Hello,
I would like to use Qiime 2 to analyze 454 data without using Qiime1 first to generate the .biom table. Can anyone think of a way to do this? Is there a way to convert the .fna file to .qza?
Thanks!
Hi @LauraMason!
Do you have a way to get that data as a fastq file? While not yet supported, we are planning on updating our DADA2 plugin to handle 454 but it does need quality information.
If not, you might be able to use our vsearch pipeline for more typical clustering, but I don't think we have tested that particular use case for it yet. @Nicholas_Bokulich, do you see any reason that wouldn't work?
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The vsearch OTU clustering pipeline (see this tutorial) should work for 454 data.
The only issue I see is that there would be no 454-specific denoising steps. You could perform denoising steps with qiime1 first, then import the denoised fasta data into QIIME2 for clustering and downstream analysis.
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Hello - the data is from a collaborator, so I would have to ask about the fastq. In the meantime, I will try that pipeline. Thanks!
Hello, @LauraMason, @ebolyen
I have had good results with GitHub - indraniel/sff2fastq: extract 454 Genome Sequencer reads from a SFF file and convert them into a FASTQ formatted output. It converts .sff files to fastq and retains the quality information. If you are need any help running it let me know. I also know a few scripts if it needs to be demultiplexed before being converted.
I have someone interested in running DADA2 with 454 data so I would like to see this supported!
Best,
Joe Sevigny
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Hi Joe
I was able to perform demultiplexing and OTU picking in Qiime1 before moving my data into Qiime2 as a feature table. I may try that method next though to compare for myself OTU picking and the ASV method.
However, I have .fna files of reads, not .sff. Will this be an issue?
Cheers
Laura
Do you also have a separate file containing the quality scores? If yes, you will need to find a different converter (qiime1 has one) to merge the .fna and qual scores into one fastq file.
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