Why were only a few taxonomies discovered?

Our code:
qiime feature-classifier classify-sklearn \

–i-classifier silva-132-99-nb-classifier.qza
–i-reads rep-skin-dada2.qza
–o-classification taxonomy_skin.qza
Thanf for your attention.

Hi @Wang_cs001632,

There could be several reasons for this, some are outlined here:

and here:

Since you are making use of the SILVA 132 full-length sequence classifier, my first guess would be that your reads may be in the wrong direction. You can make use of RESCRIPt to orient your reads to the SILVA reference database with the qiime rescript orient-seqs command.

One last suggestion, the SILVA 138 classifiers, and the files used to make them are here.

-Best wishes!

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Thank you for your timely reply!
The dataset to be processed was like that (https://www.ebi.ac.uk/ena/browser/view/PRJNA478488)
图片
SRR11242604.fastq.gz
SRR11242604_1.fastq.gz
SRR11242604_2.fastq.gz
Should we just simply cat them into one fastq.gz, such as
cat SRR11241832_1.fastq.gz SRR11241832_2.fastq.gz > 72S_L001_R1_001.fastq.gz
then input qiime2 as “CasavaOneEightSingleLanePerSampleDirFmt” ?

I think it’d be easiest to do this after you’ve merged the reads and made ASVs. That is, run this command on your DADA2 or deblur output prior to assigning taxonomy:

qiime rescript orient-seqs ...

-Mike

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