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  • If I use different type of samples in a seq lane - will that introduce a bias?

    Hi all

    I m about to sequence 50 samples (shotgun metagenomics) from animal feces (complex metagenomes) using the novaseq 6000: apx 2.5billion reads in each direction. That way I estimate to have apx 50million reads per sample.
    I would like however to add 2 positive controls from pure cultures (probably known E.coli strains that we have in the lab). That way i can check if everything is what it should. By adding 2 extra samples I will then have 52 instead of 50 samples in a single lane which will drop the output to apx 48million reads per sample (I can live with that).
    My question is: since often some samples end up having more reads than others, do I introduce a bias in this sequencing run and therefore is it probable that my 2 pos controls will have way more reads than the rest of my 50 samples? if they have less reads, i dont care but if they have much more and i end up having a reduced output for the remaining 50 samples that would be a problem...

    thanks
    P

  • #2
    This is all going to depend on how good your libraries are and how well balanced a pool you (or your sequencing provider) can make. There should be no bias in data per se just because of how you pool.

    With a large pool of samples I hope you are planning to use dual indexes. If you are particular about getting a balanced pool then running a small iSeq/MiSeq nano run to check the pool balance is well worth doing before final NovaSeq run.
    Last edited by GenoMax; 08-13-2020, 02:57 AM.

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    • #3
      the seq provider will take care of the library prep - all I have to do is send the DNA to them, but yes i hope they ll use dual indexes. I honestly hope that they know what they are doing but the truth is I have no choice but to use this company because my collaborator (who will cover 60% of the cost) has an ongoing collaboration with them.

      Thus, bottomline is that theoretically, if they use equimolar concentrations of the samples and index it properly, sample type should not be a problem? glad to hear that.

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      • #4
        Rule of thumb is small inserts (and primer dimers) cluster well. So as long as the insert sizes are more or less uniform (and there are no dimers) your results will be as uniform as the pool they can make.

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        • #5
          ok, got it, thanks! I ll probably contact them before the sequencing to ask about the library prep

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