 Okay, so this next agenda item was actually only scheduled on late Thursday afternoon. It was originally going to be the introduction to the closed session discussion of the review of the sequencing programs, but when Adam ran through it of course to practice, it seemed to me that what he was saying in terms of the history and current status of the large scale sequencing program was actually be pretty useful to talk about in open session. So what the presentation here is going to be, where we've come from with the large scale sequencing program and where we're at right now, and that will be basically the introduction and then when we go into closed session, we can start right away with the discussion of the applications. Adam? Yeah, thanks Mark. I'm just going to talk a little bit about the, I want to qualify this as recent history because there's obviously a lot of history to the program and it's a fairly high level history mostly to provide context, some background and context for all of you leading up to the discussion in the closed session. So you all probably have seen this. This is the recent history of decreasing cost, especially in the last few years. It's gone down quite considerably and because of the new platforms, but it was going down before that. This is a log scale. This is, I just want to point dating all the way to 2001. So we all know about the decreasing cost. That has allowed a reduction of funding over time and the NHGRI large scale sequencing program has tried to reduce its total annual funding over time and this graph only goes back to 2004. If you went back to 2001 or 1999, it would be closer to $200 million a year and this isn't even inflation corrected. So it's gone down over time. It's been fairly steady in the last funding period, but of course there's still increasing capacity. Again, everyone knows why this is and we expect roughly the NHGRI program output to be in terms of terabases, 350 terabases for the year of 2011 and this projection is holding true and it's based on only actual data for quarter one and quarter two of this year. I should say that looking at this hides some things. It hides the sort of kind of sequencing that's being done over this period and the kinds of changes that have happened in the last four or five years. Of course the human genome project provided and the related model organism projects provided a single focus for a number of large centers to do and as capacity grew, those centers were still working cooperatively on some large projects but at the same time were diversifying the kinds of projects they were doing and taking on multiple projects per center and that had a lot of consequences for the science, great consequences for the science but also consequences for the program was managed especially in terms of finding the good projects to do and finding good samples to fulfill those projects. So there have been many accomplishments. I can't talk about any of them in detail but just to summarize at a very high level over the last four or five years. The first three highlight kind of medical sequencing that's being done that wasn't really being done five years ago at large scale. So cancer sequencing with glioblastoma ovarian and another 20 in the pipeline, at least complex disease studies for diabetes, autism, cardiovascular, these were unapproachable five years ago pretty much because they require thousands of samples and during this time these kinds of projects have gone from, they've constantly had to change as capacities increase. So first these all started with the idea of doing 100 loci in thousands of people and then that was then whole exome sequencing came along and then it's whole exome and now people are talking about whole genome sequencing. Mendelian diseases first started as sort of mapped but you didn't know the genetic lesion to now completely unbiased or at least whole genome unbiased, I mean whole exome unbiased. Variation resources have really taken off a thousand genomes and all along still many, many organisms are being done in the last five years although I would say there was a little bit of a hesitation until recently because the new short re-technologies aren't so great at assembling de novo but there's a lot of population genetic models. Insect genomes and fungal genomes certainly have been amenable for a while with the new technologies, et cetera and also increasing addition of other modalities of sequencing and then just genomic sequencing as additions to some of these model organism projects and of course metagenomics is beginning to take off in the last four or five years. The current breakdown as of the second quarter of what is a year eight of this year, fiscal year of the grant funding is roughly this of the different kinds of projects with the bulk being 57% being cancer, about 20% being medical sequencing and 7% being organism sequencing and thousand genomes coming down from a much more substantial proportion is now a bit less. In addition to the achievements of the program, scientific achievements, we think about a lot of the benefits of the program. Benefits is probably not exactly the right word but there are other things than the production of papers and scientific results that come out of the program. There's the most obvious which is building community resources of extremely high value but also disseminating tools and technical know-how, promoting a data sharing ethic for genomics. This is something that's often cited as maybe the most lasting contribution. I've heard it cited as that. Leading standards for formats and quality, at least debating them, I think probably the first, the largest center of mass for discussions about what these should be and these are becoming increasingly important especially as lots and lots of groups want to contribute data to public resources and pioneering new project types. For example, whole exome capture, approaches to whole genome sequencing, analysis approaches. This entails a lot of feedback between developing the new methods or adapting the new platforms to new analysis methods to new capture methods to new upstream and downstream. Some other benefits of the program that are sometimes undervalued so improving and maintaining the reference sequence and I think the notion of the reference sequence is getting more complex as we go forward and are going to try to interpret clinical sequence data. This is going to become, come to the fore again, I think, and generally finishing refinement which is not done in a lot of places and it doesn't get much attention when we often when we talk about the program but it still is an important capacity that we have and maintaining the commitment to for high quality especially as new platforms come online with an eye towards those platforms should be able to reach high quality as well. And again, this is increasingly important as we start to understand the role of structural variation in disease. So we're next setting up for the next four years, two pieces of context, one is the strategic plan for genomics that you all know about and I think you saw the slide in the previous presentation and the other bit of context with the results of the large scale sequencing planning workshop that happened in 2009 that led up to the new set of RFAs. This is the diagram and just across the top is this direction from basic to more applied for medicine and where we want to be and where we think the field is going in general. In the next 20 years or so, 10 to 20, 10 years, we don't have so much time as I thought. So this is what we did in response to that. So here's this axis across the top again of where we want to be and tend to be on 10 years. Here's the sort of single mode large scale sequencing centers. We're proposing to shrink it and add these elements. So this is going to shrink down to about from $110 million a year down to $90 million a year and make room for these three additional components, Mendelian disease sequencing centers, clinical sequencing exploration centers, and sequencing informatics tools development. And these are the different RFAs that you'll hear discussed in turn during the closed session, actually in the order of this one first than this one and this one and that one. So just in words, large scale centers at 90 million a year, continuing benefits of large scale. They should be flexible, involve resource development, undertake major projects that require scale or have other unique features that requires this kind of an organization. Mendelian centers, the RFA was written for $10 million a year to focus to organize identification of all variants underlying Mendelian disease. The clinical sequencing exploration centers, the RFA is for $5.5 million a year to identify requirements for routine clinical use, essentially by pushing trying to do it and learning and figuring out what those lessons are, that's the exploration part. And then finally sequencing informatics tools because during our rounds of advice, we got lots of advice that if sequencing is ever to be democratized that people need ready to use robust tools that we don't have. So this is the new funding picture. The program as a whole will stay at about $110 million a year. The large scale centers will go down to about $90 million a year. And that's the whirlwind history and intro. I want to thank all these people. The sequencing team has grown with the number of RFA's that we're trying to, programs we're trying to put together. And with that, does anyone have any questions? Yes, Howard. Do you have any metrics? There's always those beautiful slides on the cost per genome, cost per variant, that sort of thing. Are there any, is the same thing happening on the analysis of the genomes? No, we have a really, I think, kind of poor handle on what it should cost. And even what it does cost. We know for certain projects, we know what the analysis costs are. But what we haven't done is, especially for different kinds of projects, identified consensus endpoints so we can start to understand exactly what costs are. But I think that's something, a very high priority for the next phase is to know what the informatics costs are. We know what data storage costs are, roughly. But the analysis, again, there's not a, there's a lot of churn about how to do it right. There's a lot of funds that haven't going to go capitalize the development of it, because people are still arguing about what the best way to do it is or what mix and match of the current programs are. And again, we haven't defined some of these endpoints. Bill? So, Adam, this slide with the increase in size of team sequence. With the increased capacity, with lots of collaborations between different institutes, from your point of view, what are the challenges for staff in terms of overseeing all of these projects? Yeah, so the biggest, the biggest is, I think, knowing enough. So it's just like Howard mentioned, keeping track of everything. I think what we have a pretty good handle on are what the best opportunities are for collaborations around sequencing with other groups. There's what Terry talked about. Mark has undertaken some prior efforts to understand what the sequencing universe was. So I think for the large projects we know about, the difficulties are going to be, as the program democratizes or as it shrinks in funding, being enough of a center of gravity to set precedence is going to be harder and harder. So I already noticed, for example, in the area of setting, trying to set standards for clinical sequencing, that there are many, many groups independently organizing to try to set standards for clinical sequencing, just technical standards for how good the machine output has to be. And those are kind of the things that we think are probably pretty important for us to have a real say in, but we're only one of a number of players now. So I think that's very hard. And again, as the program shrinks farther, it's going to be harder for us to get up and say, well, these are the standards we've developed and everybody else following. So as the NHGRI commitment shrinks or holds, is disseminated into different areas, what about the rest of NIH? How does the total sequencing budget from NIH look? Yeah, it actually looks reasonably good, but it is directed at specific disease areas, as you might expect. So there's a lot of work in cardiovascular disease from NHLBI. NCI has put in additional funds for cancer sequencing. NIAID has some. And there are others. So in terms of dollars, it's pretty good. And it's certainly at least maintaining the current, or the previous is probably another 60 or $70 million a year or something like that. But again, their focus is on, is not on capacity building, it's on finding the answer. And do you know how much our NHGRI large scale sequencing centers get of that pie? It's probably, it's under $35, it's around $32 to $35 million. I have some more figures in the closed session. But it's very hard for me to know what happens in out years. It's, I just don't know. And I think we can come back to these kinds of issues in closed sessions, because once we've figured out, once we've discussed the individual applications, the individual RFAs, we're going to look for counsel's advice on the structure and shape of the program going forward. Okay, thank you, Adam.