I hope that you are working with V4 region and not longer one, since otherwise there may be some difficulties with merging the reads, independently of the machine/technology used.
Yes, they can!
You can use both of them by your choice.
You need to denoise each sequencing run separately but with the same settings to avoid introducing the biases by providing different settings, and messing with error models in Dada2.
My approach would be:
Import each run separately
Remove primers (the same primers, right?)
Run Dada2 for each run (with the same settings, try to find optimal parameters for all three).
Merge representative sequences and feature tables.
Keep run info in the metadata file to be able to trace the batch effect or to account for it in stat. analyses.
Thank you, @timanix for the quick and incredibly helpful response!
Yes, I'm working with the V4 region, not the longer ones. I really appreciate your clarification on minimizing technical batch effects, especially when dealing with different sequencing runs and platforms. Your suggestions are extremely valuable.
One more question to better understand your recommendations: Since technical batch effects are common with different sequencing techniques, and your approach helps to minimize them, do you know of any publications using the methods you mentioned that merge datasets from different sequencing machine models? I would like to reference them in the Methods section of my future publication.
Again, thank you so much for your assistance!
Best,
Brandon
Hi @Brandon
Following on the great answer from @timanix.
I would say the main point is to highlight if there is any batch effect in your data because the different runs (well .. we can assume it will be there) by tracking samples from each run in the sample metadata. Then you can manage by applying statistics that can answer your biological question by considering it is masked behind the batch effect.
On paper I was curious what is out and I found this nice review:
Which include all the analysis step and a full paragraph on batch effects and statistical methods to manage it.
Cheers
Luca