A new user of QIIME 2 writes to you, and first of all I take the opportunity to tell you that I am in awe of this super-powerful tool for microbiota analysis.
As I am new, I am just exploring and trying to internalize the concepts and parameters associated with the DADA2 plugin. After looking through a DADA2 tutorial in the R environment I found that in the sequence trimming/truncating stage, the author suggests using a tool called FIGARO (Weinstein et al., 2019) that allows you to optimize these parameters in order to suggest a trimming site for both reads that minimize the expected error for both, as well as preserve the expected percentage of reads (Figure 1).
Figure 1 .Panel A: Fitting an exponential regression to the 83rd percentile for cumulative expected error
values across multiple samples from a single sequencing experiment on a MiSeq. The high
(>0.99) r2 value in both directions is representative of what was often observed with this model.
Panel B: A plot showing the percent read retention, trimming site scores, and forward and
reverse expected error allowances for a set of 16S rRNA gene sequences covering the V3 and
V4 regions generated on a MiSeq. The vertical dashed line represents the trimming site
recommended by FIGARO, providing minimal expected error allowances in both directions
while still preserving the expected percentage of reads (figure and description from Weinstein et al., 2019)
I suggest implementing this tool in , since it can contribute positively in two things: 1. increase objectivity when setting parameters and 2. save time when adjusting these parameters by doing it by trial-and-error.
Greetings to all.