cutadapt with deblur instead of dada2


I am using the newest version of qiime2 to run again on a different dataset while I need to use deblur and to do so, I need to pre-use cutadapt (q2-cutadapt) to trim/truncate what deblur can't truncate (like in case dada2).
Could you please help with choosing if my dada2 code is as following

qiime dada2 denoise-paired \
  --i-demultiplexed-seqs paired-end-demux.qza \
  --p-trunc-len-f 250 \
  --p-trunc-len-r 200 \
  --o-table dada2-table.qza \
  --p-n-threads 0 \
  --o-representative-sequences dada2-rep-seqs.qza \
  --o-denoising-stats dada2-denoising-stats.qza \

so what I can do in cutadapt to have the same result that come out from dada2
So that I can merge both forward and reverse reads to be used to Deblur

My sequences are already trimmed using trimGalore outside qiime2 which I tried before and worked fine for my results when compared to using Rstudio (was doing some trials)
In our group, we use trimGalore followed up by dada2 to get rid of the unneeded sequences

So in short
1- cutadapt
2- quality control visualising
3- joining forward and reverse
4- deblur

Your advice from the experience you have would be so helpful and makes things much easier
Thanks very much

Hi @MarwaTawfik,

Thanks for your patience! I am about to sign off for the day, but will follow up with you tomorrow to help you with this!

Hi @MarwaTawfik,

Thanks again for your patience here! I'll dive in to some thoughts and suggestions below:

q2-cutadapt can't be used to trim/truncate a fixed number of reads - but you will most likely still want to include this in your analysis pipeline for filtering (utilizing the trim-paired method, since you are working with forward and reverse reads).

The next step in your pipeline should be to merge your demultiplexed & filtered reads. You can do this using q2-vsearch with the join-pairs method. From here, your analysis will inherently diverge from your dada2 pipeline - this is because you will be working with joined reads vs. paired end reads (forward and reverse).

There isn't a direct way to replicate exactly the truncation lengths that you've utilized in your dada2 analysis with deblur, but what I'd recommend is to run qiime demux summarize (example command can be found here), which will provide you with an output visualization that you can examine in QIIME 2 View using the interactive quality plot, and get a better idea of where you should be truncating your joined reads.

Once you've determined where you want to truncate your joined reads, you can utilize the denoise-other method in q2-deblur, using --p-trim-length for truncation.

Hope this helps! Happy :qiime2: ing :slightly_smiling_face:

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