text: user1364: I want to use Canu to correct my nanopore long read (version: MinION R9.5), but I am not quite sure how to set the correctErrorRate. Should I follow the Canu manual (Nanopore R7 2D and Nanopore R9 1D Increase the maximum allowed difference in overlaps from the default of 14.4% to 22.5% with correctedErrorRate=0.225), or you guys have a better option? 
  
  user35: It's generally a good idea to trust the "official" suggestions. You can also adjust the error rate based on coverage according to parameter reference:
  
  For low coverage datasets (less than 30X), we recommend increasing
    correctedErrorRate slightly, by 1% or so.
  For high-coverage datasets (more than 60X), we recommend decreasing
    correctedErrorRate slighly, by 1% or so.
  Raising the correctedErrorRate will increase run time. Likewise,
    decreasing correctedErrorRate will decrease run time, at the risk of
    missing overlaps and fracturing the assembly.
  
  That being said, the sequencing quality can vary from between libraries or flow cells. The error rate is not a constant.
  According to the developer (full thread):
  
  if you want to assemble 1D data or have a bad run, it is possible you
    would need to increase the error rate. You could run with a high error
    rate (0.1) and look at the distribution of overlap error rates in the
    unitig step to look for a peak in the distribution. If you have a near
    neighbor you could also map the corrected reads to it and estimate the
    residual error that way.
  
  
original_text: 1364: <p>I want to use Canu to correct my nanopore long read (version: MinION R9.5), but I am not quite sure how to set the correctErrorRate. Should I follow the Canu manual (Nanopore R7 2D and Nanopore R9 1D Increase the maximum allowed difference in overlaps from the default of 14.4% to 22.5% with correctedErrorRate=0.225), or you guys have a better option? </p>
   35: <p>It's generally a good idea to trust the "official" suggestions. You can also adjust the error rate based on coverage according to <a href="http://canu.readthedocs.io/en/latest/parameter-reference.html" rel="nofollow noreferrer">parameter reference</a>:</p>
  
  <blockquote>
    <p>For low coverage datasets (less than 30X), we recommend increasing
    correctedErrorRate slightly, by 1% or so.</p>
    
    <p>For high-coverage datasets (more than 60X), we recommend decreasing
    correctedErrorRate slighly, by 1% or so.</p>
    
    <p>Raising the correctedErrorRate will increase run time. Likewise,
    decreasing correctedErrorRate will decrease run time, at the risk of
    missing overlaps and fracturing the assembly.</p>
  </blockquote>
  
  <p>That being said, the sequencing quality can vary from between libraries or flow cells. The error rate is not a constant.</p>
  
  <p>According to the developer (<a href="https://github.com/marbl/canu/issues/109" rel="nofollow noreferrer">full thread</a>):</p>
  
  <blockquote>
    <p>if you want to assemble 1D data or have a bad run, it is possible you
    would need to increase the error rate. You could run with a high error
    rate (0.1) and look at the distribution of overlap error rates in the
    unitig step to look for a peak in the distribution. If you have a near
    neighbor you could also map the corrected reads to it and estimate the
    residual error that way.</p>
  </blockquote>
  