# Possible Analysis Pipeline for Ion Torrent 16S Metagenomics Kit Data in QIIME2?

**URL:** https://forum.qiime2.org/t/possible-analysis-pipeline-for-ion-torrent-16s-metagenomics-kit-data-in-qiime2/13476
**Category:** User Support
**Tags:** best-of-the-forum
**Created:** [February 5, 2020, 12:53am UTC](https://forum.qiime2.org/t/possible-analysis-pipeline-for-ion-torrent-16s-metagenomics-kit-data-in-qiime2/13476 "2020-02-05T00:53:06Z")
**Posts on this page:** 1
**Showing post:** 31

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### Author: ![Lauren](https://forum.qiime2.org/letter_avatar_proxy/v4/letter/l/b4bc9f/32.png) [@Lauren](https://forum.qiime2.org/u/Lauren)
#### Post date: [April 3, 2020, 6:17pm UTC](https://forum.qiime2.org/t/possible-analysis-pipeline-for-ion-torrent-16s-metagenomics-kit-data-in-qiime2/13476/31 "2020-04-03T18:17:40Z")

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Hi Everyone!

@cjone228 and I want to clarify this point - we just realized that using the the full length sklearn classifier is _not_ advised because the pre-trained sklearn classifier doesn't do well with mixed-orientation reads (see [post](https://forum.qiime2.org/t/classifier-for-ion-torrent-data/3675)). We just had the problem where we were only getting ~60-70% classification with both Silva and GG and realized that mixed orientation reads are likely the culprit. Thus, we will try to move forward with classify-consensus-vsearch. Just found this [post](https://forum.qiime2.org/t/sequence-extraction-and-classifier-training-for-ion-torrent-data/14097) - super helpful! 🥳 🤩 😆 @KMaki have you gotten vsearch consensus classifier to work? If so, do you mind sharing your final code? 🙏

Investigation of this hurdle brought up another question: do we need to deal with our mixed orientation reads prior to the taxonomy steps? (Just a reminder that IT produces single end reads, but each sample includes reads from 12 different pooled amplicons: 6F primers and 6R primers.) @Jen_S [posted](https://forum.qiime2.org/t/reverse-complement-trimmed-reads/13673) on this topic and @Nicholas_Bokulich recommended separating out F from R reads prior to denoising, denoising separately, and then merging. Is this something we should do? Could mixed oriented reads be part of why only ~70% of our sequences are passing the dada2 filter? (see @cjone228 and @Jen_S discussion on that below).

Thanks much!  
Lauren :qiime2:

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