How many sequencers has Oxford Nanopore sold? It seems like it has perennially been a “in the next few years” technology.

I'm not sure how many they've actually sold but i do know that they have a loan/test program where you can pay a relatively small amount (around $2000 or less) to get set up with a MinION kit. The main recurring cost is the flow cell. I'm currently trying to figure out how to join together short multiplexed samples (150bp - 200bp) and get it sequenced on the MinION. Current short-read sequencers from Illumina or ThermoFisher cost orders of magnitude more than Oxford Nanopore's offering. Hopefully someone else is trying to use the platform for short reads.

Have a look at SAGE (https://en.wikipedia.org/wiki/Serial_analysis_of_gene_expres...), might give you some ideas for joining short reads. I suppose you'd want to look for a restriction enzyme that creates average fragment size in your desired range.

I got mine as part of the beta almost two years ago. It's been in release since, and seems popular in the community. It's not Illumina HiSeq popular, but the cost is low enough that lots of people are experimenting with it.

Nanopore sequencing is definitely "already here" in the sense that they're selling a lot of flow cells and people are doing useful research with ONT instruments but it's also a niche technology compared with Illumina.

As someone who's only casually interested in this field, what are the prospects of any of these upstarts actually unseating Illumina from the throne?

They currently specialize in different things. The larger Illumina instruments have a huge up-front cost (~$1M), tremendous throughput, low cost per base, short reads, <1% base error, and significant latency between starting sample prep and getting results back. Nanopore sequencing has trivial up-front costs, same-day results, orders of magnitude higher cost per base, >10% non-independent error rate and very long reads.

ONT will be much more useful for assembling reference genomes (which can then be polished with short reads), characterizing large scale structural variants, and real time applications like "what pathogen am I infected with?".

I expect us to use the long reads from ONT and PacBio to discover that structural variation is even more important and common than previously appreciated. If that's the case, you'd be silly to use the Illumina technology for anything more complex than population genetics, and this will probably trickle into many parts of the market as the medically-relevant parts of the field realize what the basic science is demonstrating.

The fact is, unfortunately, that Nanopore sequencing (and also, from what I’ve read, PacBio) has a dramatically higher error rate than Illumina sequencing-by-synthesis. In the near future, anyway, I would expect to see inaccurate PacBio/Nanopore long reads being used as scaffolds for accurate Illumina short reads (in fact, this is already happening). Illumina won’t be going anywhere any time soon.

>The fact is, unfortunately, that Nanopore sequencing (and also, from what I’ve read, PacBio) has a dramatically higher error rate than Illumina sequencing-by-synthesis.

This is true, but only for Insertions/Deletions. The substitution error rate is comparable to Hi-Seq.

So it's good for resequencing but without a reference or decent scaffolds, you're in the dark.

I've only sequenced a few samples on a MinION. The dominant error seemed to be miscounting the length of a homopolymer stretch (e.g. CCC->CCCCC) but the substitution error rate was also clearly worse than Illumina. I've gotten used to less than 0.1% error from DNA sequencing on a HiSeq 2500. My guess is that the MinION data had 1-3% substitution errors.

The simple explanation is that they are different products that only overlap to a limited degree.

If you're doing a standard RNA-seq experiment, short 100bp to 200bp Illumina reads are just dandy for what you need. Most of the time, at least; you could, for example, be interested in different splice variants for a gene family; in that case longer continuous reads are valuable. But then it's no longer a standard RNA-seq.

PacBio and pore-type sequencing is most valuable for polishing reference genome assemblies. For instance, this is a huge issue for crop plants because they have huge, repetitive genomes and are often polyploid. So there's a lot of interest in creating high quality assemblies not just for e.g. corn, but the major research inbreds (B73, Mo17, etc.) as well as private breeding lines. Some of the most valuable crop QTLs (R genes, microRNAs, transposon fragments, etc.) are just 'junk' sequence that plays a regulatory or defense role, so it's super important.

In general, the Illumina data is very high quality and very inexpensive, and works beautifully provided you have a high-quality assembly to work with, and what you're interested in isn't very repetitive. It has many good applications, so I don't see much risk at this point.

If, at some point, longer reads can be done with high fidelity and with similar cost, then there would be an issue. I don't think that's going to happen anytime soon, but I'm sure Illumina is looking at that long-term.

PacBio and ONT are far from upstarts, they have both already invested millions and millions into their respective technologies. Pacific Biosciences has a Market Cap of 532.88M Oxford Nanopore is at least as big.

I've personally prep libraries and used nanopore. While there is a lot of promise to the technology, I found it to be too inconsistent. Nanopore claims they can get 10gigs of data, while power users claim they get 2-5gig on average. I consider myself lucky if I get 2gigs of data.

The non-random nature of their error profile is also a problem.

Are those experiences on recent chemistries/flow cells? My first library prep gave me ~4 gigabases on a R7.4 flow cell and that was pretty low compared with everyone else in the workshop.

Also, which library prep are you using? I think the ligation kit has historically gotten better yield (not sure if that's true any more).

Are you working on cell lines or bacteria? Genomic dna? I find most people that tell me they get good data yield are working on samples where dna extraction is relatively straightforward and dna yield is abundant.

I used the flowcell version previous to the current one and got ~2gb of data. I used the ligation kit on genomic extraction of ~10 individuals (crustacean).

The new rapid kits (R3) have significantly worse performance than the R2 kits it seems.

I'm also extremely put off by how they handle support -- that is via a forum where they do their very best to barely answer anything

I agree about their communication and support. It does seem like they put all their support behind the few big labs in the UK that are actively using nanopore (free R&D for them I guess). I get a sense of "if you can't get this to work, then you are just a bad scientist" vibe from them.

The problem is Oxford Nanopore data has about a 30% insertion and deletion error rate. While PacBio is less than 1% indel and substitution error.

Don't get me wrong, the Minion is amazing, but it can't compare to PacBio in terms of quality... yet.

The error rate of recent nanopore data is much less than 30%. See here for a recent benchmark: https://github.com/rrwick/Basecalling-comparison

Interesting, I haven't tried it on the newest chemistry but last time I did a flowcell (earlier this year) that was the INDEL error rate we achieve.

Substitution error rate was very low, but you should evaluate INDELs specifically, rather than just identity like you did on your git, because it is the major drawback of this technology.

Just to be clear this isn't my analysis - and yes most of the errors here are due to indels.