I recently do classifier meet some problem , when I do taxonomy for my smple I usually get the result juse a class level ,like the picture ,I find the reads usually very long ,so I usually set the -trim-p is 0 and the -trun-p is 400 ,then I will get the long DNA, but I can't get the result about other levels ,I meet the suitation three times ,So I hope you can help me and tell me the reson , I need to solve the problem ,thank you very much .
Looks like you are only receiving kingdom-level classifications. This is almost always an indication of human error, specifically whether the correct reference database or classifier was used. Please answer the following questions:
- What gene target/primers are you using?
- What classification method are you using? Please post the exact commands.
- I see that you are using greengenes. Did you use one of QIIME2’s pretrained classifiers or are you training your own classifier?
Chances are either:
- you are using a classifier trained with the wrong primers
- greengenes is not appropriate for your data. Are these bacterial 16S rRNA gene reads?
If you are receiving non-kingdom classifications, see this post for further troubleshooting.
I hope that helps!
thank you reply my question , I also try many times and the last I get the same result which just have the kingdom level ,the data from the NCBI and I use the article data ,I use the V1-2 primers and I use the greenenes classifically ,and I use the qiime2 offer database ,I want to know the train database is depend on my primers .and then I want to know maybe I should build the different primers and usually u se database for my analyse. and I use the silva and the greenene database do the analyse ,but I don’t know this is ture .so I should train the silva and greengene database ,and I should train in different orimers ? thank you very much.
thank you ,I want to know if I have other target/primers , I want to train my database and I want to know which "ref-seqs.qza " I can use ,in the wed https://docs.qiime2.org/2018.2/data-resources/ just have the full and the 515F/806R primers , I want to know I should use which to train my database ,and if I use the silva database ,I use the 99.otus.fastas and the majority_taxonomy_7_levels.txt or consensus_taxonomy_7_levels.txt ,I don’t know which is true ,but the last I find the result isn’t good ,,yes, the result just little is annotated ,and I use the greengene have many levels .so , I want to consult the team about the classifier which is the best annotation way . thank you .
As @Nicholas_Bokulich asked above, can you please post the exact commands you ran?
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