<p>I'd recommend using Canu for correction rather than Pilon, because it has a component that is specifically designed for read-level correction. The newest version of Canu (v1.7) will track <em>all</em> reads through the correction and assembly process:</p>

<blockquote>
  <p>Ensure that every raw read is either corrected or used as evidence for correcting some other raw read. This serves to rescue short plasmids in high coverage datasets, and it is no longer necessary to set corOutCoverage to achieve the same result.</p>
</blockquote>

<p>More details <a href="https://github.com/marbl/canu/releases/tag/v1.7" rel="nofollow noreferrer">here</a>.</p>

CC BY-SA 3.0
2018-03-14T21:30:02.287Z
2018-03-14T21:30:02.287Z
gringer
<p>I have pacbio Sequel data at 50 x coverage for a strain of animal. I would like to find structural variants compared to the reference genome sequence. At the moment, I align my reads to the reference genome using <a href="https://github.com/philres/ngmlr" rel="nofollow noreferrer">NGM-LR</a> and call the variants using <a href="https://github.com/fritzsedlazeck/Sniffles" rel="nofollow noreferrer">Sniffles</a>. The resulting VCF file contains variants that are well supported in a visual inspection in IGV as well as some more questionable variants (especially larger events). I have used the reads corrected by <a href="http://canu.readthedocs.io/en/latest/" rel="nofollow noreferrer">canu</a> for alignment. I think it splits my long reads into very long reads and not-so-long reads and uses the shorter reads to correct the longer reads. However, in IGV, my reads still have a considerable number of mistakes compared to the reference. I was wondering if it is OK to use <a href="https://github.com/broadinstitute/pilon" rel="nofollow noreferrer">pilon</a> to polish my long reads with some Illumina data from the same sample? The main purpose of pilon is to correct assemblies but I was wondering if it can be used to correct subreads from PacBio sequencing?</p>

CC BY-SA 3.0
2018-04-14T16:59:52.927Z
I have no links to support it, so I will give just a comment. People say that using short reads to correct have always troubles with misplacing them due to repetitive content. I suspect that structural variants could be frequently duplicated and therefore problematic for error correction with short reads and I expect that with 50x you will get better error correction using just the long reads.
Kamil S Jaron
<variant-calling><long-reads><structural-variation><pacbio><read-correction>
Can I pilon-polish long reads with Illumina short reads to improve structural variant detection?
# Can I pilon-polish long reads with Illumina short reads to improve structural variant detection?

(Asked by: username_0 on 2018-03-09)

I have pacbio Sequel data at 50 x coverage for a strain of animal. I would like to find structural variants compared to the reference genome sequence. At the moment, I align my reads to the reference genome using [NGM-LR](https://github.com/philres/ngmlr) and call the variants using [Sniffles](https://github.com/fritzsedlazeck/Sniffles). The resulting VCF file contains variants that are well supported in a visual inspection in IGV as well as some more questionable variants (especially larger events). I have used the reads corrected by [canu](http://canu.readthedocs.io/en/latest/) for alignment. I think it splits my long reads into very long reads and not-so-long reads and uses the shorter reads to correct the longer reads. However, in IGV, my reads still have a considerable number of mistakes compared to the reference. I was wondering if it is OK to use [pilon](https://github.com/broadinstitute/pilon) to polish my long reads with some Illumina data from the same sample? The main purpose of pilon is to correct assemblies but I was wondering if it can be used to correct subreads from PacBio sequencing?

**Tags:** variant-calling, long-reads, structural-variation, pacbio, read-correction
> **Comments:**
> **username_1**: I have no links to support it, so I will give just a comment. People say that using short reads to correct have always troubles with misplacing them due to repetitive content. I suspect that structural variants could be frequently duplicated and therefore problematic for error correction with short reads and I expect that with 50x you will get better error correction using just the long reads.  

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## 1 answers

### Answer by username_2 on 2018-03-14. Score: 2 | Accepted answer

I'd recommend using Canu for correction rather than Pilon, because it has a component that is specifically designed for read-level correction. The newest version of Canu (v1.7) will track *all* reads through the correction and assembly process:

> Ensure that every raw read is either corrected or used as evidence for correcting some other raw read. This serves to rescue short plasmids in high coverage datasets, and it is no longer necessary to set corOutCoverage to achieve the same result.

More details [here](https://github.com/marbl/canu/releases/tag/v1.7).


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