What is the current consensus accuracy for PacBio?
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PacBio claims >99.999% (which I think is based on 50X coverage) due to their random errors. If ONT has random errors (or can get 'differently biased' errors from more than one pore type), then they should be able to have a very high consensus error rate as well. But I still haven't seen a clear claim of a random error model from ONT.
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Consensus is not that good with ONT at the moment, mostly because the base calling model has consistency issues with particular pentamers (with AAAAA being a particularly good/poor example) -- we were only able to manage 99% with our Influenza genome.
I still maintain that this is a software issue, and that by throwing enough excited programmers at a proper base caller, we'll be able to re-call old reads and demonstrate that the accuracy was there all along.
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I think the most important advantage of PacBio over Nanopore is the ability to do consensus for individual reads. This is fundamental and will not change with future iterations of either platform.
There is no single "consensus accuracy" for PacBio. For all-to-all mapping, the more data, the more accurate... and for shorter inserts, the more passes, the more accurate. Considering reads of insert, which are only corrected via self-consensus, the longer the raw read length, the more accurate it will be. And the raw length is increasing rapidly with new chemistry advances.
Both Nanopore and PacBio can do all-to-all mapping for error-correction. In this situation PacBio has a huge advantage in that the errors are more randomly distributed. But Nanopore can only do self-correction with 2 passes. PacBio can do self-correction with an arbitrary number of passes, proportional to the movie length versus insert size. Therefore, things like accurate full-length 16S sequencing are already possible for PacBio, but will never be possible for Nanopore.
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Isn't that just a chemistry thing though? PacBio is a sequencing-by-synthesis method after all, and I don't see any reason why Circular Consensus Synthesis couldn't be done on nanopore as well by generating the sequence prior to putting it through the sequencer.
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Originally posted by gringer View PostIsn't that just a chemistry thing though? PacBio is a sequencing-by-synthesis method after all, and I don't see any reason why Circular Consensus Synthesis couldn't be done on nanopore as well by generating the sequence prior to putting it through the sequencer.
If there was some way to make replicates of a read linked together in a giant molecule, then yes, Nanopore would be able to make CCS reads. But such a thing is not possible today, or in any claimed future developments.
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Originally posted by Brian Bushnell View PostIf there was some way to make replicates of a read linked together in a giant molecule, then yes, Nanopore would be able to make CCS reads. But such a thing is not possible today, or in any claimed future developments.
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Originally posted by Brian Bushnell View PostIf there was some way to make replicates of a read linked together in a giant molecule, then yes, Nanopore would be able to make CCS reads. But such a thing is not possible today, or in any claimed future developments.
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Originally posted by gringer View PostThis is very close to the current cost of MinION sequencing. It wouldn't surprise me if that weren't a coincidence.
A great MinION run will currently put out about 1Gbp of sequence, but that will change substantially after fast mode kicks in (about 20x sequencing speed). I wonder how flexible PacBio are with their pricing for the chip and reagents.
Of course, ONT is the only game in town for the portable market. I think that will be where its niche is until it can improve accuracy significantly.
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Originally posted by ymc View PostBut for de novo assembly, only ONT 2D reads can be used. That means usable throughput for de novo assembly is only about 20%.
While 1D reads are not particularly useful now, I have hope that a bright mathematician or computer scientist from outside ONT will substantially improve the base calling model. That will allow all those "useless" 1D reads to be retroactively recalled with much improved accuracy in the future.
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Originally posted by ymc View PostIf the pricing remains $1000 per box, it is still not competitive
There's a new flow cell design coming out in the next 6-12 months with six times the number of pores and a substantially lower marginal cost, currently projected to be $20 USD for a short 3-hour run producing 2Gbp. I expect that would mean about $100 to run the flow cell for as long as it can go.Last edited by gringer; 10-09-2015, 05:41 AM.
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Originally posted by gringer View PostIt's currently $500 USD per flow cell if ordering in bulk, with reagent cost ~$200 per run, so basically the same marginal cost as the Sequel (ignoring initial equipment cost).
There's a new flow cell design coming out in the next 6-12 months with six times the number of pores and a substantially lower marginal cost, currently projected to be $20 USD for a short 3-hour run producing 2Gbp. I expect that would mean about $100 to run the flow cell for as long as it can go.
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Originally posted by Brian Bushnell View PostIf there was some way to make replicates of a read linked together in a giant molecule, then yes, Nanopore would be able to make CCS reads. But such a thing is not possible today, or in any claimed future developments.
Nanopore sequencing provides a rapid, cheap and portable real-time sequencing platform with the potential to revolutionize genomics. Several applications, including RNA-seq, haplotype sequencing and 16S sequencing, are however limited by its relatively high single read error rate (>10%). We present INC-Seq (Intramolecular-ligated Nanopore Consensus Sequencing) as a strategy for obtaining long and accurate nanopore reads starting with low input DNA. Applying INC-Seq for 16S rRNA based bacterial profiling generated full-length amplicon sequences with median accuracy >97%. INC-Seq reads enable accurate species-level classification, identification of species at 0.1% abundance and robust quantification of relative abundances, providing a cheap and effective approach for pathogen detection and microbiome profiling on the MinION system.
[I hope the authors don't mind sharing links to this]
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