The error rate is stupidly high (somewhere between 10 and 20%) compared to Illumina or Ion Torrent who give error rates far less than 1%.
It can give very long reads, which are useful in some niche applications. But it’s been massively over-hyped (and over capitalized).
The neat thing is that it’s very small. But that isn’t really compelling given the very low accuracy.
This is not a "full" human genome, but a collection of 150bp fragments that can be realigned to an existing human genome. You cannot take this and infer the whole diploid genome of the individual. There is a huge amount that will be missed, and all of our current knowledge is based on this gappy picture of what's going on in single genomes and human populations.
> It can give very long reads, which are useful in some niche applications. But it’s been massively over-hyped (and over capitalized).
I think you're dismissing the technology out of hand because of biases derived from much more limited short-read technology that only allows us to reliably see small variants <50bp.
Without these long reads we can't see structural variation (SVs). There is an increasing amount of evidence that much of adaptive variation is driven by these kinds of variants. If you want recent evidence, see https://www.nature.com/articles/s41588-017-0010-y. There has long been evidence that there are huge copy number variations in humans, but these are still not evaluated reliably: http://science.sciencemag.org/content/330/6004/641.
We should be open to the possibility that our observational techniques are limiting our understanding how how genomes work. This has consistently occurred in the history of every observationally-driven science.
It's amusing to me that people assume that SVs are "niche" when even the limited surveys of genomes we've been able to do with short reads show that roughly an equal number of base pairs in the human population vary due to small variants like SNPs and indels and big ones like deletions, insertions, and large scale copy number variation: http://science.sciencemag.org/content/330/6004/641
There is, likely value in long reads, but what non-niche research applications are there for highly error’d reads that justify a valuation of several billion dollars?
For things approaching a read length the per-base error rate of a single read is simply irrelevant. In practice, with sufficient coverage (e.g. 20x) you simply don't care about the per base error rate of the reads.
The area where DNA sequencing will first be revolutionizing clinical practice is in sequencing pathogens for sake of identification. In these instances nanopore sequencing rules, because it can give answers in minutes.
The most compelling near term applications (NITP etc) use fragmented DNA, and long reads will have no benefit here.
So, yes. Long reads are useful, but you need to have at least reasonable performance in other respects. The same thing has been seen with PacBio, who have not played well in the market, despite having a read length advantage.
With sepsis, every hour counts.
Most structural variation I've seen based on whole genome assemblies is not even classifiable into neat categories like "deletion" or "insertion". If you think that "most" things are detected with short reads then you are deluded by the dominant technology.
The Insertion/deletion error rate is 20-30%.
The point mutation error rate is something 0.1-1% (higher than HiSeq but not crazy high).
This means with a semi-decent reference genome you should be able to do re-sequencing fairly accurately. It also means, that in conjunction with HiSeq reads you can do cheap genome assembly, using the HiSeq reads for coverage, and the minion reads for scaffolding.
I was able to get about 1-10% mutation rate, with a median of about 1.5%. Rate depending on quality of the run. In general it was on par with PacBio.
The mismatch rate is much lower. But it's hard to calculate exactly the mismatch rate when the indel rate is so high.
Are you using it for fun? professionally? academically?
Reagent kits run a few hundred dollars depending on what your doing and you get several uses out of them.
IIRC it's not certified for use as a medical diagnostics device so it's "research only".
It's a nice system with great (none) upfront costs that has a lot of potential. But read quality and quanity per dollar aren't as good as what we get with our NextSeq (which by contrast costs something crazy like 300-400k)
The problem here is that everything in that pipeline keeps improving at a fast base. Also the reference databases are updated all the time. Whereas sequencing will probably always give the right answer to the precise question it was given, I don't see any luck in certifying these methods any time soon.