A few of us from the Discord have been working on this DNA sequencing feature/pricelist. This is always a bit of a struggle, as some vendors can be less than explicit about pricing. But usually the platform specs are failure clear.
PromethION has an open front end where users run any kind of sample or prep. Without amplification in some cases. Therefore the front end is variable, that is a feature and comprises many of the customers. The only way they can provide specifications is by locking down the front end, homogenising the sample preps and fragment lengths, i.e. unpicking the main features that people buy the platform for. It is not difficult to run a library on this technology, then extrapolate how it is running from the first hour. If it isn’t on track the run can be stopped, flowcell flushed and a new library loaded so there is no risk/cost to having a open front end unlike other platforms where the run is committed once the sample is attached to the flowcell.
I don't think this is a reasonable excuse for not providing throughput estimates for particular workflows. It is of course natural that this may vary across sample type. But for example, if you're doing whole human genomes for rare diseases testing in a process where you control the sample collection... you should be able to provide a protocol (including sample collection if you want!) and throughput estimate...
Yes - but the plot that Nava worked off of that I photographed at LC was one center running a single sample type prepared with the same protocol. So yes ONT by having an open front end has a hard time having a performance guarantee, but it doesn’t change that their flowcell performance is highly variable
Academics are willing to flush flowcells; industrial and clinics basically aren’t - their labor isn’t treated as free & there are quality/carryover concerns . The group that made this plot was quite adamant that they needed one sample load per flowcell delivering 30X human coverage
ONT is releasing as beta a new PromethION flowcell with different buffer soonish - that is supposed to increase yield and I think (but don’t seem to have a photo) to improve consistency
PromethION has an open front end where users run any kind of sample or prep. Without amplification in some cases. Therefore the front end is variable, that is a feature and comprises many of the customers. The only way they can provide specifications is by locking down the front end, homogenising the sample preps and fragment lengths, i.e. unpicking the main features that people buy the platform for. It is not difficult to run a library on this technology, then extrapolate how it is running from the first hour. If it isn’t on track the run can be stopped, flowcell flushed and a new library loaded so there is no risk/cost to having a open front end unlike other platforms where the run is committed once the sample is attached to the flowcell.
I don't think this is a reasonable excuse for not providing throughput estimates for particular workflows. It is of course natural that this may vary across sample type. But for example, if you're doing whole human genomes for rare diseases testing in a process where you control the sample collection... you should be able to provide a protocol (including sample collection if you want!) and throughput estimate...
Yes - but the plot that Nava worked off of that I photographed at LC was one center running a single sample type prepared with the same protocol. So yes ONT by having an open front end has a hard time having a performance guarantee, but it doesn’t change that their flowcell performance is highly variable
Academics are willing to flush flowcells; industrial and clinics basically aren’t - their labor isn’t treated as free & there are quality/carryover concerns . The group that made this plot was quite adamant that they needed one sample load per flowcell delivering 30X human coverage
ONT is releasing as beta a new PromethION flowcell with different buffer soonish - that is supposed to increase yield and I think (but don’t seem to have a photo) to improve consistency