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.
Thanks,
Jen
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!
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.