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Old 12-07-2009, 06:30 AM   #5
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Location: Purdue University, West Lafayette, Indiana

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Originally Posted by krobison View Post
You can find some commentary on this at my blog, Omics Omics.

I think the dismissive poster is missing that PacBio will, at least initially, be playing for different customers in different spaces, though also bumping up against some of established players (particularly 454). Very long read lengths & $100 as the atomic experiment size are quite different than the existing platforms. Perhaps there will be very few labs which would want a PacBio to the exclusion of the others, but it could well play a role as a complementary machine for a lot of projects.
Yes, but still... There was the possibility that the commercial launch of PacBio's machine would immediately obsolete all current platforms. It does not look like that will be the case. Just looks like we will be living through hyper-Moore's law decreases in price/base for at least several more years to come.

I do agree that $100 in reagents for an experiment does sound like a big deal. That suggests that total cost would be less than $500 for 50 megabases of data. A similar experiment would cost close to 5-10x that price on a 454 now. But, it may well be that that Roche can close that price gap in the upcoming year.

Informatics, as predicted by anyone who gave the issue much thought, looks more and more like a bottleneck. Longer reads do help with some aspects of informatics--mainly de novo assembly. You just spent your $100-$500 for 50 megabases of sequence. Now how much to convert that sequence into something that enables the user to plan the next experiment?

Depends on the application, of course. Point being that while informatics is a bottleneck, much of its narrowness derives from the the end user's ability (or lack thereof) to understand and utilize the data generated. This issue is compounded by the typical informatician's difficulty in understanding the biology the end user is studying. That is, both ends of this informatics->biology/biology->informatics pipe tend to lack understanding of each others limitations.

It is a big problem. But it is actually the meta-problem that is most dispiriting. That is: Not only do both ends lack understanding of each others limitations, but they also are unaware of this lack of understanding and how detrimental it is to coming up with any solution.

This cannot be the first time divergent disciplines have been forced to merge to deal with a problem. And the meta-discipline: how best to foster such a merger, that would be what? Some sort of process management? Anyone know?

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