bioinformatics, genomes, biology etc. "I don't mean to sound angry and cynical, but I am, so that's how it comes across"

Why nanopore sequencing errors aren’t actually errors

Let me start by saying that what I’ve written below are opinions formed after many conversations with many different people, including some from ONT, over the last 2-3 years.  I don’t want anyone to think I am stealing their ideas – but I think it’s important to get them out there.

Oxford Nanopore’s technology, currently available in the MinION device, is the only sequencing technology to directly sequence an actual strand of DNA.  Every other technology sequences incorporation events into a template strand (including Sanger, Illumina, Ion and PacBio) – and invariably those incorporation events involve the canonical bases, A, G, C and T.  However, in nature, DNA is much more complicated than that – there are base modifications and base analogues.  The MinION (and other ONT sequencers) is the only sequencer that directly detects those modifications and analogues.  However, what we do when we “base call” the raw ONT data is to compress it from natural-DNA-space into canonical-AGCT-space, and whenever we compress we lose signal, and that lost signal turns up in the system as noise – as so-called “error”.  People talk about the error rate of the MinION being around 10% – but not all of it is error, some of it is signal, signal for something we don’t quite understand yet so we’re interpreting it (wrongly) as AGCT.

That’s one of the exciting things about nanopore sequencing that no-one is talking about.  Oxford Nanopore’s sequencers could possibly reveal a whole new alphabet for DNA that we didn’t know about before – and my bet is that it’ll explain some of what we currently struggle to understand in genetics and genomics.


  1. do you think we’re heading into the new frontier of epigenomics? and if so what are the implications?

  2. Actually, Mark Akeson has been talking about reading modified bases with nanopores for years. There is some real signal there, easily identified in known sequences, but doing base calling with a larger alphabet is more difficult—too many different sequences produce very similar current traces.

    But much of the error rate in nanopore sequencing is still due to the stochastic motors used for slowing down the DNA translocation—missing bases or reading them twice. That is still noise, not signal.

    Another major source of errors is misinterpreting the current levels—the ONT base callers do a pretty good job of deconvolving the signal from the nanopores, but there are still ambiguities, even with pure ACGT bases in the DNA. Increasing the alphabet size will increase this sort of error.

  3. Have you done any experiments with dna that is methylated or hydroxymethylated to see if that is the signal you get from it?

  4. There’s still work to be done for sure. But nanopore is the technology that’s going to get us closest to detecting known and unknown modifications and base analogies.

    As for methylation, I’ve seen data, not Akeson’s and not ONT’s, and calling methylation on nanopore is going to become the default method. The signal is pretty clear and I suspect you’ll see a publication on it this year.

  5. I and others have, yes. It works.

  6. Bertrand Jordan, Marseille

    11th September 2015 at 9:28 am

    In the early days of DNA sequencing (late 70s – early 80s), a fair amount of data was acquired using the Gilbert-Maxam method (partial degradation of labelled DNA by Hydrazine or DMS, then reading of the sequence ladders on gel) that does not involve copying the DNA (I did a lot of GM sequencing at the time). I don’t think any significant discrepancies were seen between sequences acquired this way and sequences from Sanger sequencing – so my impression is that we don’t miss much with the current techniques and that the 10% error rate on the MinIon does not represent “non-canonical” DNA (or only a very small fraction of it)

  7. I think Nick’s estimate is conservative, and comes in about 3%, estimated from comparing MinION sequencing of raw vs PCR-ed DNA samples.

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