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Old 07-11-2021, 04:13 AM   #1
Zimtblatt
Junior Member
 
Location: Switzerland

Join Date: Jul 2021
Posts: 1
Question New to 16S Seq on MiSeq

Hello Everyone!

I'm Zimtblatt and I am happy to have found this community.

I'm from a biology background and have been analyzing 16S data (obtained from a sequencing company) for a previous project with QIIME.

Now I am working in a lab that is using a MiSeq for other purposes and the idea is that I establish the 16S RNA sequencing on the MiSeq for analysis of human fecal samples there.

By now I have prepared a library (V4 primers, library prep according to the Illumina 16S protocol, 5% PhiX spike-in) and did a first run on the MiSeq (v2nano, 2 x 250).
The run looks much worse than the data we obtained for the previous project from the sequencing company (which is probably exceptionaly clean), but I am not sure whether the data quality is so bad, that it is a problem (QC>30 is 76.8%, for more information please see attachments) that should be tackled at the library prep/sequencing step or whether I can cope with the data by filtering.
I can only say, that the quality control step in QIIME2 (with dada2) takes much longer, in fact so long, that my laptop is unable to cope and I get an error message.

If the data quality is not good enough, the next questions are, how to improve sequencing and library prep. The run does not look overclustered (875 K/mm2). Should I consider increasing PhiX spike-in? (According to recent posts, a high PhiX spike-in does not seem to be necessary any more with up-to-date Illumina software).
Please let me know, if you need any further information.

I am fully aware that these are very basic questions and I would be happy about links to reliable resources, for learning these basics.

Thank you very much for your help!

kind regards,

Zimtblatt
Attached Images
File Type: png SAV run summary.png (34.6 KB, 0 views)
File Type: png SAV data by cycle.png (141.7 KB, 0 views)
File Type: png Q-Score distribution and heatmap.png (146.0 KB, 0 views)
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16s illumina analysis, phix, quality control

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