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25 changes: 12 additions & 13 deletions docs/devel/index.html
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Expand Down Expand Up @@ -354,17 +354,16 @@ <h1 class="title">Orchestrating Microbiome Analysis</h1>
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</header><p><img src="assets/cover.png" title="Orchestrating Microbiome Analysis" class="quarto-cover-image img-fluid"></p>
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<p>{strong(‘Package’)}: {pkg} <strong>Authors:</strong> &lt;br/&gt; {format(authors, include = c(‘given’, ‘family’, ‘role’)) |&gt; lapply(tags<span class="math inline">\(li) |&amp;gt; tags\)</span>ul()}&lt;br/&gt;</p>
<p><strong>Compiled:</strong> {as.character(Sys.Date())}&lt;br/&gt;</p>
<p><strong>Package version:</strong> {version}&lt;br/&gt;</p>
<p><strong>R version:</strong> &lt;b style=‘color:red;’&gt;{R.version.string}&lt;/b&gt;&lt;br/&gt;</p>
<p><strong>BioC version:</strong> &lt;b style=‘color:red;’&gt;{BiocManager::version()}&lt;/b&gt;&lt;br/&gt;</p>
<strong>License:</strong> {license}&lt;br/&gt;
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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> 2023-11-17<br><strong>Package version:</strong> 0.98.16<br><strong>R version:</strong> <b style="color:red;">R Under development (unstable) (2023-11-08 r85496)</b><br><strong>BioC version:</strong> <b style="color:red;">3.19</b><br><strong>License:</strong> CC BY-NC-SA 4.0<br></p>
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<section id="welcome" class="level1 unnumbered page-columns page-full"><h1 class="unnumbered">Welcome</h1>
<p>You are reading the online book, <a href="https://microbiome.github.io/OMA/"><strong>Orchestrating Microbiome Analysis with Bioconductor</strong></a> <span class="citation" data-cites="OMA">(<a href="#ref-OMA" role="doc-biblioref">Lahti et al. 2021</a>)</span>, where we walk through common strategies and workflows in microbiome data science.</p>
<div class="no-row-height column-margin column-container"><div id="ref-OMA" class="csl-entry" role="listitem">
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<span><span class="co">## zlibbioc 1.49.0 2023-10-24 [2] Bioconductor</span></span>
<span><span class="co">## zoo 1.8-12 2023-04-13 [2] CRAN (R 4.4.0)</span></span>
<span><span class="co">## </span></span>
<span><span class="co">## [1] /tmp/RtmpQaUrm0/Rinstb12a9a32a</span></span>
<span><span class="co">## [1] /tmp/RtmpUjPmHj/Rinstb6441c640</span></span>
<span><span class="co">## [2] /usr/local/lib/R/site-library</span></span>
<span><span class="co">## [3] /usr/local/lib/R/library</span></span>
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</ul>
</li>
<li>
<a href="#loading-experimental-microbiome-data" id="toc-loading-experimental-microbiome-data" class="nav-link" data-scroll-target="#loading-experimental-microbiome-data"><span class="header-section-number">2.4</span> Loading experimental microbiome data</a>
<a href="#sec-loading-experimental-microbiome-data" id="toc-sec-loading-experimental-microbiome-data" class="nav-link" data-scroll-target="#sec-loading-experimental-microbiome-data"><span class="header-section-number">2.4</span> Loading experimental microbiome data</a>
<ul class="collapse">
<li><a href="#s-workflow" id="toc-s-workflow" class="nav-link" data-scroll-target="#s-workflow"><span class="header-section-number">2.4.1</span> 16S workflow</a></li>
<li><a href="#sec-import-from-file" id="toc-sec-import-from-file" class="nav-link" data-scroll-target="#sec-import-from-file"><span class="header-section-number">2.4.2</span> Import from external files</a></li>
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</div></div><p>[<code>TreeSummarizedExperiment</code>] (<code>TreeSE</code>) <span class="citation" data-cites="R_TreeSummarizedExperiment">(<a href="#ref-R_TreeSummarizedExperiment" role="doc-biblioref">Huang 2020</a>)</span> was developed as an extension to incorporate hierarchical information (such as phylogenetic trees and sample hierarchies) and reference sequences.</p>
<p>[<code>MultiAssayExperiment</code>] (<code>MAE</code>) <span class="citation" data-cites="Ramos2017">(<a href="#ref-Ramos2017" role="doc-biblioref">Ramos et al. 2017</a>)</span> provides an organized way to bind several different data containers together in a single object. For example, we can bind microbiome data (in <code>TreeSE</code> container) with metabolomic profiling data (in <code>SE</code>) container, with (partially) shared sample metadata. This is convenient and robust for instance in subsetting and other data manipulation tasks. Microbiome data can be part of multiomics experiments and analysis strategies. We highlight how the methods used througout in this book relate to this data framework by using the <code>TreeSummarizedExperiment</code>, <code>MultiAssayExperiment</code>, and classes beyond.</p>
<div class="no-row-height column-margin column-container"></div><p>This section provides an introductions to these data containers. In microbiome data science, these containers link taxonomic abundance tables with rich side information on the features and samples. Taxonomic abundance data can be obtained by 16S rRNA amplicon or metagenomic sequencing, phylogenetic microarrays, or by other means. Many microbiome experiments include multiple versions and types of data generated independently or derived from each other through transformation or agglomeration. We start by providing recommendations on how to represent different varieties of multi-table data within the <code>TreeSummarizedExperiment</code> class.</p>
<p>The options and recommendations are summarized in Table <a href="#tbl-options">Table&nbsp;<span>2.1</span></a>.</p>
<p>The options and recommendations are summarized in <a href="#tbl-options">Table&nbsp;<span>2.1</span></a>.</p>
<section id="sec-assay-slot" class="level3" data-number="2.2.1"><h3 data-number="2.2.1" class="anchored" data-anchor-id="sec-assay-slot">
<span class="header-section-number">2.2.1</span> Assay data</h3>
<p>The original count-based taxonomic abundance tables may have different transformations, such as logarithmic, Centered Log-Ratio (CLR), or relative abundance. These are typically stored in <em><strong>assays</strong></em>.</p>
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<span><span class="fu"><a href="https://rdrr.io/r/utils/data.html">data</a></span><span class="op">(</span><span class="va">HintikkaXOData</span>, package <span class="op">=</span> <span class="st">"mia"</span><span class="op">)</span></span>
<span><span class="va">mae</span> <span class="op">&lt;-</span> <span class="va">HintikkaXOData</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p>Data is available in <em><a href="https://bioconductor.org/packages/3.19/SummarizedExperiment">SummarizedExperiment</a></em>, <code>r Biocpkg("TreeSummarizedExperiment")</code> and <code>r Biocpkg("MultiAssayExperiment")</code> data containers; see the separate page on <a href="https://microbiome.github.io/OMA/multitable.html">alternative containers</a> for more details.</p>
<p>Data is available in <em><a href="https://bioconductor.org/packages/3.19/SummarizedExperiment">SummarizedExperiment</a></em>, <code>r Biocpkg("TreeSummarizedExperiment")</code> and <code>r Biocpkg("MultiAssayExperiment")</code> data containers; see the separate page on <a href="../pages/23_multi-assay_analyses.html">alternative containers</a> for more details.</p>
</section><section id="curated-metagenomic-data" class="level3 page-columns page-full" data-number="2.3.3"><h3 data-number="2.3.3" class="anchored" data-anchor-id="curated-metagenomic-data">
<span class="header-section-number">2.3.3</span> Curated metagenomic data</h3>
<p><a href="https://bioconductor.org/packages/release/data/experiment/html/curatedMetagenomicData.html">curatedMetagenomicData</a> is a large collection of curated human microbiome datasets, provided as <code>(Tree)SummarizedExperiment</code> objects <span class="citation" data-cites="Pasolli2017">(<a href="#ref-Pasolli2017" role="doc-biblioref">Pasolli et al. 2017</a>)</span>. The resource provides curated human microbiome data including gene families, marker abundance, marker presence, pathway abundance, pathway coverage, and relative abundance for samples from different body sites. See the package homepage for more details on data availability and access.</p>
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<li>
<a href="https://github.com/cran/qiitr">qiitr</a> provides access to <a href="https://qiita.com/about">QIITA</a>
</li>
</ul></section></section><section id="loading-experimental-microbiome-data" class="level2" data-number="2.4"><h2 data-number="2.4" class="anchored" data-anchor-id="loading-experimental-microbiome-data">
</ul></section></section><section id="sec-loading-experimental-microbiome-data" class="level2" data-number="2.4"><h2 data-number="2.4" class="anchored" data-anchor-id="sec-loading-experimental-microbiome-data">
<span class="header-section-number">2.4</span> Loading experimental microbiome data</h2>
<section id="s-workflow" class="level3" data-number="2.4.1"><h3 data-number="2.4.1" class="anchored" data-anchor-id="s-workflow">
<span class="header-section-number">2.4.1</span> 16S workflow</h3>
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}
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<p><img src="images/mia_logo.png" width="100" alt="mia logo" align="right" style="margin: 0 1em 0 1em"></p>
<div class="quarto-layout-panel">
<div class="quarto-layout-row quarto-layout-valign-top">
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<p><img src="images/mia_logo.png" width="50%" alt="mia logo" align="middle" style="margin: 0 1em 0 1em"></p>
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<p><img src="images/ecosystem.png" width="70%" alt="mia logo" align="middle" style="margin: 0 1em 0 1em"></p>
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<p>The Bioconductor microbiome data science framework consists of:</p>
<ul>
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<strong>community</strong> of users and developers</li>
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<p><img src="images/ecosystem.png" width="100" alt="mia logo" align="right" style="margin: 0 1em 0 1em"></p>
<p>This section provides an overview of the package ecosystem. <a href="04_containers.html#sec-example-data"><span>Section&nbsp;2.3</span></a> links to various open microbiome data resources that support this framework.</p>
<section id="package-installation" class="level2" data-number="1.1"><h2 data-number="1.1" class="anchored" data-anchor-id="package-installation">
<span class="header-section-number">1.1</span> Package installation</h2>
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</div>
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<main class="content" id="quarto-document-content"><header id="title-block-header" class="quarto-title-block default"><div class="quarto-title">
<h1 class="title"><span id="sc-edatamanipulation" class="quarto-section-identifier"><span class="chapter-number">3</span>&nbsp; <span class="chapter-title">Data Manipulation</span></span></h1>
<h1 class="title"><span id="sec-datamanipulation" class="quarto-section-identifier"><span class="chapter-number">3</span>&nbsp; <span class="chapter-title">Data Manipulation</span></span></h1>
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<span></span>
<span><span class="co"># view new variable</span></span>
<span><span class="fu"><a href="https://rdrr.io/r/utils/head.html">head</a></span><span class="op">(</span><span class="va">tse</span><span class="op">$</span><span class="va">NewVariable</span><span class="op">)</span></span>
<span><span class="co">## [1] 0.9387 0.7439 0.9393 0.9141 0.4957 0.6280</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<span><span class="co">## [1] 0.05097 0.29386 0.38221 0.89491 0.85688 0.55630</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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</section><section id="merge-data" class="level2" data-number="3.3"><h2 data-number="3.3" class="anchored" data-anchor-id="merge-data">
<span class="header-section-number">3.3</span> Merge data</h2>
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2 changes: 1 addition & 1 deletion docs/devel/pages/19_visualization_techniques.html
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Expand Up @@ -476,7 +476,7 @@ <h1 class="title"><span id="sec-viz-chapter" class="quarto-section-identifier"><
</div>
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<p>Further methods of application can be found in the chapters <a href="12_quality_control.html#sec-qc"><span>Section&nbsp;4.3</span></a> and <a href="14_alpha_diversity.html#sec-richness"><span>Section&nbsp;6.1.1</span></a> and in a few <a href="https://github.com/davismcc/scater_tutorials_open_data">external tutorials</a> with open data. Additionally, <code>rowData</code> and <code>colData</code> allow manipulation and subsetting of large data sets into smaller units, as explained in chapter <span class="quarto-unresolved-ref">?sec-datamanipulation</span>.</p>
<p>Further methods of application can be found in the chapters <a href="12_quality_control.html#sec-qc"><span>Section&nbsp;4.3</span></a> and <a href="14_alpha_diversity.html#sec-richness"><span>Section&nbsp;6.1.1</span></a> and in a few <a href="https://github.com/davismcc/scater_tutorials_open_data">external tutorials</a> with open data. Additionally, <code>rowData</code> and <code>colData</code> allow manipulation and subsetting of large data sets into smaller units, as explained in chapter <a href="10_manipulation.html"><span>Chapter&nbsp;3</span></a>.</p>
</section><section id="viewing-abundance-and-prevalence-patterns" class="level3" data-number="13.1.2"><h3 data-number="13.1.2" class="anchored" data-anchor-id="viewing-abundance-and-prevalence-patterns">
<span class="header-section-number">13.1.2</span> Viewing abundance and prevalence patterns</h3>
<p>Prior-to-analysis exploration may involve questions such as how microorganisms are distributed across samples (abundance) and what microorganisms are present in most of the samples (prevalence). The information on abundance and prevalence can be summarized into a <strong>jitter</strong> or <strong>density plot</strong> and a <strong>tree</strong>, respectively, with the <em>miaViz</em> package.</p>
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Expand Up @@ -742,7 +742,7 @@ <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;">0.041</td>
<td style="text-align: right;">0.040</td>
<td style="text-align: right;">3.991</td>
<td style="text-align: right;">0.2795</td>
</tr>
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<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;">0.130</td>
<td style="text-align: right;">0.133</td>
<td style="text-align: right;">3.991</td>
<td style="text-align: right;">0.1463</td>
</tr>
Expand All @@ -760,7 +760,7 @@ <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;">0.131</td>
<td style="text-align: right;">0.113</td>
<td style="text-align: right;">3.991</td>
<td style="text-align: right;">0.0421</td>
</tr>
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<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;">0.120</td>
<td style="text-align: right;">0.106</td>
<td style="text-align: right;">1.0288</td>
<td style="text-align: right;">0.2440</td>
</tr>
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<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;">0.534</td>
<td style="text-align: right;">0.523</td>
<td style="text-align: right;">0.9283</td>
<td style="text-align: right;">0.0111</td>
</tr>
Expand All @@ -844,7 +844,7 @@ <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;">0.430</td>
<td style="text-align: right;">0.400</td>
<td style="text-align: right;">0.3319</td>
<td style="text-align: right;">0.9860</td>
</tr>
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