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    <title>16s-Sequencing on Living_Systems</title>
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    <lastBuildDate>Fri, 25 Sep 2026 16:47:12 +0200</lastBuildDate>
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      <title>The lr:hq minimap2 profile speeds up Emu by an order of magnitude for 16S data</title>
      <link>https://livingsystems.cc/posts/lrhq-speeds-up-alignment-in-emu/</link>
      <pubDate>Fri, 25 Sep 2026 16:47:12 +0200</pubDate>
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      <description>&lt;p&gt;&lt;a href=&#34;https://github.com/treangenlab/emu&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;Emu&lt;/a&gt;&#xA; is a popular read classifier and&#xA;abundance estimator for 16S sequencing (sequencing of the 16S ribosomal RNA&#xA;subunit, which is a common method for determining the abundance of bacteria in&#xA;a sample, typically at the granularity of genus and/or species). We use it&#xA;as part of the &lt;a href=&#34;https://github.com/genomic-medicine-sweden/trana&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;Trana pipeline&lt;/a&gt;&#xA; for a selection of&#xA;16S sequencing samples at the Karolinska Hospital.&lt;/p&gt;&#xA;&lt;p&gt;Emu was specifically created to account for the generally lower accuracy of&#xA;Oxford Nanopore (ONT) reads. Although this situation has drastically improved in&#xA;recent years, with new flow cells and basecalling models, the error rate still&#xA;typically remains around 1%, which, especially for a very sensitive analysis&#xA;like 16S sequencing, is significant.&lt;/p&gt;</description>
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