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  • What is problem with this run?

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    What is problem with this run?
    The point is "Non-index read" data can't analysis.
    S502...etc cycle 160 is turn red and Miseq can't recognized index.
    Please help me.
    Last edited by Min Jung Lee; 03-17-2016, 01:03 AM.

  • #2
    It appears that the index read 2 in this run either failed or is not yielding much usable data. Your best bet to to contact Illumina tech support and let them have a look at the run remotely (if your machine is not connected to the net they may ask you to send them a set of files). They can help diagnose the issue (if it is hardware related) and suggest options.

    What chemistry version is this and what kind of libraries are these? If your libraries allow for it it may be possible to salvage some data based on tag read 1.

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    • #3
      I think that the flow cell density chart may show the signs of overclustering. I say this as your density increases from bottom to top. It should be highest at the bottom and decrease towards the top. Overclustering can lead to a artificial decrease in estimated density as clusters that are close together are interpreted as one. I think this problem can be made worse if your library is of low diversity.

      Is my HiSeq or MiSeq run overclustered? | Illumina Video:



      Diagnosing and preventing flow cell overclustering by Illumina:


      I have never seen those bright circular spots on any thumbnail images before either.

      You might have another problem. I recently had a library that was overclustered and/or of low diversity and had very low %PF (5-10%). I have never run an Illumina instrument myself so you may very well have another problem. Perhaps someone else with more practical experience can comment as to whether your data shows the signature of overclustering.

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      • #4
        I agree with Genomax-- your first step should be contacting Illumina tech support so that they can help you troubleshoot the run more specifically. If there are hardware issues, they'd be the best people to help you with that.

        Based on the data you've provided, it seems AT-GC is correct; the run appears to be overclustered. I'm basing that on the run summary, which states there are ~900K clusters/mm^2 , but with a PF rate of less than 50%. As AT-GC mentioned, it's very common to see an artificially depressed cluster density count when overclustered because the software can't resolve all the clusters present, so it just throws them out. The 900K number represents the clusters it can recognize, and of those, only about half are of good enough quality to pass filters, based on the data you provided. Also, the 2nd and 3rd images appear to have a lot of overlapping clusters. The first image, using the A filter, will tend to have less cross-talk with other bases which is why it appears cleaner than the other images.

        If there's not a lot of base pair diversity in the second index (depends on the adapters you selected) then that might explain why only the second index read is having the %Q30 issues that you're noticing-- it may just be that the second index is of much lower complexity. The rest of the library itself may be fine, it may just need to be diluted before you re-run it. I'd recommend re-quantifying it before you try. Also, check your adapter sequences and see if there might be issues with low complexity in one or both index reads. Keep in mind that it's not uncommon for Q scores in index reads to be lower than the non-index reads. This is especially true if you have a library pool containing only a few unique indexes.

        The bright spots in the first and third images may just be tile specific. I occasionally see the same thing on some of my runs-- a slightly hazy effect on a circular region of a tile that shows up in the same tile, on each cycle. I have assumed that it's probably a flow cell defect or something to do with the way the templates clustered. I usually don't see more than one or two on any given run that's otherwise passing (but mostly on rather densely clustered flow cells), and when I've contacted Illumina about these kinds of things in the past, they have explained that the software throws out that data (probably because it won't pass filters) but the effect is usually negligible. It doesn't affect a large enough portion of the run data to significantly impact flow cell yield, etc.

        The other possibility, if the issue is transient, is that you may just have dye blobs, but they aren't usually so circular. I've seen things like that before, and they're especially common on overclustered flow cells, for some reason, though my evidence for that is more anecdotal. It may be that I dig into failed/overclustered run data a lot more thoroughly and so if there are things like dye blobs I'm more likely to see them in overclustered runs. The main thing to check is whether the issue you're seeing is linked to a particular cycle of a run or tile of a flow cell. If it persists across runs and flow cells, then you probably have a hardware issue. All of the issues I have with these kinds of things don't persist beyond the run in which they're observed and they don't usually affect more than a small portion of one or two tiles.

        I'm attaching two images, one shows the same kind of circular haziness that some of your images have (but without the very bright spot). I see it only under the C filter on this run. The second image is most likely a dye blob and is visible on all four filters. The cluster density on this run was upwards of 900K/mm^2, PF rate was 90%+ and the run otherwise passed all of our specs. Neither artifact appeared on the run I started the very next day.

        I hope that helps.
        Attached Files

        Comment


        • #5
          Originally posted by GenoMax View Post
          It appears that the index read 2 in this run either failed or is not yielding much usable data. Your best bet to to contact Illumina tech support and let them have a look at the run remotely (if your machine is not connected to the net they may ask you to send them a set of files). They can help diagnose the issue (if it is hardware related) and suggest options.

          What chemistry version is this and what kind of libraries are these? If your libraries allow for it it may be possible to salvage some data based on tag read 1.
          Thank you for reply.
          I used Nextera XT prep. kit.

          Comment


          • #6
            Hi!
            Do you have the forth thumbnail image - would be very interesting ?

            Comment


            • #7
              Hi,

              Interesting thread.

              I have seen this with dust or water droplets on the flow cell surface - do you have a "leaky" flow cell connection for example - on the Miseq system itself?

              I have to say I doubt "Dye Blobs" - that sort of thing would not get through QC stage at manufacture.

              Comment


              • #8
                Originally posted by ATϟGC View Post
                I think that the flow cell density chart may show the signs of overclustering. I say this as your density increases from bottom to top. It should be highest at the bottom and decrease towards the top.
                Except that the Flow Cell chart at the left is not displaying Cluster Density, it is showing per tile Intensity, Cycle 1, Channel A.

                Looking at the Density box plot (bottom, middle) as well as the run summary table it shows that the raw, per tile densities are in a tight distribution around 920K/mm^2. On over clustered flow cell you normally see a very broad range of raw densities per tile. I don't believe this flow cell is over loaded.

                Comment


                • #9
                  I apologize. You are right kmcarr. I think my brain filled in a few of those grainy pixels and read density instead of intensity. That explains why the gradient scale is not a sensible number for cluster density.

                  Comment


                  • #10
                    Originally posted by kmcarr View Post
                    Looking at the Density box plot (bottom, middle) as well as the run summary table it shows that the raw, per tile densities are in a tight distribution around 920K/mm^2. On over clustered flow cell you normally see a very broad range of raw densities per tile. I don't believe this flow cell is over loaded.
                    I respectfully disagree. I think the box plot is perfectly consistent (as are the images) with an overclustered flow cell on a MiSeq.

                    The last run I overclustered (which granted, it's been a couple years), had a cluster density of 1319 +/- 32. The PF rate was also in the 40%s. I just had a run the other week that came in at 907+/-16, PF rate 90%+. Other runs with lower cluster densities have even tighter distributions.

                    I do seem to recall some HiSeq runs (from back when I worked with HiSeqs) that behaved the way you describe, where the cluster distribution is much more broad on overclustered flow cells, but that doesn't seem to be the case with MiSeqs, at least not in my experience.

                    I should add that all of what I've said applies to MiSeq v2 chemistry, as that's what I'm using. There may a different root cause for the run failure, as I'm not very familiar with the v3 chemistry-- shouldn't the intensity plot look a bit different than it does? I thought they were supposed to have a general upward trend, but maybe that's only for longer (i.e. 600bp) runs? Still, the images and the low PF rate look like overclustering to me.

                    Comment


                    • #11
                      I think it looks overclustered but I usually run amplicons so am aiming for 700-800k. I've had a string of runs fail with horrible index 2, it seems like mine is related to the tm of my custom primers which is a bit low (these are common custom primers though and the bad runs are recent). My issue seemed to be fixed by increasing my primer spike in and decreasing my loading concentration (last run was 700k and worked well)

                      Look at your metrics between top and bottom-I bet your PF on the bottom is way worse than the top (something I've seen with overclustered runs)
                      Microbial ecologist, running a sequencing core. I have lots of strong opinions on how to survey communities, pretty sure some are even correct.

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