If you did analysis with DADA2, then you have ASVs. It’s a little bit jargony, but “ASV” is short hand that tells you the sequence was denoised and should have single nucleotide resolution. OTU says the sequences were clustured, and that has all sorts of implications for external validity, resolution, how sequences are discarded, etc. It is really important for clear communication with people who have worked in the microbiome to specify that you’re using ASVs instead of OTUs and it will matter a lot to them.
Two things to consider: first, most publications take time to get to print. So, what you see in the literature today was probably started two or more years ago. Second, they likely did use OTUs. You used ASVs. It’s a methodological difference.
I’m not sure I understand this question. You used ASVs as the basis for all of your data, so for example, you should have “observed ASVs” (not observed OTUs). But, when you talk about diversity, it depends on what table you used. Did you use your ASV table? Did you collapse some how? Your description should reflect how you handled the data.
I think we all get there and need a sounding board sometimes, especially as things are transitioning between methods. Hopefully this helps make it more clear, but feel free to come back and discuss more! Science is so much harder in a vacuum.
i have one doubt i am using table.qza which was generated after the dada2 denoising process and when i visualize this table in form of table.qzv i found the feature table. and this table.qza i used to create an alfa rarefaction curve i successfully generate the alfa rarefaction curve. here one more box name is metric, i scroll it and i found that it showing observed OTUs, but i am using a feature table which is consists ASVs not OTUs. so how can we write in the paper that its OTUs or ASVs. for more detail i have attached the image which clearly show observed OTUS NOT ASVs… how can we justify this thing?
I used the DADA2 pipeline for data analysis. When I submitted a paper in 2018, I used “observed_OTUs” following suggestions from the above post. I had to explain to a reviewer why “observed_OTUs” was used: it is a parameter name although I used ASVs.
I submitted a paper this year, a reviewer asked the same question again, I will change it to “observed_ASVs” this time.
The term “Observed OTUs” is just as valid as “Observed elephants”, both are simply labels. It is important however that you know what in fact is being “observed”. In your case, as you used an ASV table to generate the rarefaction curves, you are looking to “observed ASVs” and that is a valid way to reference this diversity metric, but you can also use “richness” or “observed features”, which are more generic. In fact, to solve this recurrent doubt, the most recent QIIME2 version changed the label “Observed OTUs” to “Observed features”, a generic term that works for both OTU tables and ASV tables.