# IonTorrent 16S Metagenomic Kit - Consensus feature table across V regions

**URL:** https://forum.qiime2.org/t/iontorrent-16s-metagenomic-kit-consensus-feature-table-across-v-regions/25755
**Category:** General Discussion
**Tags:** ion-torrent, feature-table
**Created:** [March 10, 2023, 2:05pm UTC](https://forum.qiime2.org/t/iontorrent-16s-metagenomic-kit-consensus-feature-table-across-v-regions/25755 "2023-03-10T14:05:34Z")
**Posts on this page:** 1
**Showing post:** 2

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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: [March 10, 2023, 5:34pm UTC](https://forum.qiime2.org/t/iontorrent-16s-metagenomic-kit-consensus-feature-table-across-v-regions/25755/2 "2023-03-10T17:34:14Z")

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Hello @andresarroyo,

Welcome to the forums!

I have good news! This multi-region kit has been [discussed in great detail](https://forum.qiime2.org/t/possible-analysis-pipeline-for-ion-torrent-16s-metagenomics-kit-data-in-qiime2/13476), and some methods have been proposed within Qiime2 to deal with it.

The bad news is that this is still pretty difficult and there is no standard method for addressing this.

EDIT: But there is a new plugin you should try: [q2-sidle](https://github.com/jwdebelius/q2-sidle) 👈

> [@andresarroyo](#):
>
> However, developing 6 downstream analysis using 6 feature tables (one per V region) will generate a vast amount of results that can be a nightmare when we need to interpret them. For example, if we are working with clinical data when comparing healthy and cancer patients, this could be tedious to interpret.

Correct. 🙃

> [@andresarroyo](#):
>
> **Is there a way to integrate the dada2 preprocessed results (feature table and representative sequences) from each V region and generate a "consensus" feature table?**

No, because the regions themselves don't overlap so you can't tread it like genomics and 'assemble' them into a full-length 16S gene.

You could place your disparate ASVs into a tree, but that still does not create a single ASV from the 7 regions you sequenced.

EDIT, which is where sidle comes in:

> we present Sidle, an implementation of the Short MUltiple Reads Framework algorithm with a novel tree-building approach to reconstruct rRNA genes from individually amplified regions.

Definitely worth a try!

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_[View the full topic](https://forum.qiime2.org/t/iontorrent-16s-metagenomic-kit-consensus-feature-table-across-v-regions/25755)._