Converting ASVs from DADA2 to OTUs

I am relatively new to Qiime. I need your help for this problem
Is it possible to convert the output of DADA2 (ASV) table into an OTU table? ( I already saw a previous publication about this topic : Converting ASV from DADA2 to OTU ) but I didn't really understand. if It's the case what command line I should write because Mr Matteo_Scanu putted the command line that permits to genetae the ASV I think not the OTU from ASV :confused:
I really need your help !!

Hello @Dali,

Welcome to the forums! :qiime2:

I'm glad you found that thread on conversion. I think it's a great resource! The answers to your questions are inside. :mag_right:

The 3rd post by Luca is extremely important because converting from ASVs to OTUs is usually a bad idea that you want to avoid!!

Review that thread carefully, then report back here.

Do you understand why OTUs are usually worse than ASVs?
For your study, do you still want to use OTUs, and if so, why?


thank you very much for your response !!
Actually I need OTU because I'm going to use picrust2 for functional prediction and as far as I know picrust2 works with OTUs

Fortunately, Picrust2 works great with both OTUs and ASVs, as mentioned in the Picrust2 Wiki!

There's even a plugin with Picrust2 plugin that makes this process even easier.

If you want to transform ASVs into OTUs, it's possible! Picrust1 does require closed-reference OTUs...

I'm sorry I've not been answering your questions very directly. I know a lot of guides on the internet are old and may show methods that are no longer current. My goal is to help get stuff done with modern methods, and often this means advising against methods I view as obsolete.

In the end, the choice is up to you.


Thank you very much for this clarification I'm really grateful. I still have 2 more questions : we can apply picrust2 on 16s rRNA bacterial gene. if it's the case , do you have please an example of files like in the tutorial by that I mean : biom.qza , seqs.qza , metadata.tsv
thank you in advance !!!


I usually download example files from the qiime2 tutorials.

The picrust2 example has a feature table called biom.qza.
In the pd-mice tutorial the feature table is called dada2_table.qza

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Good afternoon,

I hope this message finds you well. I don't mean to interrupt your ongoing discussion, but I am currently working with metagenomic data targeting the ITS regions of fungi. I was wondering if it's feasible to utilize PICRUSt2 for this kind of analysis?

Additionally, when employing PICRUSt2, is there a universal input file format that applies to various organisms, such as mice, monkeys, chickens, and fungi? Or does each organism necessitate its unique file type?

Lastly, for functional analysis, is there a dedicated database we should be referencing, like KEGG or something similar?

Thank you for your time and insights.

I think this is a good time to review the Picrust2 paper (free PMC link)

There are two main criticisms of amplicon-based functional prediction. First, the predictions are biased towards existing reference genomes, which means that rare environment-specific functions are less likely to be identified. ...
The second criticism is that amplicon-based predictions cannot provide resolution to distinguish strain-specific functionality. This is an important limitation of PICRUSt2 and any amplicon-based analysis, which can only differentiate taxa to the degree they differ at the amplified marker gene sequence.

PICRUSt is a remarkable method. Using only a few hundred basepairs of RNA, it can search a database to predict hundreds of functional pathways that could be expressed.

But it's only a prediction of functional potential. It's not a replacement for transcriptomic sequencing.

I like using EggNOG, which is similar and free
Run EggNOG online: EggNOG Database | Orthology predictions and functional annnotaion
Run EggNOG on your own supercomputer: GitHub - eggnogdb/eggnog-mapper: Fast genome-wide functional annotation through orthology assignment

For these, you need real transcripts

Thank you sir for tour previous time.
In this case I think picrust2 is not suitable to perform the prediction of functional analysis on ITS regions. Correct me if I'm wrong

Hi @ahlemfrigui,
Yes, I believe that you are correct that picrust2 was only designed for use on 16S data.

I initially had the same thought, but after seeing this link, I'm now uncertain : ITS-2 data and picrust2 · Issue #9 · gavinmdouglas/q2-picrust2 · GitHub

Yes you are right.
Read this preprint about picrust2 that was linked in the issue:

It seems like it can be used but is less accurate.

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