Hello, I was wondering if @osaama.shehzad could share his Ion Torrent pipeline that he used for this analysis.
I am using the same data and have pieced together a work around using other tools in addition to Qiime. Would love to do it all in Qiime.
Continuing the discussion from Importing Ion Torrent data:
Hi @Jen_S! I understand that Ion 16S can be very stressful with QIIME. Basically, you use picard tools to convert your UBAMs into FASTQs following by building the latter files into Manifest as a Single End sequencing. Once the manifest is built using QIIME plugins, you should be good. Does that help?
Thanks @osaama.shehzad ! This would be a great topic for a community tutorial if you ever have any interest in posting a tutorial to help guide other users!
@Nicholas_Bokulich I will definitely do that very soon! Thanks for all your support, Nicholas!
Here are the steps I used:
Process your run data on the Ion Torrent server w/o barcodes. Export the data from your Ion Torrent server using the FastqCreator plugin. This should create a single fastq file with all your reads and associated quality scores.
Convert your .fastq file into a .fasta and .qual file using the convert_fastqual_fastq.py command in QIIME:
- Proceed wtih splitting libraries, picking OTUs, etc.
Note–I worked this all out it QIIME 1. I am now working on developing a workflow in QIIME2 but haven’t figured out how to sort out multiple amplicons with the same barcodes–looking into cutadapt as an option but haven’t quite figured it out yet.
Hope that helps.
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