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  • james hadfield
    Moderator
    Cambridge, UK
    Community Forum
    • Feb 2008
    • 224

    Finally a nanopore sequencer that works

    Hi All,
    The Nanopore buzz and hype have got lots of us thinking about what we migt be doing in another year or two and offer us the tantalising ability to sequence genomes at fractional costs comapred to today. However it is all taking a little longer than we might like. To try and lighten the mood I posted on April 1st about a new Nanopore sequencing company. I hope you like it.



    Today I was given an exclusive preview from the newest nanopore sequencing company on the planet, Norfolk Nanopore Technology. The new "Polo...


  • GenoMax
    Senior Member
    • Feb 2008
    • 7142

    #2
    All disruptive technologies start in this realm.

    I remember listening to a presentation from Solexa at ISMB (perhaps 2004, I can't remember the exact year) and thinking no way is this going to work in practice. And here we are today ...

    Let us hope one of these nanopore sequencers makes it as a real product to the market .. soon .. so we can move on and start the anticipation for the "next" generation.

    Comment

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    • GATTACAT
      Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
      by GATTACAT
      Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
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    • SEQadmin2
      Nine Things a Sample Prep Scientist Thinks About Before Sequencing
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      I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.

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      Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.


      The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
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