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optimum parameters for ONT reads #68
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Hi, if you can share a few example input datasets, I think I may be able to give you some suggestions in terms of parameters. |
Actually this is not for a specific scenario; I'll use it in my algorithm and currently testing it with ONT data of some samples (reads can be retrieved from the crams here: https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1KG_ONT_VIENNA/hg38/). Basically it should be fast enough for 20-30K long ONT reads. I'm currently using wtdbg2 for this. |
I'm also sending a sample cluster of reads. This is one of the large clusters (25 reads), so not all of them are that large. |
I am not sure the scenario you specifically refer to. |
I actually want to generate a consensus but since the poa algorithms are slower, I had to use wtdbg2. Your algorithm seems to be much faster, so I wanted to test it. For the ONT reads of 20-30K, which w, k, min-w, etc. would you suggest? |
For your data H2-s218243_1350.fasta.zip, I see the read lengths varies a lot and they are not from the same strand. Since I don't know how you obtained this cluster of reads (based on mapping position?), I can only suggest you run |
Hi,
I'm trying to use the library to generate consensus of ONT reads for multiple clusters of reads. Each cluster has around 10 - 30 reads. However, I'm not sure which parameters to use for minimizer-based seeding and partitioning in order to balance the accuracy and speed.
I'll be happy if you can suggest me a set of parameters to optimize for speed, memory and accuracy.
Thank you,
Arda
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