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<article>
  <header>
    <h1>DNA Chisel - a versatile sequence optimizer</h1>
  </header>
  <nav>
    <p class="center">
      <a href="/david/" title="Aller à l’accueil"><svg class="icon icon-home">
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      <a href="https://edinburgh-genome-foundry.github.io/DnaChisel/" title="Lien vers le contenu original">Source originale</a>
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  <hr>
  <p>DNA Chisel (complete documentation <a class="reference external" href="https://edinburgh-genome-foundry.github.io/DnaChisel/">here</a>)
is a Python library for optimizing DNA sequences with respect to a set of
constraints and optimization objectives. It comes with over 15 classes of
sequence specifications which can be composed to, for instance, codon-optimize
genes, meet the  constraints of a commercial DNA provider, avoid homologies
between sequences, tune GC content, or all of this at once!</p>

<p>DNA Chisel also allows users to define their own specifications in Python,
making the library suitable for a large range of automated sequence design
applications, and complex custom design projects. It can be used as a Python
library, a command-line interface, or a <a class="reference external" href="https://cuba.genomefoundry.org/sculpt_a_sequence">web application</a>.</p>

<div class="section" id="example-of-use">
<h2>Example of use</h2>
<div class="section" id="defining-a-problem-via-scripts">
<h3>Defining a problem via scripts</h3>
<p>In this basic example we generate a random sequence and optimize it so that</p>
<ul class="simple">
<li><p>It will be rid of BsaI sites.</p></li>
<li><p>GC content will be between 30% and 70% on every 50bp window.</p></li>
<li><p>The reading frame at position 500-1400 will be codon-optimized for <em>E. coli</em>.</p></li>
</ul>
<p>Here is the code to achieve that:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">dnachisel</span> <span class="kn">import</span> <span class="o">*</span>

<span class="c1"># DEFINE THE OPTIMIZATION PROBLEM</span>

<span class="n">problem</span> <span class="o">=</span> <span class="n">DnaOptimizationProblem</span><span class="p">(</span>
    <span class="n">sequence</span><span class="o">=</span><span class="n">random_dna_sequence</span><span class="p">(</span><span class="mi">10000</span><span class="p">),</span>
    <span class="n">constraints</span><span class="o">=</span><span class="p">[</span>
        <span class="n">AvoidPattern</span><span class="p">(</span><span class="s2">"BsaI_site"</span><span class="p">),</span>
        <span class="n">EnforceGCContent</span><span class="p">(</span><span class="n">mini</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">maxi</span><span class="o">=</span><span class="mf">0.7</span><span class="p">,</span> <span class="n">window</span><span class="o">=</span><span class="mi">50</span><span class="p">),</span>
        <span class="n">EnforceTranslation</span><span class="p">(</span><span class="n">location</span><span class="o">=</span><span class="p">(</span><span class="mi">500</span><span class="p">,</span> <span class="mi">1400</span><span class="p">))</span>
    <span class="p">],</span>
    <span class="n">objectives</span><span class="o">=</span><span class="p">[</span><span class="n">CodonOptimize</span><span class="p">(</span><span class="n">species</span><span class="o">=</span><span class="s1">'e_coli'</span><span class="p">,</span> <span class="n">location</span><span class="o">=</span><span class="p">(</span><span class="mi">500</span><span class="p">,</span> <span class="mi">1400</span><span class="p">))]</span>
<span class="p">)</span>

<span class="c1"># SOLVE THE CONSTRAINTS, OPTIMIZE WITH RESPECT TO THE OBJECTIVE</span>

<span class="n">problem</span><span class="o">.</span><span class="n">resolve_constraints</span><span class="p">()</span>
<span class="n">problem</span><span class="o">.</span><span class="n">optimize</span><span class="p">()</span>

<span class="c1"># PRINT SUMMARIES TO CHECK THAT CONSTRAINTS PASS</span>

<span class="k">print</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">constraints_text_summary</span><span class="p">())</span>
<span class="k">print</span><span class="p">(</span><span class="n">problem</span><span class="o">.</span><span class="n">objectives_text_summary</span><span class="p">())</span>
</pre></div>
</div>
<p>DnaChisel implements advanced constraints such as the preservation of coding
sequences,  or the inclusion or exclusion of advanced patterns (see
<a class="reference external" href="https://edinburgh-genome-foundry.github.io/DnaChisel/ref/builtin_specifications.html">this page</a>
for an overview of available specifications), but it is also easy to implement
our own constraints and objectives as subclasses of <code class="docutils literal notranslate"><span class="pre">dnachisel.Specification</span></code>.</p>
</div>
<div class="section" id="defining-a-problem-via-genbank-features">
<h3>Defining a problem via Genbank features</h3>
<p>You can also define a problem by annotating directly a Genbank as follows:</p>
<p align="center">
<img alt="report" title="report" src="https://raw.githubusercontent.com/Edinburgh-Genome-Foundry/DnaChisel/master/docs/_static/images/example_sequence_map.png">
<br><br>
</p><p>I this record:</p>
<ul class="simple">
<li><p>Constraints (colored in blue in the illustration) are features of type
<code class="docutils literal notranslate"><span class="pre">misc_feature</span></code> with a prefix <code class="docutils literal notranslate"><span class="pre">@</span></code> followed
by the name of the constraints and its parameters, which are the same as in
python scripts.</p></li>
<li><p>Optimization objectives (colored in yellow in the illustration) are features
of type <code class="docutils literal notranslate"><span class="pre">misc_feature</span></code> with a prefix <code class="docutils literal notranslate"><span class="pre">~</span></code> followed by the name of the
constraints and its parameters.</p></li>
</ul>
<p>The file can be directly fed to the <a class="reference external" href="https://cuba.genomefoundry.org/sculpt_a_sequence">web app</a>
or processed via the command line interface:</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span><span class="c1"># Output the result to "optimized_record.gb"</span>
dnachisel annotated_record.gb optimized_record.gb
</pre></div>
</div>
<p>Or via a Python script:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">dnachisel</span> <span class="kn">import</span> <span class="n">DnaOptimizationProblem</span>
<span class="n">problem</span> <span class="o">=</span> <span class="n">DnaOptimizationProblem</span><span class="o">.</span><span class="n">from_record</span><span class="p">(</span><span class="s2">"my_record.gb"</span><span class="p">)</span>
<span class="n">problem</span><span class="o">.</span><span class="n">optimize_with_report</span><span class="p">(</span><span class="n">target</span><span class="o">=</span><span class="s2">"report.zip"</span><span class="p">)</span>
</pre></div>
</div>
<p>By default, only the built-in specifications of DnaChisel can be used in the
annotations, however it is easy to add your own specifications to the Genbank
parser, and build applications supporting custom specifications on top of
DnaChisel.</p>
</div>
<div class="section" id="reports">
<h3>Reports</h3>
<p>DnaChisel also implements features for verification and troubleshooting. For
instance by generating optimization reports:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">problem</span><span class="o">.</span><span class="n">optimize_with_report</span><span class="p">(</span><span class="n">target</span><span class="o">=</span><span class="s2">"report.zip"</span><span class="p">)</span>
</pre></div>
</div>
<p>Here is an example of summary report:</p>
<p align="center">
<img alt="report" title="report" src="https://raw.githubusercontent.com/Edinburgh-Genome-Foundry/DnaChisel/master/docs/_static/images/report_screenshot.png">
<br><br>
</p></div>
</div>

<div class="section" id="how-it-works">
<h2>How it works</h2>
<p>DnaChisel hunts down every constraint breach and suboptimal region by
recreating local version of the problem around these regions. Each type of
constraint can be locally <em>reduced</em> and solved in its own way, to ensure fast
and reliable resolution.</p>
<p>Below is an animation of the algorithm in action:</p>
<p align="center">
<img alt="DNA Chisel algorithm" title="DNA Chisel" src="https://raw.githubusercontent.com/Edinburgh-Genome-Foundry/DnaChisel/master/docs/_static/images/dnachisel_algorithm.gif">
<br>
</p></div>

<div class="section" id="installation">
<h2>Installation</h2>
<p>You can install DnaChisel through PIP:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">sudo</span> <span class="n">pip</span> <span class="n">install</span> <span class="n">dnachisel</span><span class="p">[</span><span class="n">reports</span><span class="p">]</span>
</pre></div>
</div>
<p>The <code class="docutils literal notranslate"><span class="pre">[reports]</span></code> suffix will install some heavier libraries
(Matplotlib, PDF reports, sequenticon) for report generation,
you can omit it if you just want to use DNA chisel to edit sequences and
generate genbanks (for any interactive use, reports are highly recommended).</p>
<p>Alternatively, you can unzip the sources in a folder and type</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">sudo</span> <span class="n">python</span> <span class="n">setup</span><span class="o">.</span><span class="n">py</span> <span class="n">install</span>
</pre></div>
</div>
<p>Optionally, also install Bowtie to be able to use <code class="docutils literal notranslate"><span class="pre">AvoidMatches</span></code> (which
removes short homologies with existing genomes). On Ubuntu:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">sudo</span> <span class="n">apt</span><span class="o">-</span><span class="n">get</span> <span class="n">install</span> <span class="n">bowtie</span>
</pre></div>
</div>
</div>

<div class="section" id="more-biology-software">
<h2>More biology software</h2>
<a class="reference external image-reference" href="https://edinburgh-genome-foundry.github.io/"><img alt="https://raw.githubusercontent.com/Edinburgh-Genome-Foundry/Edinburgh-Genome-Foundry.github.io/master/static/imgs/logos/egf-codon-horizontal.png" src="https://raw.githubusercontent.com/Edinburgh-Genome-Foundry/Edinburgh-Genome-Foundry.github.io/master/static/imgs/logos/egf-codon-horizontal.png"></a>
<p>DNA Chisel is part of the <a class="reference external" href="https://edinburgh-genome-foundry.github.io/">EGF Codons</a> synthetic biology software suite for DNA design, manufacturing and validation.</p>
</article>


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