I read here that the read lengths must be the same for all sequencing runs being compared to avoid study-specific bias. If one sequencing run used V4 16S primers and a different run used V3+V4 16S primers, would that mean I must give both runs the same —p-trunc-len values when using DADA2 or Deblur? If so, what value would be an acceptable cut off point based on the quality plots that I included?
Also, originally I trimmed it based on the value 235 from the quality plot for the V4 only run, but if I use that value as a trimming cut off point for the V3+V4 run, would I be losing the part of the read that was amplified by the V4 primer?
After this step I was planning to merge both feature tables and sequences and use the fragment-insertion plug-in.
depends what you want to do. See also the q2-fragment-insertion tutorial (and read the paper at the bottom of the tutorial if that sounds like it fits your needs)
No, because the 5’ primers are different. Instead, trim to the same primer sites. The best approach would be to use qiime cutadapt trim-paired to cut to the same sites prior to dada2 (this would require the primers to be present at the time of trimming).
Since you have paired-end reads it does not matter where you truncate, so long as your reads are still merging successfully.
Ah you have already found q2-fragment insertion. If so, you do not need to use the same dada2 parameters (specifically for q2-fragment-insertion… for other steps like taxonomy-based analyses you would need to do so).