DADA2 pairwise alignments parameter tuning

[salias (Sergio Alías-Segura)]

Hello @Nicholas_Bokulich ,

Thank you for your response.

@Nicholas_Bokulich

Many users are using QIIME 2 to analyze ITS and other non-16S targets, so we need to consider their needs as well. So let's not rule this out just yet...

That's true (I could serve as a example). The thing is that, as you say:

@Nicholas_Bokulich

This sounds quite hypothetical — they should be re-examined, but it sounds like the appropriate settings are not known and would need to be explored.

So maybe there is no need to fine-tune these parameters and we are just overthinking it. The only way to know if it is worth it is, as you say:

@Nicholas_Bokulich

Ideally, some benchmarking should be done with a ground truth (e.g., mock community or other positive control)

So what I could do is:

1. Get mock data e.g. from mockrobiota, as they do in the Fungal ITS analysis tutorial
2. Follow tutorial until the denoising step.
3. Export sequences, then use DADA2 in R and try combinations of a range of values of KDIST_CUTOFF and BAND_SIZE.
4. Go back to QIIME2, and do taxonomic classificiation for each test
5. Evaluate accuracy and see if best combinations are different enough from default values

I'm currently focusing in my ITS QIIME2 Snakemake pipeline but I can spend some time to do the benchmarking and then share my findings here. If we spot some improvements by changing the default values of those parameters, I could even try to do a pull request to the q2-dada2 GitHub repository, although I would need to do some research on plugin creation, structure and philosophy.

Best wishes