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<li><a href="#wolves-diet-based-on-dna-metabarcoding" id="toc-wolves-diet-based-on-dna-metabarcoding" class="nav-link active" data-scroll-target="#wolves-diet-based-on-dna-metabarcoding"><span class="toc-section-number">3.1</span> Wolves’ diet based on DNA metabarcoding</a></li>
<li><a href="#step-by-step-analysis" id="toc-step-by-step-analysis" class="nav-link" data-scroll-target="#step-by-step-analysis"><span class="toc-section-number">3.2</span> Step by step analysis</a>
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<li><a href="#recover-full-sequence-reads-from-forward-and-reverse-partial-reads" id="toc-recover-full-sequence-reads-from-forward-and-reverse-partial-reads" class="nav-link" data-scroll-target="#recover-full-sequence-reads-from-forward-and-reverse-partial-reads"><span class="toc-section-number">3.2.1</span> Recover full sequence reads from forward and reverse partial reads</a></li>
<li><a href="#remove-unaligned-sequence-records" id="toc-remove-unaligned-sequence-records" class="nav-link" data-scroll-target="#remove-unaligned-sequence-records"><span class="toc-section-number">3.2.2</span> Remove unaligned sequence records</a></li>
<li><a href="#assign-each-sequence-record-to-the-corresponding-samplemarker-combination" id="toc-assign-each-sequence-record-to-the-corresponding-samplemarker-combination" class="nav-link" data-scroll-target="#assign-each-sequence-record-to-the-corresponding-samplemarker-combination"><span class="toc-section-number">3.2.3</span> Assign each sequence record to the corresponding sample/marker combination</a></li>
<li><a href="#dereplicate-reads-into-uniq-sequences" id="toc-dereplicate-reads-into-uniq-sequences" class="nav-link" data-scroll-target="#dereplicate-reads-into-uniq-sequences"><span class="toc-section-number">3.2.4</span> Dereplicate reads into uniq sequences</a></li>
<li><a href="#denoise-the-sequence-dataset" id="toc-denoise-the-sequence-dataset" class="nav-link" data-scroll-target="#denoise-the-sequence-dataset"><span class="toc-section-number">3.2.5</span> Denoise the sequence dataset</a></li>
<li><a href="#taxonomic-assignment-of-sequences" id="toc-taxonomic-assignment-of-sequences" class="nav-link" data-scroll-target="#taxonomic-assignment-of-sequences"><span class="toc-section-number">3.2.6</span> Taxonomic assignment of sequences</a></li>
<li><a href="#assign-each-sequence-to-a-taxon" id="toc-assign-each-sequence-to-a-taxon" class="nav-link" data-scroll-target="#assign-each-sequence-to-a-taxon"><span class="toc-section-number">3.2.7</span> Assign each sequence to a taxon</a></li>
<li><a href="#generate-the-final-result-table" id="toc-generate-the-final-result-table" class="nav-link" data-scroll-target="#generate-the-final-result-table"><span class="toc-section-number">3.2.8</span> Generate the final result table</a></li>
<li><a href="#looking-at-the-data-in-r" id="toc-looking-at-the-data-in-r" class="nav-link" data-scroll-target="#looking-at-the-data-in-r"><span class="toc-section-number">3.2.9</span> Looking at the data in R</a></li>
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<h1 class="title d-none d-lg-block"><span class="chapter-number">3</span>&nbsp; <span class="chapter-title">OBITools V4 Tutorial</span></h1>
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<p>Here is a short tutorial on how to analyze DNA metabarcoding data produced on Illumina sequencers using:</p>
<ul>
<li>the OBITools</li>
<li>some basic Unix commands</li>
</ul>
<section id="wolves-diet-based-on-dna-metabarcoding" class="level2" data-number="3.1">
<h2 data-number="3.1" class="anchored" data-anchor-id="wolves-diet-based-on-dna-metabarcoding"><span class="header-section-number">3.1</span> Wolves’ diet based on DNA metabarcoding</h2>
<p>The data used in this tutorial correspond to the analysis of four wolf scats, using the protocol published in <span class="citation" data-cites="Shehzad2012-pn">Shehzad et al. (<a href="references.html#ref-Shehzad2012-pn" role="doc-biblioref">2012</a>)</span> for assessing carnivore diet. After extracting DNA from the faeces, the DNA amplifications were carried out using the primers <code>TTAGATACCCCACTATGC</code> and <code>TAGAACAGGCTCCTCTAG</code> amplifiying the <em>12S-V5</em> region <span class="citation" data-cites="Riaz2011-gn">(<a href="references.html#ref-Riaz2011-gn" role="doc-biblioref">Riaz et al. 2011</a>)</span>, together with a wolf blocking oligonucleotide.</p>
<p>The complete data set can be downloaded here: <a href="wolf_diet.tgz">the tutorial dataset</a></p>
<p>Once the data file is downloaded, using a UNIX terminal unarchive the data from the <code>tgz</code> file.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">tar</span> zxvf wolf_diet.tgz</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>That command create a new directory named <code>wolf_data</code> containing every required data files:</p>
<ul>
<li><p><code>fastq &lt;fastq&gt;</code> files resulting of aGA IIx (Illumina) paired-end (2 x 108 bp) sequencing assay of DNA extracted and amplified from four wolf faeces:</p>
<ul>
<li><code>wolf_F.fastq</code></li>
<li><code>wolf_R.fastq</code></li>
</ul></li>
<li><p>the file describing the primers and tags used for all samples sequenced:</p>
<ul>
<li><code>wolf_diet_ngsfilter.txt</code> The tags correspond to short and specific sequences added on the 5' end of each primer to distinguish the different samples</li>
</ul></li>
<li><p>the file containing the reference database in a fasta format:</p>
<ul>
<li><code>db_v05_r117.fasta</code> This reference database has been extracted from the release 117 of EMBL using <code>obipcr</code></li>
</ul></li>
</ul>
<div class="cell">
</div>
<p>To not mix raw data and processed data a new directory called <code>results</code> is created.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="fu">mkdir</span> results</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="step-by-step-analysis" class="level2" data-number="3.2">
<h2 data-number="3.2" class="anchored" data-anchor-id="step-by-step-analysis"><span class="header-section-number">3.2</span> Step by step analysis</h2>
<section id="recover-full-sequence-reads-from-forward-and-reverse-partial-reads" class="level3" data-number="3.2.1">
<h3 data-number="3.2.1" class="anchored" data-anchor-id="recover-full-sequence-reads-from-forward-and-reverse-partial-reads"><span class="header-section-number">3.2.1</span> Recover full sequence reads from forward and reverse partial reads</h3>
<p>When using the result of a paired-end sequencing assay with supposedly overlapping forward and reverse reads, the first step is to recover the assembled sequence.</p>
<p>The forward and reverse reads of the same fragment are <em>at the same line position</em> in the two fastq files obtained after sequencing. Based on these two files, the assembly of the forward and reverse reads is done with the <code>obipairing</code> utility that aligns the two reads and returns the reconstructed sequence.</p>
<p>In our case, the command is:</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obipairing</span> <span class="at">--min-identity</span><span class="op">=</span>0.8 <span class="dt">\</span></span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a> <span class="at">--min-overlap</span><span class="op">=</span>10 <span class="dt">\</span></span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a> <span class="at">-F</span> wolf_data/wolf_F.fastq <span class="dt">\</span></span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a> <span class="at">-R</span> wolf_data/wolf_R.fastq <span class="dt">\</span></span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/wolf.fastq </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>The <code>--min-identity</code> and <code>--min-overlap</code> options allow discarding sequences with low alignment quality. If after the aligment, the overlaping parts of the reads is shorter than 10 base pairs or the similarity over this aligned region is below 80% of identity, in the output file, the forward and reverse reads are not aligned but concatenated, and the value of the <code>mode</code> attribute in the sequence header is set to <code>joined</code> instead of <code>alignment</code>.</p>
</section>
<section id="remove-unaligned-sequence-records" class="level3" data-number="3.2.2">
<h3 data-number="3.2.2" class="anchored" data-anchor-id="remove-unaligned-sequence-records"><span class="header-section-number">3.2.2</span> Remove unaligned sequence records</h3>
<p>Unaligned sequences (:py<code class="interpreted-text" role="mod">mode=joined</code>) cannot be used. The following command allows removing them from the dataset:</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obigrep</span> <span class="at">-p</span> <span class="st">'annotations.mode != "join"'</span> <span class="dt">\</span></span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a> results/wolf.fastq <span class="op">&gt;</span> results/wolf.ali.fastq</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>The <code>-p</code> requires a go like expression. <code>annotations.mode != "join"</code> means that if the value of the <code>mode</code> annotation of a sequence is different from <code>join</code>, the corresponding sequence record will be kept.</p>
<p>The first sequence record of <code>wolf.ali.fastq</code> can be obtained using the following command line:</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb5"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span> <span class="at">-n</span> 4 results/wolf.ali.fastq</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>The folling piece of code appears on thew window of tour terminal.</p>
<pre><code>@HELIUM_000100422_612GNAAXX:7:108:5640:3823#0/1 {"ali_dir":"left","ali_length":62,"mode":"alignment","pairing_mismatches":{"(T:26)-&gt;(G:13)":62,"(T:34)-&gt;(G:18)":48},"score":484,"score_norm":0.968,"seq_a_single":46,"seq_ab_match":60,"seq_b_single":46}
ccgcctcctttagataccccactatgcttagccctaaacacaagtaattaatataacaaaattgttcgccagagtactaccggcaatagcttaaaactcaaaggacttggcggtgctttatacccttctagaggagcctgttctaaggaggcgg
+
CCCCCCCBCCCCCCCCCCCCCCCCCCCCCCBCCCCCBCCCCCCC&lt;CcCccbe[`F`accXV&lt;TA\RYU\\ee_e[XZ[XEEEEEEEEEE?EEEEEEEEEEDEEEEEEECCCCCCCCCCCCCCCCCCCCCCCACCCCCACCCCCCCCCCCCCCCC</code></pre>
</section>
<section id="assign-each-sequence-record-to-the-corresponding-samplemarker-combination" class="level3" data-number="3.2.3">
<h3 data-number="3.2.3" class="anchored" data-anchor-id="assign-each-sequence-record-to-the-corresponding-samplemarker-combination"><span class="header-section-number">3.2.3</span> Assign each sequence record to the corresponding sample/marker combination</h3>
<p>Each sequence record is assigned to its corresponding sample and marker using the data provided in a text file (here <code>wolf_diet_ngsfilter.txt</code>). This text file contains one line per sample, with the name of the experiment (several experiments can be included in the same file), the name of the tags (for example: <code>aattaac</code> if the same tag has been used on each extremity of the PCR products, or <code>aattaac:gaagtag</code> if the tags were different), the sequence of the forward primer, the sequence of the reverse primer, the letter <code>T</code> or <code>F</code> for sample identification using the forward primer and tag only or using both primers and both tags, respectively (see <code>obimultiplex</code> for details).</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb7"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obimultiplex</span> <span class="at">-t</span> wolf_data/wolf_diet_ngsfilter.txt <span class="dt">\</span></span>
<span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a> <span class="at">-u</span> results/unidentified.fastq <span class="dt">\</span></span>
<span id="cb7-3"><a href="#cb7-3" aria-hidden="true" tabindex="-1"></a> results/wolf.ali.fastq <span class="dt">\</span></span>
<span id="cb7-4"><a href="#cb7-4" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/wolf.ali.assigned.fastq</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>This command creates two files:</p>
<ul>
<li><code>unidentified.fastq</code> containing all the sequence records that were not assigned to a sample/marker combination</li>
<li><code>wolf.ali.assigned.fastq</code> containing all the sequence records that were properly assigned to a sample/marker combination</li>
</ul>
<p>Note that each sequence record of the <code>wolf.ali.assigned.fastq</code> file contains only the barcode sequence as the sequences of primers and tags are removed by the <code>obimultiplex</code> program. Information concerning the experiment, sample, primers and tags is added as attributes in the sequence header.</p>
<p>For instance, the first sequence record of <code>wolf.ali.assigned.fastq</code> is:</p>
<pre><code>@HELIUM_000100422_612GNAAXX:7:108:5640:3823#0/1_sub[28..127] {"ali_dir":"left","ali_length":62,"direction":"direct","experiment":"wolf_diet","forward_match":"ttagataccccactatgc","forward_mismatches":0,"forward_primer":"ttagataccccactatgc","forward_tag":"gcctcct","mode":"alignment","pairing_mismatches":{"(T:26)-&gt;(G:13)":35,"(T:34)-&gt;(G:18)":21},"reverse_match":"tagaacaggctcctctag","reverse_mismatches":0,"reverse_primer":"tagaacaggctcctctag","reverse_tag":"gcctcct","sample":"29a_F260619","score":484,"score_norm":0.968,"seq_a_single":46,"seq_ab_match":60,"seq_b_single":46}
ttagccctaaacacaagtaattaatataacaaaattgttcgccagagtactaccggcaatagcttaaaactcaaaggacttggcggtgctttataccctt
+
CCCBCCCCCBCCCCCCC&lt;CcCccbe[`F`accXV&lt;TA\RYU\\ee_e[XZ[XEEEEEEEEEE?EEEEEEEEEEDEEEEEEECCCCCCCCCCCCCCCCCCC</code></pre>
</section>
<section id="dereplicate-reads-into-uniq-sequences" class="level3" data-number="3.2.4">
<h3 data-number="3.2.4" class="anchored" data-anchor-id="dereplicate-reads-into-uniq-sequences"><span class="header-section-number">3.2.4</span> Dereplicate reads into uniq sequences</h3>
<p>The same DNA molecule can be sequenced several times. In order to reduce both file size and computations time, and to get easier interpretable results, it is convenient to work with unique <em>sequences</em> instead of <em>reads</em>. To <em>dereplicate</em> such <em>reads</em> into unique <em>sequences</em>, we use the <code>obiuniq</code> command.</p>
<table class="table">
<colgroup>
<col style="width: 86%">
</colgroup>
<tbody>
<tr class="odd">
<td>Definition: Dereplicate reads into unique sequences</td>
</tr>
<tr class="even">
<td><ol type="1">
<li>compare all the reads in a data set to each other</li>
<li>group strictly identical reads together</li>
<li>output the sequence for each group and its count in the original dataset (in this way, all duplicated reads are removed)</li>
</ol>
<p>Definition adapted from <span class="citation" data-cites="Seguritan2001-tg">Seguritan and Rohwer (<a href="references.html#ref-Seguritan2001-tg" role="doc-biblioref">2001</a>)</span></p></td>
</tr>
</tbody>
</table>
<p>For dereplication, we use the <code>obiuniq</code> command with the <code>-m sample</code>. The <code>-m sample</code> option is used to keep the information of the samples of origin for each uniquesequence.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb9"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obiuniq</span> <span class="at">-m</span> sample <span class="dt">\</span></span>
<span id="cb9-2"><a href="#cb9-2" aria-hidden="true" tabindex="-1"></a> results/wolf.ali.assigned.fastq <span class="dt">\</span></span>
<span id="cb9-3"><a href="#cb9-3" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/wolf.ali.assigned.uniq.fasta</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>Note that <code>obiuniq</code> returns a fasta file.</p>
<p>The first sequence record of <code>wolf.ali.assigned.uniq.fasta</code> is:</p>
<pre><code>&gt;HELIUM_000100422_612GNAAXX:7:93:6991:1942#0/1_sub[28..126] {"ali_dir":"left","ali_length":63,"count":1,"direction":"reverse","experiment":"wolf_diet","forward_match":"ttagataccccactatgc","forward_mismatches":0,"forward_primer":"ttagataccccactatgc","forward_tag":"gaatatc","merged_sample":{"26a_F040644":1},"mode":"alignment","pairing_mismatches":{"(A:10)-&gt;(G:34)":76,"(C:06)-&gt;(A:34)":58},"reverse_match":"tagaacaggctcctctag","reverse_mismatches":0,"reverse_primer":"tagaacaggctcctctag","reverse_tag":"gaatatc","score":730,"score_norm":0.968,"seq_a_single":45,"seq_ab_match":61,"seq_b_single":45}
ttagccctaaacataaacattcaataaacaagaatgttcgccagagaactactagcaaca
gcctgaaactcaaaggacttggcggtgctttatatccct</code></pre>
<p>The run of <code>obiuniq</code> has added two key=values entries in the header of the fasta sequence:</p>
<ul>
<li><code class="interpreted-text" role="mod">"merged_sample":{"29a_F260619":1}</code>: this sequence have been found once in a single sample called <strong>29a_F260619</strong></li>
<li><code>"count":1</code> : the total count for this sequence is <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mn>1</mn><annotation encoding="application/x-tex">1</annotation></semantics></math></li>
</ul>
<p>To keep only these two attributes, we can use the <code>obiannotate</code> command:</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb11"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obiannotate</span> <span class="at">-k</span> count <span class="at">-k</span> merged_sample <span class="dt">\</span></span>
<span id="cb11-2"><a href="#cb11-2" aria-hidden="true" tabindex="-1"></a> results/wolf.ali.assigned.uniq.fasta <span class="dt">\</span></span>
<span id="cb11-3"><a href="#cb11-3" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/wolf.ali.assigned.simple.fasta</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>The first five sequence records of <code>wolf.ali.assigned.simple.fasta</code> become:</p>
<pre><code>&gt;HELIUM_000100422_612GNAAXX:7:26:18930:11105#0/1_sub[28..127] {"count":1,"merged_sample":{"29a_F260619":1}}
ttagccctaaacacaagtaattaatataacaaaatwattcgcyagagtactacmggcaat
agctyaaarctcamagrwcttggcggtgctttataccctt
&gt;HELIUM_000100422_612GNAAXX:7:58:5711:11399#0/1_sub[28..127] {"count":1,"merged_sample":{"29a_F260619":1}}
ttagccctaaacacaagtaattaatataacaaaattattcgccagagtwctaccgssaat
agcttaaaactcaaaggactgggcggtgctttataccctt
&gt;HELIUM_000100422_612GNAAXX:7:100:15836:9304#0/1_sub[28..127] {"count":1,"merged_sample":{"29a_F260619":1}}
ttagccctaaacatagataattacacaaacaaaattgttcaccagagtactagcggcaac
agcttaaaactcaaaggacttggcggtgctttataccctt
&gt;HELIUM_000100422_612GNAAXX:7:55:13242:9085#0/1_sub[28..126] {"count":4,"merged_sample":{"26a_F040644":4}}
ttagccctaaacataaacattcaataaacaagagtgttcgccagagtactactagcaaca
gcctgaaactcaaaggacttggcggtgctttacatccct
&gt;HELIUM_000100422_612GNAAXX:7:86:8429:13723#0/1_sub[28..127] {"count":7,"merged_sample":{"15a_F730814":5,"29a_F260619":2}}
ttagccctaaacacaagtaattaatataacaaaattattcgccagagtactaccggcaat
agcttaaaactcaaaggactcggcggtgctttataccctt</code></pre>
</section>
<section id="denoise-the-sequence-dataset" class="level3" data-number="3.2.5">
<h3 data-number="3.2.5" class="anchored" data-anchor-id="denoise-the-sequence-dataset"><span class="header-section-number">3.2.5</span> Denoise the sequence dataset</h3>
<p>To have a set of sequences assigned to their corresponding samples does not mean that all sequences are <em>biologically</em> meaningful i.e.&nbsp;some of these sequences can contains PCR and/or sequencing errors, or chimeras.</p>
<section id="tag-the-sequences-for-pcr-errors-sequence-variants" class="level4 unnumbered">
<h4 class="unnumbered anchored" data-anchor-id="tag-the-sequences-for-pcr-errors-sequence-variants">Tag the sequences for PCR errors (sequence variants)</h4>
<p>The <code>obiclean</code> program tags sequence variants as potential error generated during PCR amplification. We ask it to keep the <span class="title-ref">head</span> sequences (<code>-H</code> option) that are sequences which are not variants of another sequence with a count greater than 5% of their own count (<code>-r 0.05</code> option).</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb13"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb13-1"><a href="#cb13-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obiclean</span> <span class="at">-s</span> sample <span class="at">-r</span> 0.05 <span class="at">-H</span> <span class="dt">\</span></span>
<span id="cb13-2"><a href="#cb13-2" aria-hidden="true" tabindex="-1"></a> results/wolf.ali.assigned.simple.fasta <span class="dt">\</span></span>
<span id="cb13-3"><a href="#cb13-3" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/wolf.ali.assigned.simple.clean.fasta </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>One of the sequence records of <code>wolf.ali.assigned.simple.clean.fasta</code> is:</p>
<pre><code>&gt;HELIUM_000100422_612GNAAXX:7:66:4039:8016#0/1_sub[28..127] {"count":17,"merged_sample":{"13a_F730603":17},"obiclean_head":true,"obiclean_headcount":1,"obiclean_internalcount":0,"obi
clean_samplecount":1,"obiclean_singletoncount":0,"obiclean_status":{"13a_F730603":"h"},"obiclean_weight":{"13a_F730603":25}}
ctagccttaaacacaaatagttatgcaaacaaaactattcgccagagtactaccggcaac
agcccaaaactcaaaggacttggcggtgcttcacaccctt</code></pre>
<p>To remove such sequences as much as possible, we first discard rare sequences and then rsequence variants that likely correspond to artifacts.</p>
</section>
<section id="get-some-statistics-about-sequence-counts" class="level4 unnumbered">
<h4 class="unnumbered anchored" data-anchor-id="get-some-statistics-about-sequence-counts">Get some statistics about sequence counts</h4>
<div class="cell">
<div class="sourceCode cell-code" id="cb15"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obicount</span> results/wolf.ali.assigned.simple.clean.fasta</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>time="2023-02-23T18:43:26+01:00" level=info msg="Appending results/wolf.ali.assigned.simple.clean.fasta file\n"
2749 36409 273387</code></pre>
</div>
</div>
<p>The dataset contains <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mn>4313</mn><annotation encoding="application/x-tex">4313</annotation></semantics></math> sequences variant corresponding to 42452 sequence reads. Most of the variants occur only a single time in the complete dataset and are usualy named <em>singletons</em></p>
<div class="cell">
<div class="sourceCode cell-code" id="cb17"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb17-1"><a href="#cb17-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obigrep</span> <span class="at">-p</span> <span class="st">'sequence.Count() == 1'</span> results/wolf.ali.assigned.simple.clean.fasta <span class="dt">\</span></span>
<span id="cb17-2"><a href="#cb17-2" aria-hidden="true" tabindex="-1"></a> <span class="kw">|</span> <span class="ex">obicount</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>time="2023-02-23T18:43:26+01:00" level=info msg="Appending results/wolf.ali.assigned.simple.clean.fasta file\n"
time="2023-02-23T18:43:26+01:00" level=info msg="Reading sequences from stdin in guessed\n"
time="2023-02-23T18:43:26+01:00" level=info msg="On output use JSON headers"
2623 2623 261217</code></pre>
</div>
</div>
<p>In that dataset sigletons corresponds to <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mn>3511</mn><annotation encoding="application/x-tex">3511</annotation></semantics></math> variants.</p>
<p>Using <em>R</em> and the <code>ROBIFastread</code> package able to read headers of the fasta files produced by <em>OBITools</em>, we can get more complete statistics on the distribution of occurrencies.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb19"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb19-1"><a href="#cb19-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ROBIFastread)</span>
<span id="cb19-2"><a href="#cb19-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ggplot2)</span>
<span id="cb19-3"><a href="#cb19-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb19-4"><a href="#cb19-4" aria-hidden="true" tabindex="-1"></a>seqs <span class="ot">&lt;-</span> <span class="fu">read_obifasta</span>(<span class="st">"results/wolf.ali.assigned.simple.clean.fasta"</span>,<span class="at">keys=</span><span class="st">"count"</span>)</span>
<span id="cb19-5"><a href="#cb19-5" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb19-6"><a href="#cb19-6" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> seqs, <span class="at">mapping=</span><span class="fu">aes</span>(<span class="at">x =</span> count)) <span class="sc">+</span></span>
<span id="cb19-7"><a href="#cb19-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_histogram</span>(<span class="at">bins=</span><span class="dv">100</span>) <span class="sc">+</span></span>
<span id="cb19-8"><a href="#cb19-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_sqrt</span>() <span class="sc">+</span></span>
<span id="cb19-9"><a href="#cb19-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_x_sqrt</span>() <span class="sc">+</span></span>
<span id="cb19-10"><a href="#cb19-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_vline</span>(<span class="at">xintercept =</span> <span class="dv">10</span>, <span class="at">col=</span><span class="st">"red"</span>, <span class="at">lty=</span><span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb19-11"><a href="#cb19-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">xlab</span>(<span class="st">"number of occurrencies of a variant"</span>) </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<p><img src="tutorial_files/figure-html/unnamed-chunk-9-1.png" class="img-fluid" width="672"></p>
</div>
</div>
<p>In a similar way it is also possible to plot the distribution of the sequence length.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb20"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb20-1"><a href="#cb20-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> seqs, <span class="at">mapping=</span><span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">nchar</span>(sequence))) <span class="sc">+</span></span>
<span id="cb20-2"><a href="#cb20-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_histogram</span>() <span class="sc">+</span></span>
<span id="cb20-3"><a href="#cb20-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_log10</span>() <span class="sc">+</span></span>
<span id="cb20-4"><a href="#cb20-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_vline</span>(<span class="at">xintercept =</span> <span class="dv">80</span>, <span class="at">col=</span><span class="st">"red"</span>, <span class="at">lty=</span><span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb20-5"><a href="#cb20-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">xlab</span>(<span class="st">"sequence lengths in base pair"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<p><img src="tutorial_files/figure-html/unnamed-chunk-10-1.png" class="img-fluid" width="672"></p>
</div>
</div>
</section>
<section id="keep-only-the-sequences-having-a-count-greater-or-equal-to-10-and-a-length-shorter-than-80-bp" class="level4 unnumbered">
<h4 class="unnumbered anchored" data-anchor-id="keep-only-the-sequences-having-a-count-greater-or-equal-to-10-and-a-length-shorter-than-80-bp">Keep only the sequences having a count greater or equal to 10 and a length shorter than 80 bp</h4>
<p>Based on the previous observation, we set the cut-off for keeping sequences for further analysis to a count of 10. To do this, we use the <code class="interpreted-text" role="doc">obigrep &lt;scripts/obigrep&gt;</code> command. The <code>-p 'count&gt;=10'</code> option means that the <code>python</code> expression :py<code class="interpreted-text" role="mod">count&gt;=10</code> must be evaluated to :py<code class="interpreted-text" role="mod">True</code> for each sequence to be kept. Based on previous knowledge we also remove sequences with a length shorter than 80 bp (option -l) as we know that the amplified 12S-V5 barcode for vertebrates must have a length around 100bp.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb21"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obigrep</span> <span class="at">-l</span> 80 <span class="at">-p</span> <span class="st">'sequence.Count() &gt;= 10'</span> results/wolf.ali.assigned.simple.clean.fasta <span class="dt">\</span></span>
<span id="cb21-2"><a href="#cb21-2" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/wolf.ali.assigned.simple.clean.c10.l80.fasta</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>The first sequence record of <code>results/wolf.ali.assigned.simple.clean.c10.l80.fasta</code> is:</p>
<pre><code>&gt;HELIUM_000100422_612GNAAXX:7:22:2603:18023#0/1_sub[28..127] {"count":12182,"merged_sample":{"15a_F730814":7559,"29a_F260619":4623},"obiclean_head":true,"obiclean_headcount":2,"obiclean_internalcount":0,"obiclean_samplecount":2,"obiclean_singletoncount":0,"obiclean_status":{"15a_F730814":"h","29a_F260619":"h"},"obiclean_weight":{"15a_F730814":9165,"29a_F260619":6275}}
ttagccctaaacacaagtaattaatataacaaaattattcgccagagtactaccggcaat
agcttaaaactcaaaggacttggcggtgctttataccctt</code></pre>
<p>At that time in the data cleanning we have conserved :</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb23"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb23-1"><a href="#cb23-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obicount</span> results/wolf.ali.assigned.simple.clean.c10.l80.fasta</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>time="2023-02-23T18:43:28+01:00" level=info msg="Appending results/wolf.ali.assigned.simple.clean.c10.l80.fasta file\n"
26 31337 2585</code></pre>
</div>
</div>
</section>
</section>
<section id="taxonomic-assignment-of-sequences" class="level3" data-number="3.2.6">
<h3 data-number="3.2.6" class="anchored" data-anchor-id="taxonomic-assignment-of-sequences"><span class="header-section-number">3.2.6</span> Taxonomic assignment of sequences</h3>
<p>Once denoising has been done, the next step in diet analysis is to assign the barcodes to the corresponding species in order to get the complete list of species associated to each sample.</p>
<p>Taxonomic assignment of sequences requires a reference database compiling all possible species to be identified in the sample. Assignment is then done based on sequence comparison between sample sequences and reference sequences.</p>
<section id="download-the-taxonomy" class="level4 unnumbered">
<h4 class="unnumbered anchored" data-anchor-id="download-the-taxonomy">Download the taxonomy</h4>
<p>It is always possible to download the complete taxonomy from NCBI using the following commands.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb25"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb25-1"><a href="#cb25-1" aria-hidden="true" tabindex="-1"></a><span class="fu">mkdir</span> TAXO</span>
<span id="cb25-2"><a href="#cb25-2" aria-hidden="true" tabindex="-1"></a><span class="bu">cd</span> TAXO</span>
<span id="cb25-3"><a href="#cb25-3" aria-hidden="true" tabindex="-1"></a><span class="ex">curl</span> http://ftp.ncbi.nih.gov/pub/taxonomy/taxdump.tar.gz <span class="dt">\</span></span>
<span id="cb25-4"><a href="#cb25-4" aria-hidden="true" tabindex="-1"></a> <span class="kw">|</span> <span class="fu">tar</span> <span class="at">-zxvf</span> <span class="at">-</span></span>
<span id="cb25-5"><a href="#cb25-5" aria-hidden="true" tabindex="-1"></a><span class="bu">cd</span> ..</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>For people have a low speed internet connection, a copy of the <code>taxdump.tar.gz</code> file is provided in the wolf_data directory. The NCBI taxonomy is dayly updated, but the one provided here is ok for running this tutorial.</p>
<p>To build the TAXO directory from the provided <code>taxdump.tar.gz</code>, you need to execute the following commands</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb26"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb26-1"><a href="#cb26-1" aria-hidden="true" tabindex="-1"></a><span class="fu">mkdir</span> TAXO</span>
<span id="cb26-2"><a href="#cb26-2" aria-hidden="true" tabindex="-1"></a><span class="bu">cd</span> TAXO</span>
<span id="cb26-3"><a href="#cb26-3" aria-hidden="true" tabindex="-1"></a><span class="fu">tar</span> zxvf wolf_data/taxdump.tar.gz </span>
<span id="cb26-4"><a href="#cb26-4" aria-hidden="true" tabindex="-1"></a><span class="bu">cd</span> ..</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
</section>
<section id="build-a-reference-database" class="level4 unnumbered">
<h4 class="unnumbered anchored" data-anchor-id="build-a-reference-database">Build a reference database</h4>
<p>One way to build the reference database is to use the <code>obipcr</code> program to simulate a PCR and extract all sequences from a general purpose DNA database such as genbank or EMBL that can be amplified <em>in silico</em> by the two primers (here <strong>TTAGATACCCCACTATGC</strong> and <strong>TAGAACAGGCTCCTCTAG</strong>) used for PCR amplification.</p>
<p>The two steps to build this reference database would then be</p>
<ol type="1">
<li><p>Today, the easiest database to download is <em>Genbank</em>. But this will take you more than a day and occupy more than half a terabyte on your hard drive. In the <code>wolf_data</code> directory, a shell script called <code>download_gb.sh</code> is provided to perform this task. It requires that the programs <code>wget2</code> and <code>curl</code> are available on your computer.</p></li>
<li><p>Use <code>obipcr</code> to simulate amplification and build a reference database based on the putatively amplified barcodes and their recorded taxonomic information.</p></li>
</ol>
<p>As these steps can take a long time (about a day for the download and an hour for the PCR), we already provide the reference database produced by the following commands so you can skip its construction. Note that as the Genbank and taxonomic database evolve frequently, if you run the following commands you may get different results.</p>
<section id="download-the-sequences" class="level5 unnumbered">
<h5 class="unnumbered anchored" data-anchor-id="download-the-sequences">Download the sequences</h5>
<div class="cell">
<div class="sourceCode cell-code" id="cb27"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb27-1"><a href="#cb27-1" aria-hidden="true" tabindex="-1"></a><span class="fu">mkdir</span> genbank</span>
<span id="cb27-2"><a href="#cb27-2" aria-hidden="true" tabindex="-1"></a><span class="bu">cd</span> genbank</span>
<span id="cb27-3"><a href="#cb27-3" aria-hidden="true" tabindex="-1"></a><span class="ex">../wolf_data/install_gb.sh</span></span>
<span id="cb27-4"><a href="#cb27-4" aria-hidden="true" tabindex="-1"></a><span class="bu">cd</span> ..</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>DO NOT RUN THIS COMMAND EXCEPT IF YOU ARE REALLY CONSIENT OF THE TIME AND DISK SPACE REQUIRED.</p>
</section>
<section id="use-obipcr-to-simulate-an-in-silico-pcr" class="level5 unnumbered">
<h5 class="unnumbered anchored" data-anchor-id="use-obipcr-to-simulate-an-in-silico-pcr">Use obipcr to simulate an in silico` PCR</h5>
<div class="cell">
<div class="sourceCode cell-code" id="cb28"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb28-1"><a href="#cb28-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obipcr</span> <span class="at">-t</span> TAXO <span class="at">-e</span> 3 <span class="at">-l</span> 50 <span class="at">-L</span> 150 <span class="dt">\ </span></span>
<span id="cb28-2"><a href="#cb28-2" aria-hidden="true" tabindex="-1"></a> <span class="ex">--forward</span> TTAGATACCCCACTATGC <span class="dt">\</span></span>
<span id="cb28-3"><a href="#cb28-3" aria-hidden="true" tabindex="-1"></a> <span class="at">--reverse</span> TAGAACAGGCTCCTCTAG <span class="dt">\</span></span>
<span id="cb28-4"><a href="#cb28-4" aria-hidden="true" tabindex="-1"></a> <span class="at">--no-order</span> <span class="dt">\</span></span>
<span id="cb28-5"><a href="#cb28-5" aria-hidden="true" tabindex="-1"></a> genbank/Release-251/gb<span class="pp">*</span>.seq.gz</span>
<span id="cb28-6"><a href="#cb28-6" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/v05.pcr.fasta</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>Note that the primers must be in the same order both in <code>wolf_diet_ngsfilter.txt</code> and in the <code>obipcr</code> command. The part of the path indicating the <em>Genbank</em> release can change. Please check in your genbank directory the exact name of your release.</p>
</section>
<section id="clean-the-database" class="level5 unnumbered">
<h5 class="unnumbered anchored" data-anchor-id="clean-the-database">Clean the database</h5>
<ol type="1">
<li>filter sequences so that they have a good taxonomic description at the species, genus, and family levels (<code>obigrep</code> command command below).</li>
<li>remove redundant sequences (<code>obiuniq</code> command below).</li>
<li>ensure that the dereplicated sequences have a taxid at the family level (<code>obigrep</code> command below).</li>
<li>ensure that sequences each have a unique identification (<code>obiannotate</code> command below)</li>
</ol>
<div class="cell">
<div class="sourceCode cell-code" id="cb29"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb29-1"><a href="#cb29-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obigrep</span> <span class="at">-t</span> TAXO <span class="dt">\</span></span>
<span id="cb29-2"><a href="#cb29-2" aria-hidden="true" tabindex="-1"></a> <span class="at">--require-rank</span> species <span class="dt">\</span></span>
<span id="cb29-3"><a href="#cb29-3" aria-hidden="true" tabindex="-1"></a> <span class="at">--require-rank</span> genus <span class="dt">\</span></span>
<span id="cb29-4"><a href="#cb29-4" aria-hidden="true" tabindex="-1"></a> <span class="at">--require-rank</span> family <span class="dt">\</span></span>
<span id="cb29-5"><a href="#cb29-5" aria-hidden="true" tabindex="-1"></a> results/v05.ecopcr <span class="op">&gt;</span> results/v05_clean.fasta</span>
<span id="cb29-6"><a href="#cb29-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb29-7"><a href="#cb29-7" aria-hidden="true" tabindex="-1"></a><span class="ex">obiuniq</span> <span class="at">-c</span> taxid <span class="dt">\</span></span>
<span id="cb29-8"><a href="#cb29-8" aria-hidden="true" tabindex="-1"></a> results/v05_clean.fasta <span class="dt">\</span></span>
<span id="cb29-9"><a href="#cb29-9" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/v05_clean_uniq.fasta</span>
<span id="cb29-10"><a href="#cb29-10" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb29-11"><a href="#cb29-11" aria-hidden="true" tabindex="-1"></a><span class="ex">obirefidx</span> <span class="at">-t</span> TAXO results/v05_clean_uniq.fasta <span class="dt">\</span></span>
<span id="cb29-12"><a href="#cb29-12" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/v05_clean_uniq.indexed.fasta</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<div class="warning">
<div class="title">
<p>Warning</p>
</div>
<p>From now on, for the sake of clarity, the following commands will use the filenames of the files provided with the tutorial. If you decided to run the last steps and use the files you have produced, you'll have to use <code>results/v05_clean_uniq.indexed.fasta</code> instead of <code>wolf_data/db_v05_r117.indexed.fasta</code>.</p>
</div>
</section>
</section>
</section>
<section id="assign-each-sequence-to-a-taxon" class="level3" data-number="3.2.7">
<h3 data-number="3.2.7" class="anchored" data-anchor-id="assign-each-sequence-to-a-taxon"><span class="header-section-number">3.2.7</span> Assign each sequence to a taxon</h3>
<p>Once the reference database is built, taxonomic assignment can be carried out using the <code>obitag</code> command.</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb30"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb30-1"><a href="#cb30-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obitag</span> <span class="at">-t</span> TAXO <span class="at">-R</span> wolf_data/db_v05_r117.indexed.fasta <span class="dt">\</span></span>
<span id="cb30-2"><a href="#cb30-2" aria-hidden="true" tabindex="-1"></a> results/wolf.ali.assigned.simple.clean.c10.l80.fasta <span class="dt">\</span></span>
<span id="cb30-3"><a href="#cb30-3" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/wolf.ali.assigned.simple.clean.c10.l80.taxo.fasta</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>The <code>obitag</code> adds several attributes in the sequence record header, among them:</p>
<ul>
<li>obitag_bestmatch=ACCESSION where ACCESSION is the id of hte sequence in the reference database that best aligns to the query sequence;</li>
<li>obitag_bestid=FLOAT where FLOAT*100 is the percentage of identity between the best match sequence and the query sequence;</li>
<li>taxid=TAXID where TAXID is the final assignation of the sequence by <code>obitag</code></li>
<li>scientific_name=NAME where NAME is the scientific name of the assigned taxid.</li>
</ul>
<p>The first sequence record of <code>wolf.ali.assigned.simple.clean.c10.l80.taxo.fasta</code> is:</p>
<div class="sourceCode" id="cb31"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb31-1"><a href="#cb31-1" aria-hidden="true" tabindex="-1"></a><span class="op">&gt;</span>HELIUM_000100422_612GNAAXX:7:81:18704:12346#0/1_sub[28..126] <span class="dt">{</span><span class="st">"count"</span><span class="dt">:88</span><span class="op">,</span><span class="st">"merged_sample"</span><span class="dt">:{</span><span class="st">"26a_F040644"</span><span class="dt">:88}</span><span class="op">,</span><span class="st">"obiclean_head"</span><span class="dt">:true</span><span class="op">,</span><span class="st">"obiclean_headcount"</span><span class="dt">:1</span><span class="op">,</span><span class="st">"obiclean_internalcount"</span><span class="dt">:0</span><span class="op">,</span><span class="st">"obiclean_samplecount"</span><span class="dt">:1</span><span class="op">,</span><span class="st">"obiclean_singletoncount"</span><span class="dt">:0</span><span class="op">,</span><span class="st">"obiclean_status"</span><span class="dt">:{</span><span class="st">"26a_F040644"</span><span class="dt">:</span><span class="st">"h"</span><span class="dt">}</span><span class="op">,</span><span class="st">"obiclean_weight"</span><span class="dt">:{</span><span class="st">"26a_F040644"</span><span class="dt">:208}</span><span class="op">,</span><span class="st">"obitag_bestid"</span><span class="dt">:0.9207920792079208</span><span class="op">,</span><span class="st">"obitag_bestmatch"</span><span class="dt">:</span><span class="st">"AY769263"</span><span class="op">,</span><span class="st">"obitag_difference"</span><span class="dt">:8</span><span class="op">,</span><span class="st">"obitag_match_count"</span><span class="dt">:1</span><span class="op">,</span><span class="st">"obitag_rank"</span><span class="dt">:</span><span class="st">"clade"</span><span class="op">,</span><span class="st">"scientific_name"</span><span class="dt">:</span><span class="st">"Boreoeutheria"</span><span class="op">,</span><span class="st">"taxid"</span><span class="dt">:1437010}</span></span>
<span id="cb31-2"><a href="#cb31-2" aria-hidden="true" tabindex="-1"></a><span class="ex">ttagccctaaacataaacattcaataaacaagaatgttcgccagaggactactagcaata</span></span>
<span id="cb31-3"><a href="#cb31-3" aria-hidden="true" tabindex="-1"></a><span class="ex">gcttaaaactcaaaggacttggcggtgctttatatccct</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</section>
<section id="generate-the-final-result-table" class="level3" data-number="3.2.8">
<h3 data-number="3.2.8" class="anchored" data-anchor-id="generate-the-final-result-table"><span class="header-section-number">3.2.8</span> Generate the final result table</h3>
<p>Some unuseful attributes can be removed at this stage.</p>
<ul>
<li>obiclean_head</li>
<li>obiclean_headcount</li>
<li>obiclean_internalcount</li>
<li>obiclean_samplecount</li>
<li>obiclean_singletoncount</li>
</ul>
<div class="cell">
<div class="sourceCode cell-code" id="cb32"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb32-1"><a href="#cb32-1" aria-hidden="true" tabindex="-1"></a><span class="ex">obiannotate</span> <span class="at">--delete-tag</span><span class="op">=</span>obiclean_head <span class="dt">\</span></span>
<span id="cb32-2"><a href="#cb32-2" aria-hidden="true" tabindex="-1"></a> <span class="at">--delete-tag</span><span class="op">=</span>obiclean_headcount <span class="dt">\</span></span>
<span id="cb32-3"><a href="#cb32-3" aria-hidden="true" tabindex="-1"></a> <span class="at">--delete-tag</span><span class="op">=</span>obiclean_internalcount <span class="dt">\</span></span>
<span id="cb32-4"><a href="#cb32-4" aria-hidden="true" tabindex="-1"></a> <span class="at">--delete-tag</span><span class="op">=</span>obiclean_samplecount <span class="dt">\</span></span>
<span id="cb32-5"><a href="#cb32-5" aria-hidden="true" tabindex="-1"></a> <span class="at">--delete-tag</span><span class="op">=</span>obiclean_singletoncount <span class="dt">\</span></span>
<span id="cb32-6"><a href="#cb32-6" aria-hidden="true" tabindex="-1"></a> results/wolf.ali.assigned.simple.clean.c10.l80.taxo.fasta <span class="dt">\</span></span>
<span id="cb32-7"><a href="#cb32-7" aria-hidden="true" tabindex="-1"></a> <span class="op">&gt;</span> results/wolf.ali.assigned.simple.clean.c10.l80.taxo.ann.fasta</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>The first sequence record of <code>wolf.ali.assigned.simple.c10.l80.clean.taxo.ann.fasta</code> is then:</p>
<pre><code>&gt;HELIUM_000100422_612GNAAXX:7:84:16335:5083#0/1_sub[28..126] {"count":96,"merged_sample":{"26a_F040644":11,"29a_F260619":85},"obiclean_status":{"26a_F040644":"s","29a_F260619":"h"},"obiclean_weight":{"26a_F040644":14,"29a_F260619":110},"obitag_bestid":0.9595959595959596,"obitag_bestmatch":"AC187326","obitag_difference":4,"obitag_match_count":1,"obitag_rank":"subspecies","scientific_name":"Canis lupus familiaris","taxid":9615}
ttagccctaaacataagctattccataacaaaataattcgccagagaactactagcaaca
gattaaacctcaaaggacttggcagtgctttatacccct</code></pre>
</section>
<section id="looking-at-the-data-in-r" class="level3" data-number="3.2.9">
<h3 data-number="3.2.9" class="anchored" data-anchor-id="looking-at-the-data-in-r"><span class="header-section-number">3.2.9</span> Looking at the data in R</h3>
<div class="cell">
<div class="sourceCode cell-code" id="cb34"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb34-1"><a href="#cb34-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ROBIFastread)</span>
<span id="cb34-2"><a href="#cb34-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(vegan)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stderr">
<pre><code>Le chargement a nécessité le package : permute</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Le chargement a nécessité le package : lattice</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>This is vegan 2.6-4</code></pre>
</div>
<div class="sourceCode cell-code" id="cb38"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb38-1"><a href="#cb38-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(magrittr)</span>
<span id="cb38-2"><a href="#cb38-2" aria-hidden="true" tabindex="-1"></a> </span>
<span id="cb38-3"><a href="#cb38-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb38-4"><a href="#cb38-4" aria-hidden="true" tabindex="-1"></a>diet_data <span class="ot">&lt;-</span> <span class="fu">read_obifasta</span>(<span class="st">"results/wolf.ali.assigned.simple.clean.c10.l80.taxo.fasta"</span>) </span>
<span id="cb38-5"><a href="#cb38-5" aria-hidden="true" tabindex="-1"></a>diet_data <span class="sc">%&lt;&gt;%</span> <span class="fu">extract_features</span>(<span class="st">"obitag_bestmatch"</span>,<span class="st">"obitag_rank"</span>,<span class="st">"scientific_name"</span>,<span class="st">'taxid'</span>)</span>
<span id="cb38-6"><a href="#cb38-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb38-7"><a href="#cb38-7" aria-hidden="true" tabindex="-1"></a>diet_tab <span class="ot">&lt;-</span> <span class="fu">extract_readcount</span>(diet_data,<span class="at">key=</span><span class="st">"obiclean_weight"</span>)</span>
<span id="cb38-8"><a href="#cb38-8" aria-hidden="true" tabindex="-1"></a>diet_tab</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>4 x 26 sparse Matrix of class "dgCMatrix"</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code> [[ suppressing 26 column names 'HELIUM_000100422_612GNAAXX:7:72:17638:8081#0/1_sub[28..126]', 'HELIUM_000100422_612GNAAXX:7:17:3675:13316#0/1_sub[28..126]', 'HELIUM_000100422_612GNAAXX:7:58:11419:17203#0/1_sub[28..126]' ... ]]</code></pre>
</div>
<div class="cell-output cell-output-stdout">
<pre><code>
26a_F040644 15 17 481 . . . 208 . . . . . 14 31 . . 43 52 14 72
13a_F730603 . . 19 1 . 15 . 22 . . 20 25 . . . 8409 . . . .
15a_F730814 . . 5 . . . . . . . . . . . . . . . . .
29a_F260619 . . 1 13 25 . . . 16 44 . . . . 391 . . . 110 .
26a_F040644 88 18 . . 12830 .
13a_F730603 . . 9 . . .
15a_F730814 . . 4 . . 9165
29a_F260619 . . . 353 . 5884</code></pre>
</div>
</div>
<dl>
<dt>This file contains 26 sequences. You can deduce the diet of each sample:</dt>
<dd>
<ul>
<li>13a_F730603: Cervus elaphus</li>
<li>15a_F730814: Capreolus capreolus</li>
<li>26a_F040644: Marmota sp. (according to the location, it is Marmota marmota)</li>
<li>29a_F260619: Capreolus capreolus</li>
</ul>
</dd>
</dl>
<p>Note that we also obtained a few wolf sequences although a wolf-blocking oligonucleotide was used.</p>
<div id="refs" class="references csl-bib-body hanging-indent" role="doc-bibliography" style="display: none">
<div id="ref-Riaz2011-gn" class="csl-entry" role="doc-biblioentry">
Riaz, Tiayyba, Wasim Shehzad, Alain Viari, François Pompanon, Pierre Taberlet, and Eric Coissac. 2011. <span>“<span class="nocase">ecoPrimers: inference of new DNA barcode markers from whole genome sequence analysis</span>.”</span> <em>Nucleic Acids Research</em> 39 (21): e145. <a href="https://doi.org/10.1093/nar/gkr732">https://doi.org/10.1093/nar/gkr732</a>.
</div>
<div id="ref-Seguritan2001-tg" class="csl-entry" role="doc-biblioentry">
Seguritan, V, and F Rohwer. 2001. <span>“<span class="nocase">FastGroup: a program to dereplicate libraries of 16S rDNA sequences</span>.”</span> <em>BMC Bioinformatics</em> 2 (October): 9. <a href="https://doi.org/10.1186/1471-2105-2-9">https://doi.org/10.1186/1471-2105-2-9</a>.
</div>
<div id="ref-Shehzad2012-pn" class="csl-entry" role="doc-biblioentry">
Shehzad, Wasim, Tiayyba Riaz, Muhammad A Nawaz, Christian Miquel, Carole Poillot, Safdar A Shah, Francois Pompanon, Eric Coissac, and Pierre Taberlet. 2012. <span>“<span class="nocase">Carnivore diet analysis based on next-generation sequencing: Application to the leopard cat (Prionailurus bengalensis) in Pakistan</span>.”</span> <em>Molecular Ecology</em> 21 (8): 1951–65. <a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-294X.2011.05424.x">https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-294X.2011.05424.x</a>.
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