I think I understand - it sounds like you’d like to know which genbank ids were most similar to your sequences (in the
rep-seqs.qza file). Is that right? We unfortunately don’t have a way to get that information at the moment, though it is something we would like to add. This is in part because, with taxonomy assignment, typically more than one of the reference sequences is informing each individual taxonomy assignment.
If I understand what you’re looking for, you may be able to get this information using
vsearch directly (not through QIIME 2).
vsearch will already be installed in your QIIME 2 environment. A command that I’ve used for this before is:
vsearch --db dna-sequences.fasta \ --usearch_global queries.fasta \ --alnout out.aln \ --blast6out out.bl6 \ --id 0.0 \ --maxaccepts 10 \ --qmask none
This will do a BLAST-like search of all of the sequences in
queries.fasta against the sequences in
dna-sequences.fasta, and will report back the 10 best matches for each sequence in
queries.fasta. We plan to make this accessible as a method in QIIME 2, but we haven’t done that yet. If this does do what you’re looking for, can you let me know? That type of feedback helps us to prioritize new functionality.
What i look for is exactly what you mentioned in your anwser. Now I am working on a project on diets of wild animals. We have our plants in animal feces analysed by vsearch, but the rumen bacterial community analysed by qiime2. So now it is hard for me to do the mantel test between plants diversity and bacterial diversity. Thank you again for your help.
I’m happy to try to help with that if you explain the issue that you’re having. This should definitely be possible to achieve with QIIME 2 if you have a feature table where the features are plant taxa (e.g., species identifiers) and the samples are the same (i.e., have the same identifiers) as the ones for which you have bacterial data.
what confuses me now is not mantel test any more, i finally find a way for mantel. I wonder how could I have an otu table, not the taxon table of every sample (like in the image)? Best.
Hi @Yanfei-Geng, I think the OTU table that you’re looking for should be the
feature-table-2.qza artifact that you’ve been working with. You could export that with
qiime tools export, and then convert the resulting
.biom file to tab-separated text with
biom convert --to-tsv. Would that get you what you need? If not, can you describe what the features are in your
feature-table-2.qza file, and what you would like the features to be in the table you’re trying to generate?
[email protected] the one you told me the output is like this
but the one I want is like following, is this possible?
I found something in alpha-rarefaction.qzv
after downloading, the table is like this
did i understand this table correctly? Thank you so so much.
$ qiime tools export table.qza --output-dir ./ $ biom convert -i feature-table.biom -o feature-table.tsv --to-tsv $ biom head -i feature-table.tsv # Constructed from biom file #OTU ID L1S105 L1S140 L1S208 L1S257 L1S281 4b5eeb300368260019c1fbc7a3c718fc 2222.0 0.0 0.0 0.0 0.0 fe30ff0f71a38a39cf1717ec2be3a2fc 5.0 0.0 0.0 0.0 0.0 d29fe3c70564fc0f69f2c03e0d1e5561 0.0 0.0 0.0 0.0 0.0 868528ca947bc57b69ffdf83e6b73bae 0.0 2276.0 2156.0 1205.0 1772.0 154709e160e8cada6bfb21115acc80f5 812.0 1176.0 713.0 407.0 242.0
Here, the first column contains feature or OTU ids (e.g.,
4b5eeb300368260019c1fbc7a3c718fc), the first row contains sample ids (e.g.,
L1S105), and the values in the table indicate the number of times each feature was observed in each sample. So, in this case, feature
4b5eeb300368260019c1fbc7a3c718fc was observed 2222 times in sample
L1S105, and zero times in each of the other samples.
2 off-topic replies have been split into a new topic: What does the number represent in observed_otus.csv
Please keep replies on-topic in the future.
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