Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

is daccordcontig suitable for the error correction with ONT data? #12

Open
bitcometz opened this issue Dec 10, 2018 · 3 comments
Open

Comments

@bitcometz
Copy link

Hello,
I have used the daccordcontig to do the error correction of scaffolds with PacBio reads, and it works really well, for example, the BUSCO assessment usually achieve above 90%.
However, when I used the daccordcontig to do the error correction with ONT(Oxford Nanopore technologies) data, it seems that it did not work well because the BUSCO assessment is about 50%, which was even lower than the Racon.
I think it is abnormal. Maybe there is something wrong. Can you give me some advice? Thanks!!!

Best

@gt1
Copy link
Owner

gt1 commented Dec 11, 2018

Hi,

I have not run any ONT data through daccord recently. I hope I'll find the time to do so soon.

Best

@bitcometz
Copy link
Author

Thanks! Looking forward to your good news!

Best

@HaploKit
Copy link

Hi, German Tischler.

I also found a similar situation in my cases (Daccord performs much worse(10 times) on ONT reads, compared with PacBio reads, though Daccord performs really well on Pacbio reads error correction.

Have you already tested ONT data on your own? I do want to use Daccord in my applications, but could you please tell me what could be the possible reasons that it performs much worse on ONT data? By the way, may I ask why daccord is not published in a journal since it shows the best performance in terms of accuracy on PacBio data(at least it does in my experiments). Many thanks in advance.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants