Comments (1)
hani-girgis
commented on August 10, 2024
Hi, Evan.
The length range of the microbiome sequences in the paper is 171–372, which is more homogenous than yours.
Yes, dividing your data set based on length would work. Then I would cluster each group separately.
After that you may want to extract the centers and use Identity (all-vs-all) on the centers and merge (select one) centers that are similar (with identity scores greater than the threshold).
Finally, run Identity on the reduced center set and the entire data set and assign a sequence to the closest center.
This is a work around for now. But this process can be automated in future releases.
Let me know if you have additional questions.
Best regards.
Hani
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Related Issues (20)
- Identity on very large data HOT 10
- A sequence is too short HOT 1
- kmer-db HOT 1
- How to get MeShClust v3.0.0 HOT 3
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- Floating point exception (core dumped) HOT 1
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- Turn off warning?
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- Segmentation fault HOT 2
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