Comments (6)
@rwhetten
Thank you for your interest in using GoldRush for your projects.
The GoldRush parameters are not optimal for a genome of your size and complexity. We are working on a solution for genome of that size and complexity. The following suggestions are experimental:
- k = 24
- w = 18
- s = 101101111011110111101101
Because the size of certain plant genomes are so large, k and w sizes need to be adjusted to accommodate for the possible number of k-mers (and incorrect k-mers). Do note, that due to the increase in k and w, GoldRush will now need upwards of ~800GB to run for plant genomes of that size, but since your reads are corrected, the RAM usage should be lower than estimated.
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OK, thanks. I have access to a compute node with 1 Tb RAM, so I'll do a test on that node.
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This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your interest in GoldRush!
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The job used up to 1.2 Tb RAM, which is not a problem, but the resulting assembly is about 2x the expected size (46 Gb instead of 23), and consists of 1.9 million scaffolds with N50 of around 30 kb, which is similar to the N50 of the long read data used. Are there other parameter adjustments that would help to increase contiguity? A haplotype-separated diploid assembly would be great if that is possible, but at this point it is not useful.
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Unfortunately, GoldRush with genome of that size and complexity is very experimental. The results you show is in line with we have in-house and it is unlikely that the generated assembly is haplotype-separated. Unfortunately I don't think simple parameter changes will be enough to assemble genome of that size and complexity. This will be one of the tasks we will actively work on.
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This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your interest in GoldRush!
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