ASV or OTU ? What do I have?

I have search a lot the qiime forum and Moving pic tutorial eg Overview of QIIME 2 Plugin Workflows — QIIME 2 2022.2.0 documentation
but still I am not sure If I have ASVs or OTUs. Please, if someone can clarify it for me.

My workflow:
qiime dada2 denoise-paired --p-n-threads 0 --i-demultiplexed-seqs meta.qza --p-trunc-len-f 300 --p-trunc-len-r 255 --p-trim-left-f 17 --p-trim-left-r 21 --o-table meta_table --o-representative-sequences rep-seq-meta-dada2 --o-denoising-stats stat_meta

qiime phylogeny align-to-tree-mafft-fasttree
--i-sequences rep-seq-meta-dada2.qza
--o-alignment aligned-rep-seqs.qza
--o-masked-alignment masked-aligned-rep-seqs.qza
--o-tree unrooted-tree.qza
--o-rooted-tree rooted-tree.qza

qiime diversity core-metrics-phylogenetic --i-phylogeny rooted-tree.qza --i-table meta_table.qza --p-sampling-depth 12055 --m-metadata-file metadane_qiime_combine.txt --output-dir core-metrics-results_combine

qiime diversity alpha-group-significance --i-alpha-diversity core-metrics-results_combine/observed_features.qza --m-metadata-file metadane_qiime_combine2.txt --o-visualization core-metrics-results_combine/alpha-group-sig-obs-features.qzv

I hope I did not skipped any done step.
The final result of alpha diversity for observed features is in fact observed ASVs because I did not perform any clustering?


Hi @elina2410 ,

You are correct, you do have ASVs as result of dada2 denoising.

Thanks fo rsharing all your command and settings. How many sequences are passing your trimming lengths? I am asking because I got the feeling that the truncation at 300 bp on the forward sequences could be very strict and not many sequences can pass it.
Hope it helps,


Hello @llenzi
thanks for your answer and further question.
Here is reads quality:

and rep-seqs.qzv statistics:

Do you mean that I can have some reads shorter than 300bp which were discarded with applying --p-trunc-len-f 300?
I imported to qiime raw reads, and according to fastqc/multiQC all reads were 301bp.

Hi @elina2410 ,

yes dada2 works discarding reads shorter than the threshold you set, so you could have lost few reads by setting that to 300bp. Your statistics is showing you retain more than 70% of the sequences for some of the samples, this is good, but maybe you could recover few more sequences for the samples with below 30% of sequences passing the filters, by setting a lower threshold.

Hope it helps

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