Comments (5)
Hi @wdecoster,
Can you provide a minimal example (bam) that reproduces this? Our current pre-release may fix this; we've worked quite a bit on how chunks of data are handled. The pre-release is available on pypi: pip install medaka==0.7.0a1
. If you want to test this, note that some command line options may have changed.
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I encountered this issue for a 20x human genome coverage bam, but not for two larger bams. The bam is 80Gb, which is perhaps not a 'minimal' example. I'll have a look at the pre-release.
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Wouter can you confirm the v0.7.x releases resolve this issue for you?
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I'm now on v0.7.0-alpha.1, and running in parallel in separate windows over the genome (I should maybe look into using the GPUs of our PromethION...).
I haven't encountered the error anymore, but I also haven't exactly reproduced what caused in the first place, so I cannot confirm conclusively that it is resolved.
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Thanks, I believe the issue is resolved: I have run successfully through a chrom1 dataset.
Using a GPU is definitely preferred if available; a V100 will perform the consensus steps at around 10Mb per minute.
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Related Issues (20)
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