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Old 09-24-2018, 05:11 AM   #4
GenoMax
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Join Date: Feb 2008
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Low nucleotide diversity in this case means majority of clusters will have e.g. an "A". When that happens the ability of the image analysis software to distinguish among clusters is hampered which then can lead to poor Q scores.

I assume this is a V3 reagent run (since you have 1100 k/mm^2 cluster density). While it is possible to push the limit of cluster density (with good/diverse libraries) the fall over the cliff (in terms of Q score drop) is precipitous.

Have you analyzed the data to see if your assumption in #2 above checks out. In general, smaller fragments will cluster efficiently and will out compete larger ones every time. Since you have a reference genome available you can use the method described by Brian in this post to actually find the real insert sizes in your data. It would be interesting to see what the results look like compared to your expectation.

Can you show us what the "Summary" looks like for phiX alignments in that third tab?

Last edited by GenoMax; 09-24-2018 at 05:13 AM.
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