# Is my truncation parameter exploration sufficient, and is my interpretation correct?

**URL:** <https://forum.qiime2.org/t/is-my-truncation-parameter-exploration-sufficient-and-is-my-interpretation-correct/34264>\
**Category:** General Discussion\
**Tags:** dada2\
**Created:** [July 27, 2026, 3:18pm UTC](https://forum.qiime2.org/t/is-my-truncation-parameter-exploration-sufficient-and-is-my-interpretation-correct/34264 "2026-07-27T15:18:44Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Rakaya](https://forum.qiime2.org/letter_avatar_proxy/v4/letter/r/91b2a8/32.png) [@Rakaya](https://forum.qiime2.org/u/Rakaya)\
**Post date:** [July 27, 2026, 3:18pm UTC](https://forum.qiime2.org/t/is-my-truncation-parameter-exploration-sufficient-and-is-my-interpretation-correct/34264/1 "2026-07-27T15:18:44Z")

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![IMG_1790](https://forum-qiime2-org.s3.dualstack.us-west-2.amazonaws.com/original/3X/2/2/22f1f93712b716f0c9a205c0e4c8882cc82ce4b7.jpeg)

[2\_trimmed.qzv](https://forum.qiime2.org/uploads/short-url/v3oBeXJKf56e2JQMcV4tvBuo2fB.qzv) (368.8 KB)

Hi everyone,

I’m working with 16S rRNA V3–V4 data in QIIME 2/DADA2 and tried to choose truncation parameters by systematically exploring forward and reverse truncation lengths, similar to the approach discussed in this thread [Help/advice on truncation parameters - #9 by Deyan\_Donchev](https://forum.qiime2.org/t/help-advice-on-truncation-parameters/33462/9) .

I’ve attached the quality score plots + retention heatmaps for three representative samples.

From these results, my interpretation is that:

- very short reverse truncation lengths reduce merging and retained reads, as expected,
- beyond approximately 180 bp for the reverse reads, the retained non-chimeric reads become fairly stable across a broad range of truncation combinations,
- instead of a single sharp optimum, the data appear to have a plateau where moderate changes in truncation lengths produce very similar results.

My questions are:

1. **Does this look like a sufficiently broad exploration to confidently choose a truncation “sweet spot,” or would you recommend exploring the upper-right region (longer forward and/or reverse truncation lengths) further?**
2. **Is my interpretation correct that this plateau suggests my dataset is relatively insensitive to moderate changes in truncation lengths, and that this is generally a good sign of robustness rather than a limitation?**
3. **If my interpretation is incorrect or incomplete, could you explain how you would reason through these heatmaps when selecting the final truncation parameters?** I’m trying to understand the principles behind the decision.

I’d really appreciate any feedback. I’m relatively new to this aspect of DADA2 and would like to make sure I understand the reasoning behind parameter selection.

Thank you!

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**Author:** ![colinbrislawn](https://forum.qiime2.org/user_avatar/forum.qiime2.org/colinbrislawn/32/6221_2.png) [@colinbrislawn](https://forum.qiime2.org/u/colinbrislawn)\
**Post date:** [July 28, 2026, 3:21am UTC](https://forum.qiime2.org/t/is-my-truncation-parameter-exploration-sufficient-and-is-my-interpretation-correct/34264/2 "2026-07-28T03:21:23Z")

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Hello Rakaya,

I really appreciate a visual result like this! I can tell you have thought a lot about this.

> [@Rakaya](#):
>
> From these results, my interpretation is that:
> 
> - very short reverse truncation lengths reduce merging and retained reads, as expected,
> - beyond approximately 180 bp for the reverse reads, the retained non-chimeric reads become fairly stable across a broad range of truncation combinations,
> - instead of a single sharp optimum, the data appear to have a plateau where moderate changes in truncation lengths produce very similar results.

I concur! And this is pretty much expected for Illumina data.

Note that the plots show "% non-chimeric read per sample", which is true, but this implies that chimeric levels change with trimming, which they do not. I suspect with fill="% merged" this would be clearer!

> **Does this look like a sufficiently broad exploration**

Sure, and this is a great check to run when working with new primers or a new sequencing technology! Consider a test that you can apply to _all_ your samples, not just three. Consider using [GitHub - Zymo-Research/figaro: An efficient and objective tool for optimizing microbiome rRNA gene trimming parameters · GitHub](https://github.com/Zymo-Research/figaro), if you have not found it already.

> **this plateau suggests my dataset is relatively insensitive to moderate changes in truncation lengths**

Yes, and this is normal for Illumina runs.

> and that this is generally a good sign of robustness rather than a limitation?

Uh, neutral. It's just how DADA2 works with Illumina data. I find I can use the same DADA2 trimming settings for a primer set for years, so these settings are robust as long as the primers stay the same.

This is a great example of how the trimming setting work for DADA2!  
Thank you for adding this to the forums.

Good job!