Just wondering if there is anyone out there who is using MGI-derived amplicon data on the QIIME2 pipeline?
I have predominantly used Illumina in the past and am seeing some differences, particularly with DADA2 quality scoring. I realise this tool is trained with Illumina data which may be causing some of the issue, but would love to hear if anyone else has had experience with MGI derived data.
DADA2 actually estimates quality scores on a per-run basis, so it's not tied to the instrument necessarily.
I haven't worked with MGI data, but you would expect to see some differences between runs on the same instrument, so it may not be too much of an issue.
What kind of differences are you noticing?
The main one being the quality of R2. Very jaggy. But look at the FastQC, she looks exactly like we would expect illumina data.
Just trying to puzzle out what could be causing the difference
To clarify, the qiime quality plot and the fastqc quality plot look different for the same data? Would you mind attaching the fastqc plot?