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  • MiSeq lower quality on the bottom surface

    Hello all,

    Just wondering if anyone else that uses a MiSeq has observed this issue? We invariably see that the error rate and quality scores are worse on the bottom flow cell surface than the top.

    In our current run, the difference is stark and will probably lead to the run failing to meet Illumina's quality standards.

    Here is an example of some of the plots:


    Cluster density was 1430K/mm2 but with only 75% passing filter.
    Kit is a 2x300 v3. Samples are NexteraXT from gDNA.

    To me it looks like a problem with focussing on the bottom surface - leading to a failure to accurately pick out clusters and also subsequently call the sequences.

  • #2
    look at your FWMH-that if it's a focusing issue it will show up there. The intensity is lower on the bottom-maybe your error rate is higher just because of the lower intensity.
    Microbial ecologist, running a sequencing core. I have lots of strong opinions on how to survey communities, pretty sure some are even correct.

    Comment


    • #3
      Here are the FWHM plots:



      The bottom surface is broader and spikier - but not sure if this is a significant (meaningful) difference.

      By the way, final stats for the run were as follows:

      Code:
       Run Summary
      Level	Cycles	Yield	Proj	Aligned	Error	Intens	% >= Q30
      Read 1	300	7.42	7.42	0.85	4.31	184	67.91
      Read 2	8	0.17	0.17	0.00	0.00	469	90.70
      Read 3	8	0.17	0.17	0.00	0.00	423	85.89
      Read 4	300	7.42	7.42	0.78	6.07	171	54.65
      NI Tot	600	14.85	14.85	0.81	5.19	178	61.28
      Total	616	15.20	15.20	0.81	5.19	312	61.90
      
      Lane	Tiles	Density (K/mm2)	Cluster PF (%)	Phas/Prephas (%)	Reads (M)	Reads PF (M)	% >= Q30	Yield (G)	Cycles Err Rated	Aligned (%)	Error Rate (%)	Error Rate 35 cycle (%)	Error Rate 75 cycle (%)	Error Rate 100 cycle (%)	Intensity Cycle 1
      Read 1
      1	38	1430 +/- 36	74.39 +/- 13.26	0.286 / 0.053	33.24	24.83	67.91	7.42	299	0.85 +/- 0.13	4.31 +/- 0.89	0.28 +/- 0.16	0.79 +/- 0.65	1.02 +/- 0.78	184 +/- 15
      Read 2 (I)
      1	38	1430 +/- 36	74.39 +/- 13.26	0.000 / 0.000	33.24	24.83	90.70	0.17	0	0.00 +/- 0.00	0.00 +/- 0.00	0.00 +/- 0.00	0.00 +/- 0.00	0.00 +/- 0.00	469 +/- 127
      Read 3 (I)
      1	38	1430 +/- 36	74.39 +/- 13.26	0.000 / 0.000	33.24	24.83	85.89	0.17	0	0.00 +/- 0.00	0.00 +/- 0.00	0.00 +/- 0.00	0.00 +/- 0.00	0.00 +/- 0.00	423 +/- 113
      Read 4
      1	38	1430 +/- 36	74.39 +/- 13.26	0.140 / 0.023	33.24	24.83	54.65	7.42	299	0.78 +/- 0.10	6.07 +/- 1.33	0.51 +/- 0.24	0.79 +/- 0.38	0.95 +/- 0.43	171 +/- 49
      Last edited by M4TTN; 10-13-2015, 11:47 PM.

      Comment


      • #4
        I just looked through several of my runs (and my machine has focusing issues) and I don't see that much difference between the 2 surfaces. Have you sent this run to tech support yet? I think your q30 is below spec but run v2 500 cycles so don't know for sure the cutoffs for the 600 cycle kit.
        Microbial ecologist, running a sequencing core. I have lots of strong opinions on how to survey communities, pretty sure some are even correct.

        Comment


        • #5
          Yes, we've contact tech support. They responded last week, but nothing since...

          The run is definitely below spec. When using v3 chemistry, the published specs state 2x300 should generate %Q30 >70%

          We've actually had a few runs replaced due to dropping below 70%, but I don't think any have had such a massive different between top and bottom of the flow cell.

          Overall, our read4 is also always worse than read 1 (but I understand that is expected due to the turnaround step that broadens/merges clusters slightly).

          What I don't really get, is that our first ever run gave extremely good data (Q30 > 80% I think), but we've not since been able to achieve that level even after 2-3 engineer visits.

          Comment


          • #6
            Unless you are sequencing the same library (where you got 80+% Q30) there is no specific reason to get that PF everytime. That metric is going to be library quality dependent.

            Comment


            • #7
              Indeed, these are different samples each time.

              Any idea what might have caused the first library to be so much better?

              We prepare genomic DNA by a similar method each time and prepare samples using NexteraXT.

              Even when we get good clustering (25 M) and good % passing filter (>90%), the resulting Q-scores never hit what that first run gave us.

              Perhaps it is simply variation in insert-length due to variation in the Nextera efficiency?

              In any case, none of this explains (I don't think) the lower quality on the bottom surface. Something that happens from time to time - and when there is a difference it is always the bottom flow cell surface that is worse.

              Comment

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