators such as Chao1 and ACE, however, must not be used with amplicon sequence variant (ASV) data. Algorithms that generate ASVs, like DADA2 and Deblur, typically remove singletons, which are essential for these richness calculations. This removal leads to meaningless results. Although ASVs offer higher resolution than operational taxonomic units (OTUs) and are increasingly used, the removal of singletons invalidates the application of Chao1 and ACE. Therefore, alternative alpha diversity metrics that do not depend on singletons or doubletons should be considered, or OTUs could be used specifically for alpha diversity analysis to retain low-abundance taxa. Additionally, the inability of denoising algorithms to distinguish true singleton sequences from artifacts further complicates the issue, making traditional richness estimators unsuitable for ASV datasets, which are often standardized for sequencing depth.<span class="citation" data-cites="Deng2024">(<a href="#ref-Deng2024" role="doc-biblioref">Deng, Umbach, and Neufeld 2024</a>)</span></p>
+<p><strong>Evenness</strong> focuses on the distribution of species abundances, and it can thus complement the number of species. Pielou’s evenness is a commonly used index, obtained by normalizing Shannon diversity by (the natural logarithm of) observed richness.</p>
 <p>These main classes of alpha diversity are sometimes complemented with indices of dominance or rarity:</p>
 <p><strong>Dominance</strong> indices are in general negatively correlated with alpha diversity. A high dominance is obtained when one or a few species have a high share of the total species abundance in the community. Note that dominance indices are generally inversely correlated with other alpha diversity indices.</p>
 <p><strong>Rarity</strong> indices characterize the concentration of species at low abundance. Prevalence and detection thresholds determine rare species whose total concentration will determine the value of a rarity index.</p>

docs/devel/pages/beta_diversity.html

@@ -1004,20 +1004,20 @@ <h1 class="title"><span id="sec-community-similarity" class="quarto-section-iden
 <p>In typical use cases, we would like to know how well the ordination reflects the original similarity structures; then the quantity of interest is the so-called “stress” function, which measures the difference in pairwise similarities between the data points in the original (high-dimensional) vs.&nbsp;projected (low-dimensional) space.</p>
 <p>Hence, we propose that for PCoA and other ordination methods, users would report relative stress, which varies within the unit interval and is better if smaller. This can be calculated as shown below.</p>
 <div class="cell" data-layout-align="center">
-<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span></span>
-<span><span class="co"># Quantify dissimilarities in the original feature space</span></span>
-<span><span class="co"># Pick relabunance assay separately</span></span>
-<span><span class="va">x</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html">assay</a></span><span class="op">(</span><span class="va">tse</span>, <span class="st">"relabundance"</span><span class="op">)</span></span>
-<span><span class="va">d0</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html">as.matrix</a></span><span class="op">(</span><span class="fu">vegan</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/vegan/man/vegdist.html">vegdist</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/t.html">t</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span>, <span class="st">"bray"</span><span class="op">)</span><span class="op">)</span></span>
+<div class="sourceCode" id="cb17"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="co"># Quantify dissimilarities in the original feature space</span></span>
+<span><span class="va">d0</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html">as.matrix</a></span><span class="op">(</span><span class="fu">vegan</span><span class="fu">::</span><span class="fu"><a href="https://rdrr.io/pkg/vegan/man/vegdist.html">vegdist</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/t.html">t</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/pkg/SummarizedExperiment/man/SummarizedExperiment-class.html">assay</a></span><span class="op">(</span><span class="va">tse</span>, <span class="st">"relabundance"</span><span class="op">)</span><span class="op">)</span>, <span class="st">"bray"</span><span class="op">)</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># PCoA Ordination</span></span>
-<span><span class="va">pcoa</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/as.data.frame.html">as.data.frame</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/cmdscale.html">cmdscale</a></span><span class="op">(</span><span class="va">d0</span>, k <span class="op">=</span> <span class="fl">2</span><span class="op">)</span><span class="op">)</span></span>
-<span><span class="fu"><a href="https://rdrr.io/r/base/names.html">names</a></span><span class="op">(</span><span class="va">pcoa</span><span class="op">)</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"PCoA1"</span>, <span class="st">"PCoA2"</span><span class="op">)</span></span>
+<span><span class="va">tse</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/pkg/scater/man/runMDS.html">runMDS</a></span><span class="op">(</span><span class="va">tse</span>,</span>
+<span>                FUN <span class="op">=</span> <span class="fu">vegan</span><span class="fu">::</span><span class="va"><a href="https://rdrr.io/pkg/vegan/man/vegdist.html">vegdist</a></span>,</span>
+<span>                name <span class="op">=</span> <span class="st">"PCoA"</span>,</span>
+<span>                method <span class="op">=</span> <span class="st">"bray"</span>,</span>
+<span>                assay.type <span class="op">=</span> <span class="st">"relabundance"</span><span class="op">)</span></span>
 <span></span>
 <span><span class="co"># Quantify dissimilarities in the ordination space</span></span>
-<span><span class="va">dp</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html">as.matrix</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/dist.html">dist</a></span><span class="op">(</span><span class="va">pcoa</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="va">dp</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/matrix.html">as.matrix</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/stats/dist.html">dist</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/pkg/SingleCellExperiment/man/reducedDims.html">reducedDim</a></span><span class="op">(</span><span class="va">tse</span>, <span class="st">"PCoA"</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span>
 <span></span>
-<span><span class="co"># Calculate stress i.e. relative difference</span></span>
+<span><span class="co"># Calculate stress i.e. relative difference </span></span>
 <span><span class="co"># in the original and projected dissimilarities</span></span>
 <span><span class="va">stress</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html">sum</a></span><span class="op">(</span><span class="op">(</span><span class="va">dp</span> <span class="op">-</span> <span class="va">d0</span><span class="op">)</span><span class="op">^</span><span class="fl">2</span><span class="op">)</span> <span class="op">/</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html">sum</a></span><span class="op">(</span><span class="va">d0</span><span class="op">^</span><span class="fl">2</span><span class="op">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
@@ -1129,7 +1129,7 @@ <h1 class="title"><span id="sec-community-similarity" class="quarto-section-iden
 <td style="text-align: right;">6</td>
 <td style="text-align: right;">1.1157</td>
 <td style="text-align: right;">1.940</td>
-<td style="text-align: right;">0.029</td>
+<td style="text-align: right;">0.037</td>
 <td style="text-align: right;">3.991</td>
 <td style="text-align: right;">0.2795</td>
 </tr>
@@ -1138,7 +1138,7 @@ <h1 class="title"><span id="sec-community-similarity" class="quarto-section-iden
 <td style="text-align: right;">4</td>
 <td style="text-align: right;">0.5837</td>
 <td style="text-align: right;">1.522</td>
-<td style="text-align: right;">0.127</td>
+<td style="text-align: right;">0.135</td>
 <td style="text-align: right;">3.991</td>
 <td style="text-align: right;">0.1463</td>
 </tr>
@@ -1147,7 +1147,7 @@ <h1 class="title"><span id="sec-community-similarity" class="quarto-section-iden
 <td style="text-align: right;">1</td>
 <td style="text-align: right;">0.1679</td>
 <td style="text-align: right;">1.751</td>
-<td style="text-align: right;">0.124</td>
+<td style="text-align: right;">0.108</td>
 <td style="text-align: right;">3.991</td>
 <td style="text-align: right;">0.0421</td>
 </tr>
@@ -1276,7 +1276,7 @@ <h1 class="title"><span id="sec-community-similarity" class="quarto-section-iden
 <td style="text-align: right;">0.0628</td>
 <td style="text-align: right;">2.7440</td>
 <td style="text-align: right;">999</td>
-<td style="text-align: right;">0.130</td>
+<td style="text-align: right;">0.108</td>
 <td style="text-align: right;">1.0288</td>
 <td style="text-align: right;">0.2440</td>
 </tr>
@@ -1287,7 +1287,7 @@ <h1 class="title"><span id="sec-community-similarity" class="quarto-section-iden
 <td style="text-align: right;">0.0103</td>
 <td style="text-align: right;">0.4158</td>
 <td style="text-align: right;">999</td>
-<td style="text-align: right;">0.524</td>
+<td style="text-align: right;">0.557</td>
 <td style="text-align: right;">0.9283</td>
 <td style="text-align: right;">0.0111</td>
 </tr>
@@ -1298,7 +1298,7 @@ <h1 class="title"><span id="sec-community-similarity" class="quarto-section-iden
 <td style="text-align: right;">0.0113</td>
 <td style="text-align: right;">17.0255</td>
 <td style="text-align: right;">999</td>
-<td style="text-align: right;">0.427</td>
+<td style="text-align: right;">0.393</td>
 <td style="text-align: right;">0.3319</td>
 <td style="text-align: right;">0.9860</td>
 </tr>

docs/devel/pages/differential_abundance.html

@@ -118,7 +118,7 @@
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