As a beginner in QIIME2 i'm encountering some problems. I'm trying to analyze data I got from 2015, but the raw data are deleted and can't be found, all I have is 1 .fastq file for each sample assuming it's a forward read single end file, I used to run them in QIIME1 with no problem,. But while importing I always get the error /se-33-manifest.csv is not a(n) SingleEndFastqManifestPhred64 file: The manifest file was created strictly according to the instruction. I've tried both SE33 and SE64. And while comparing the sample data provided with my data, the format looks quite different, my question is what format is my fastq file? And which procedure should I use to import it in QIIME2 for otu generation. Screenshot of my data is attached. Any help is appreciated. Many thanks!!!
This indicates that the problem is most likely your manifest file, not the fastq files. The fastq files look fine, though those quality scores look really bizarre and you should confirm that you are using the correct Phred offset.
What version of QIIME 2 are you using and what is your import command?
Hi Evan @ebolyen , sorry for the late reply, it was produced by Illumina miseq, I just send them in to the sequencing company and they take care of it, do you mind elaborating a bit more for them being bizzare? Are they bad? In what sense? Thanks
as the tutorial site specified but of course with file path changed. In what sense are the quality score bizzarre? are the qualities low? Because I usually just isolate the dna myself and send it in to a sequencing company and they take care of it from there, its produced by Illumina Miseq. Yes maybe the Phred offset is wrong, I’ll have to confirm it with them as it was so long ago. Thanks for the advice!
Hi guys @Nicholas_Bokulich@ebolyen , I'd like to attach the fastq files but its over the limit of 40 mb, here is a screenshot of another sample of another batch but from the same sequencing company, are these bizzare too? Because I've been using them for analysis for a long time, I hope there aren't any fundamental errors in them. Thanks for all the help.
Yes, those quality scores look pretty much the same. It does not necessarily signal anything "bad", it just looks very abnormal (and could just be because you are sharing a screenshot, not a plot of quality score distributions such as qiime demux summarize would report). The quality scores are very homogeneous and (depending on your PHRED offset) very high quality.
