Where should I have to truncate the forward and reverse read after removal of primers using qiime cutadapt?My trimmed.qzv is followed.

Hello Mandeep,

Welcome to the forums! :qiime2:

What region did you sequence and how long do you expect it to be?
(I ask because we want to trim as much as possible while still allowing your reads to join when running dada2.)

We have sequenced the V3-V4 region of 16S rRNA. If you need more information please let me know. I will be very grateful for your support.

OK, V3-V4 is pretty common.

How long do you expect the amplicon to be, on average? This can be a little different depending on which V3-V4 primers are used.

Have you tried running the data through DADA2 without trimming?

We used the primers
16S rRNA F
16S rRNA R
ACTACHVGGGTATCTAATCC. I don't know how much the length should be if you know the expected length by using these primers please the suggestion according to that. And I didn't use dada2 without trimming.

What company sold you these primers? How long do they expect the resulting amplicon to be?

What paper are these primers based on? How long did the authors of this paper observe their amplicon to be?

Another option is to just run this through dada2 'blindly' (without estimating amplicon length). Do this a few times and pick the setting that cause the most reads to join. :person_shrugging:

The length of V3-V4 region is 200-450bp. Now please tell me where should I have truncate the forward and reverse reads based of amplicon size and the demux.qzv

Hi @Mandeep,

Jumping in here with a reminder to please review our code of conduct, in particular the section regarding doing your own work. It is ultimately your responsibility to understand your data and your tools, perform your own analysis, and derive meaning from your data.

If you are unsure of where to trim and truncate, please go through our user documentation in detail and follow one of our many tutorials (Moving Pictures is a great one to start with) to get yourself better familiarized with how to make those determinations on your own. We are happy to help with any troubleshooting or how-to's, but you ultimately need to be the one who makes the informed decisions on your analysis.

Cheers :lizard:


I have done all the quality filtering and trimming steps before importing my data in qiime2. After import I have done the joining or merging of reads with the help of qiime vsearch . Now I have joined_reads_with_quality. Can you please guide me for further analysis and the expected length I want 400bp-450bp of my amplicon. How to proceed further.

Hello @Mandeep,

It's far more common to provide the unmerged but quality controlled paired reads to dada2 (which will dereplicate and denoise your reads along side merging them) rather than merging reads pre-dada2.


Can we just process our reads with dada2 only with quality score 25 rather than providing the forward and reverse trunction length ? If it's possible than please tell me, because with trunction length info I lost many reads, I just want to process my sequences with quality score.
Please help me .

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Hello @Mandeep,

Yes, you can achieve this by setting the truncation parameters to 0, not providing the trim parameters, and setting --p-trunc-q to 25.


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