pre-trained UNITE 9.0 classifiers for QIIME 2024.2 (and older!)

UNITE version 9.0 is out, and I've built classifiers for it compatible with the newest version of Qiime2:

Other notes unite-train

Eventually, this will be superseded and UNITE will be provided directly on the Data Resources Page.

Need a different database? Please send me a direct message!

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Thank you very much Sir

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I see "all" eukaryotes? Does this mean CO1?

Good question! I think UNITE is ITS only (so, no CO1 to my knowledge)

You can read more on their page: UNITE - Resources

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Hello @colinbrislawn - I have a novice question about using this pre-trained classifier.

The qza files available in the GitHub link you posted, can these be used directly in the "test the classifier" portion of this q2-feature-classifier tutorial?

Ex:
qiime feature-classifier classify-sklearn
--i-classifier unite_ver9_dynamic_25.07.2023-Q2-2023.9.qza
--i-reads rep-seqs.qza
--o-classification taxonomy.qza

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Hi @Taylor_Akers,
From what I understand, this should work!

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Great, thank you @cherman2 ! It worked!

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An off-topic reply has been split into a new topic: qiime2 does not recognize classifier as a .qza artifact

Please keep replies on-topic in the future.

Hi @colinbrislawn thank you for creating this classifier!

I downloaded the latest version and tried it with my data. However, it runs for about 20 minutes before the job is killed. I am assuming this is due to insufficient RAM (I have 16GB)?

In that case, I should likely create my own classifier using RESCRIPt? Thank you.

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Making a new classifier takes more memory then using an existing classifier. Using one of these pre-made ones still probably your best option with limited memory...

I would try using a smaller number of reads per batch, say --p-reads-per-batch 5000 or 1000.
Also consider using a search based classifier like classify-consensus-blast: classify-consensus-blast: BLAST+ consensus taxonomy classifier โ€” QIIME 2 2023.9.2 documentation

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