General metabarcoding dataset

I've been wanting to ask this for quite a while.

Is there a chance that QIIME 2 devs will develop the same pipeline for macroorganisms (non-microbes) or expand the current pipeline to cater to other macroorgansism datasets?

Or are there publications on macroorganisms that used this pipeline already that I was not aware of?

Hi @jbbq ,
Welcome to the QIIME 2 forum!

Short answer: QIIME 2 is already fully functional for diet metabarcoding, eDNA, etc for macro-organism studies.

QIIME 2 is not a pipeline. It is a software platform with different interconnected plugins to provide domain-specific functionalities. Pipelines exist, built on QIIME 2, but QIIME 2's plugins are rather the parts needed to build different pipelines.

So in that sense, QIIME 2 can be used to make a macroorganism pipeline, or existing pipelines built on QIIME 2 for microbes could be altered to switch some inputs or plugins (e.g., different reference databases, some different analysis steps) to make a customized macrobe metabarcoding pipeline.

Many! There are already quite a few in the literature that use QIIME 2. Here is one testing the accuracy of the q2-feature-classifier plugin for eDNA biodiversity surveys:
https://onlinelibrary.wiley.com/doi/10.1111/1755-0998.13407

Here an article describing how to build customized databases for any marker gene, and a benchmark of some customized CO1 databases by @devonorourke for diet metabarcoding and eDNA surveys (full disclosure: I am corresponding author on this paper). There are tutorials elsewhere on this forum for how to use RESCRIPt to build different marker-gene databases (CO1, 12S, etc) if you want to give it a try:

and another one by @devonorourke that benchmarked different clustering/denoising strategies for diet metabarcoding (full disclosure: I am a middle author):
https://onlinelibrary.wiley.com/doi/full/10.1002/ece3.6594

and finally another one by @devonorourke this time looking at bat diet metabarcoding (full disclosure: I am also a middle author on this one):

Yes, this is something that we will probably get to later this year. In the meantime, QIIME 2 is fully functional for this, only not as a monolithic pipeline to perform one long analysis specific to that data type. You will need to follow tutorials or chain together separate processing steps on your own to get where you are going. For the most part, the same steps that are used for microbial biodiversity surveys (and we have plenty of tutorials on that topic) can be used for macro-organism surveys, you basically just need to swab the reference databases used, and possibly consider different processing steps (e.g., whether to use OTU clustering or not? It depends on the marker gene, and see also the article of @devonorourke 's above).

So I recommend taking a look at existing tutorials and ignore the marker gene for the moment — then if you would like help on adapting a specific step (e.g., how to swap in a different reference database0, just open a new topic in the forum to ask. We are here to help!

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Thanks for this comprehensive response! This is greatly appreciated.

I have been using QIIME2 for some time now and I am really amazed at how detailed and systematic the platform is (and also how responsive and active the community is?). As I am planning to expand my field to macroorganisms, I wondered if this can still be used (with 'Microbial Ecology' on QII'ME').

Anyhow, I can't wait for your team's future projects. Again, many many thanks, and more power!

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Very good point! The name is historical (from qiime1 days), and to my knowledge the use of metabarcoding for non-microbial biodiversity monitoring came a bit later, otherwise perhaps the acronym would be different. We could just pretend that the "M" stands for "M*croorganism". Similarly, the plugin functionality and uses have expanded beyond the original focus on ecology.

When you have mastered using QIIME 2 for macroorganism biodiversity applications, please consider contributing a community tutorial to the forum, so that others can follow in your footsteps! :wink:

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