<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>

CC BY-SA 3.0
2017-08-24T00:01:39.523Z
2017-08-24T00:01:39.523Z
burger
<p>There seems to be some confusion here. </p>

<p>For the first stage of the Canu pipeline (read correction), i think the parameter to use is <strong>rawErrorRate</strong>. </p>

<p>From the docs: </p>

<p><strong>rawErrorRate</strong>  The allowed difference in an overlap between two uncorrected reads, expressed as fraction error. Sets corOvlErrorRate and corErrorRate. The rawErrorRate typically does not need to be modified. It might need to be increased if very early reads are being assembled. The default is 0.300 For PacBio reads, and 0.500 for Nanopore reads.</p>

<p>I think that <strong>correctedErrorRate</strong> is what you use at the next stages of the pipeline (trimming and assemble).</p>

CC BY-SA 3.0
2017-09-08T08:07:38.117Z
2017-09-08T08:07:38.117Z
dkainer
<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>

<nanopore><canu><quality-control>
Error rate setting in Canu error correction
# Error rate setting in Canu error correction

(Asked by: username_0 on 2017-08-23)

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?

**Tags:** nanopore, canu, quality-control

---

## 2 answers

### Answer by username_1 on 2017-08-24. Score: 3

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](http://canu.readthedocs.io/en/latest/parameter-reference.html):

> 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](https://github.com/marbl/canu/issues/109)):

> 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.


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### Answer by username_2 on 2017-09-08. Score: 0

There seems to be some confusion here.

For the first stage of the Canu pipeline (read correction), i think the parameter to use is **rawErrorRate**.

From the docs:

**rawErrorRate** The allowed difference in an overlap between two uncorrected reads, expressed as fraction error. Sets corOvlErrorRate and corErrorRate. The rawErrorRate typically does not need to be modified. It might need to be increased if very early reads are being assembled. The default is 0.300 For PacBio reads, and 0.500 for Nanopore reads.

I think that **correctedErrorRate** is what you use at the next stages of the pipeline (trimming and assemble).


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