Let's do some baseball. The Caribbean series is going on right now. If you're not sure what that is, it's the winning team from each domestic league of the winter ball leagues, like the Dominican Republic has a league, Venezuela has a league, so it's not the all stars from that country. It's the winning team from those leagues go to a series and play against each other. So this is the pool play around Venezuela versus Dominican Republic, the one seed and the two seed. And there's not a lot of meaning tied to this game, but there's a lot of pride on the line. The rankings aren't gonna get messed up and we have a big double in the eighth inning down one DR. And he says, shh, don't tell nobody. Just don't tell nobody. Just let me, oh yeah, oh yeah. Let me do the talking.  But he's excited. He's excited. He throws his helmet and then he catches it. And he's like, I don't know why I threw it. That's something I do when I'm angry. Then they bunt the runner over to third and here's where the controversy starts because they call safe third baseman's like, hey, replay, replay, review, review, review. Now I watched this game, but the broadcast is only in Spanish and I don't speak Spanish. That's on me. So I'm not positive what goes on here, but you can see him say he slid into my leg. He pointed at the catcher saying, come on, challenge it, review it, review it, review it. I don't know the rules of this series if every play in the eighth inning gets reviewed, if you have a certain amount of time, if you have to call it, but the foot blocks the foot from touching the base. And you can see he never touches the base and the gloves there. Now it's a tough call for the umpire, maybe. I mean, because he might not have a great angle down on this gap, but the guy never touches the base. And they should have reviewed it and seen this and called him out. I had a lot of people on Twitter saying it's interference, but as long as he has the ball and his glove, he can block the base.  As long as you have the ball, it's not interference. So once he got the ball and his glove, that's fine, unless there's different rules than MLB, but that's fine. This happened with Josh Donaldson once a while back where he blocked it with his knee. So they got this call wrong. Then I don't know why. I don't speak Spanish, so I'll rely on people in the comments below that do to let me know what happened here. Some people had commented via Google Translate. I read that they ran out of time to review it, so they couldn't. And then people responded to that and said, no, but it's the eighth inning, everything's reviewable. Some people said it did get reviewed, but didn't get overturned because they said interference, which I don't know if that's correct, because it doesn't seem like that's a correct call. So I really don't know what happened, but I know they argued for a while because it's the tying run now on third base in the bottom of the eighth inning and our dude, Ostadio Laturtuga, he's talking to the ump, trying to figure it out and the coach is gonna come over and try to interrupt, he's like, it's fine, it's fine, it's fine, it's fine, it's fine, it's fine, we're just talking over here. I'm cool, I'm cool about it.  Why don't we just get the calls right if we can get the calls right? It's gotta be his feeling, takes the hat off, you know, universal sign for frustration. The next batter is gonna ground out to Ostadio, who has to race back and get him and the ump says, yes, yes, yes, yes, bam, out. Yes, he did. Great call by the ump, love the enthusiasm, doesn't go to the bag, goes to the tag, worked out either way, but then the next batter comes up, puts one into the outfield and now that runner who's on third, who was out, he tags up and scores the tying run for the Dominican Republic pinch runner, got thrown out, now he scores the tying run. They intentionally walk Robinson Cano to get to Marcel Ozuna and Ozuna flies out and that ends the inning in the eighth, which brings us to the 10th inning now and they got bases loaded and the DR gonna take full advantage of that replay and they're in another sack fly which scores the winning run. Sack fly to tie it, sack fly to win it, they are the one seed, Venezuela is the two seed, the games are actually being played today, the semifinals and then on Thursday is the championship. So it's on ESPN plus if you wanna watch it, if you're itching for some baseball, it's quality baseball, quality broadcast and some drama.


They have made a couple of changes to their starting line up and we see Tajik Koopa coming in to the bat, the number three he'll be alongside Jaheem Parma, Taraj Andrews and Enrique Gordon Maximus. Davis of course is the one between the sticks in the middle of the patch of Alon Brown on the left, Rashon Livingston on the right, Jeremy Nelson and Marvin Williams down the middle behind Stryker's Jason Wright and Thorne Simpson in a 4-4-2 Cristela. Yeah 4-4-2 Thorne Simpson preferred up front to Tevin Scott, they're just trying to find that combination for Jason Wright who couldn't quite get going in the first game, had some good looks Jason Wright but unable to convert. Tajik Koopa, the 19-year-old from Trelawney gets a big start. Ricardo White is now between the sticks instead of Eric Edwards, they have a back four Philando Wing, Rashon Amos, Joel Cunningham and Deontre Cunningham unchanged in the middle of the pot, Marlon Martin, Jamon Sheppard, Jaheem Thomas unchanged and up top, Warner Brown will play through the middle, Kimani Arboin has been shifted to the left, Shay Smith still on the right. Right move, I think Warner Brown, they're playing in a 4-3-3, I think Warner Brown more of a natural striker, I think Kimani Arboin with his inch. Let's take a look at the full time highlights here, Shay Smith's effort straight to goalkeeper Maximus Davis, Arboin playing this one inside and Warner Brown's effort taking a deflection and going wide of the mark, Sheppard's ball inside was cleared out and then Philando Wing driving this one and Davis moving across to his right, got a hand on it but it was not strong enough and Wing celebrating his first goal in the Jamaica Premier League, giving effort and Wing on the score sheet, right, now Livingston and he dragged that one, took a slight deflection there and Arboin, he was having fun, Wing sending it across and couldn't quite convert on that occasion, Arnett Gardens, Livingston with a wonderful ball inside and that was pushed over by Richarda Smith, the header coming in from Jason Wright and Wright instrumented again into the path of Simpson, we really should have done better there and this was a lovely run by Jaheem Thomas, laid off to Smith, Smith on a platter and came up, Warner Brown tried to clear his line, Tajay Cooper, but right into the path of the unrushing Warner Brown and then Arboin, looked so dangerous on the left hand side and took a shot and it took a wicked deflection, it was going goalwards, yeah but the deflected effort flew past Maximus Davis and Arboin again, touching it inside and this was a really good goal, playing it around the area, shepherd with the final pass to Arboin, getting a second of the game and wonderful finish there, looked a lot more dangerous on the left hand side, Arboin cut again and he was very much involved in the interplay there and that was the fourth of the game, could have put one back before the half-time interval, Mullines United, wonderful turn that was Tarajan Jews and then the finish left a lot to be desired and the second half now, so much open space for Arnett Gardens, Jamon Shepard should have opened his scoring there in the Jamaica Premier League, still looking for his first goal, Shepard and then this effort from Kevin Scott who came on as a substitute in the second half, deflected wide and then Warner Brown having a couple of bites here, couple of blocks, he'll set up for Jamon Shepard who again didn't do a lot with it and then Gerald Neal with that delightful board inside and Warner Brown from point blank range and the aftermath of that he could only go on bended knees, should have scored, he knows it on another day he could have had a hat trick and then that was a wonderful block by Eric Edwards denying Jaqim Parma, Mullines United had 13 shots through which were on target and the guns had four of their 14 or six of their 14 shots on target, 26 fouls committed in this game, a couple of the other guards were shown to the Arnett Gardens men, Mullines United had more corner kicks but Arnett Gardens had more possession at 57 percent. Kimani first of all congratulations on your management match performances, just one goal last season, two goals now in two games for you, it's an excellent start. Yeah I've been working, I looked at the pass and I see I need to score more goals and that's what I've been working on all pre-season long. In the first match you played as a central striker today out wide, you seem more comfortable in that position, do you rather that? Well it's the coach's decision, wherever I perform at training he put me there and I was playing well at the wing for the last week so I guess he took the chance and put me out on the wing and it was well deserved. He's certainly working for you Kimani, congrats on the game today I will look forward to seeing more goals from you this season. Yeah for sure that's the aim, the team, there's been a lot of doubt in the team and we are here to prove our point, prove to all the people, all the Ouse, keep last game gone, we're there, see them in most of us, the youngsters them, work with them, get a thing together, get a core and move forward. Well you made a big point today congrats, all the best. Yeah thank you. Kimani.


Chandni Chowk and the city of Shahjahanabad or Old Delhi is a great place to see architecture from different eras of Delhi's history. But it is the similarity in style across religious structures that is interesting. Writer and historian Swapna Little has walked this area many a time. Her take back puts many Hindu Muslim dividers to shame. The city of Shahjahanabad or Old Delhi was founded by the Mughal Emperor Shah Jahan in the 17th century. As a result, we would expect to find many examples of Mughal architecture and we do. But look at the similarities. The Jama Masjid is built of red sandstone and white marble and has a striped dome. The Digamper Jain Lal Mandir shares a similar style with red sandstone and white marble ornamentation and striped domes. In the 20th century, additions were made to the temple in the form of towering red shikhars. The gilded bulbous dome of the Gurudwara Seasganj is very similar to the domes of the 18th century Sunerimasjit right beside it. Through the previous century or so, colonial scholars had been studying Indian architecture and classifying it rather simplistically as Buddhist, Hindu or Islamic. According to this interpretation, domes and arches were Islamic and shikhars were Hindu and by extension, Jain. Indians gradually came to accept this interpretation too. While the original builders of the temple had not found anything Islamic about a dome, their 20th century successors felt that a temple must have a shikhar instead. January and February are the perfect months to do this walk. Amidst the many culinary delicacies that also exist here, the mouth-watering jalebes from Shivmish Tanpandar, Bheedmi Puri and Nagori Halwa from Shyam Sweets and multiple options for mutton korma, nahari and paya will also blend in perfectly along the way.


Tighten's hit an eye on second and five. Going to run Henry, fine through, up the middle. He's going 35 for the 40. Midfield, 40, 30, 20, 10, 5, and zone. Ladies and gentlemen, 69 yards. Garrett Henry, touchdown! Tighten!


It is time for another video on where to start with Murder Mysteries. Hello friends, welcome back to my channel. Today we're doing a video on the best places to start with Murder Mystery books for beginners. I did this video the first time about a year and a half, two years ago? I don't even know how long ago. I think a year and a half ago I did it. It somehow has now become my most viewed video. So I decided I'd want to give the people what they want. And I thought, you know, I've read a lot more Murder Mysteries since then. And I thought it'd be a good time to kind of renew the list and give you a part two. But before we get into the video, I want to say a massive thank you to the sponsor, which is Book of the Month. Book of the Month are one of my favorite brands to work with. I love Book of the Month so much. Book of the Month is a super popular online book service for readers where you get to choose a new release every month to read. Their mission is to promote new and emerging authors, shown by the fact that actually the two books that I chose this month are debuts. We'll get into that in a little bit. But they scour through all the new releases. It's my favorite thing about them. They look through all the new releases coming out in a month. And they pick some of the most exciting ones coming out. So you don't have to do the research. You don't have to be scouring what new releases are coming out. You can just subscribe to Book of the Month and let them help you discover your new favorite books. Book of the Month is risk-free. You can skip any month if none of the picks interest you that month. And they have the best prize for new release hardcover fiction, which I always think is amazing. You can get your first book for only £9.99 using the code MegwithBooks. So let's just quickly chat about the two books that I chose this month. And they're two that I'm really excited for. First we have Thistlefoot. This is a fantasy inspired by Jewish folklore. And I love books and fantasy books in particular inspired by folklore. I think it just gives fantasy books this kind of fairy tale kind of energy. I mean a lot of you will know one of my favorite series is The Bear and the Nightingale series. And so I just feel like this is right on my street. It's a lot about like I think Baba Yaga and Baba Yaga's house maybe, the house with chicken legs. So I've never read a story that focuses on that, but I've heard a lot about that kind of folk tale. So really excited to get to this. And then we have As Long As Lemon Trees Grow, which has already been getting incredible reviews. I've had a look at like reviews and ratings for this and they've all been so high. We're following a young Syrian woman whose life is upended by war and kind of her journey of self-discovery. So very excited to get to this. I feel like it's going to be very emotionally hard hitting. It's pitched for fountains of the Book Thief and Salk to the Sea. So I'm a bit scared for myself. But yeah, these are both debuts. So I love that they're included in the Book of the Month choices. If you're interested in either these books or any other of the picks of this month, definitely use my code Meg with Books to get your first one for only $9.99. I love Book of the Month. And I think coming up to festive season, it's great to get as a gift for a book lover in your life or to ask for as a gift. I love getting subscription services as like asking for that as a gift at the festive season because it's kind of the gift that keeps on giving because it you know carries on for a couple months. So yeah, I'd honestly recommend you go check out the link in the description and use my code Meg with Books. So the way I did the first video with these is that there's two ways you can do this. I've got different categories that we're going to chat about in where you can start with Murder Mystery Books. You can either view this as a journey I would recommend you take. You start with this category, you move through the categories, right? Or I would recommend you can pick any of these as a place you could start. Okay, whenever you're ready. I'm ready. Okay. I'm ready. Whenever you're ready. I'm ready. The first category is very interesting because the first category I had in the other video was the Modern Mystery Thriller Hybrid because I spoke about how a lot of mysteries are marketed as thrillers because that's where the money is. That's where marketing's money is, publishing's money is. But things have changed. Things have changed quite dramatically since I made that video in the year and a half. I'm going to take the hat off actually. It's not it's not going well with my head today. So the big genre, the big kind of trend in mysteries now is the Modern Cozy Crime Murder Mysteries. And this really began with the Thursday Murder Club. This is the series. Oh my God, look how cute they all look together. I have only read the first two. Oh my God, I'm like struggling. The third one has just come out but I'm going to read it probably next month. So let me just hold up these two because they're the ones I can actually recommend. So Richard Ellsman wrote Thursday Murder Club series. These are following elderly people at a retirement village. Oh my God, can you hear my stomach rumbling? My goodness, I'm trying to film. It was rude and I didn't deserve it. So we're following friends at a retirement village as they solve Murder Mysteries. And it has got this quaint coziness to it that is taking over the genre. There are so many books that I say are copycats of this where it's like other older people solving Murder Mysteries but not even just that. I think before we would just see cozy mysteries as like historical mysteries or you know what I mean? There was always that kind of that genre of cozy mysteries that were not as mainstream. But I'd say the kind of cozy crime Murder Mystery that stems from the success of this is really taking over the mainstream genre. And I love this. This was my favorite book, was it last year? Or my second favorite? I think it was my favorite book that I read last year and I also gave the second one five stars. I think these are really well written, the mysteries are really well plotted, and they are so accessible for being a first Murder Mystery book. I think these books are probably for a lot of people the first Murder Mystery books they've read or maybe the first they've read in a long time. If maybe they've read Agatha Christie when they were younger but then they're seeing the success of these in like Waterstones and they're just everywhere. I mean these books are everywhere. I think the third one like broke the UK record for hardcover sales like in the first day or week or whatever. Like this is breaking records. This is the most popular series in the UK right now. You wish you had what I had in the bank darling. So because there's going to be so much more of this style of book coming out because of the success of this I would recommend this as a great place to start. They're not super gory. They're not super like dark like man detective solving that. Do you know what I mean? They're not that vibe. They're gentle and cosy and heartwarming and heartbreaking at times. They've got a lot of other plot other than just the Murder Mystery as well. So I'd humbly recommend this as a great place to start and I think it's been a really successful place to start for a lot of people. Another quick mention for another like mainstream cosy that's been really successful is The Maid by Neeta prose. I only gave this four stars. I mean I love this edition though. I love her so much. We're following a maid who works at this grand hotel and a murder happens in one of the rooms and she is kind of framed as the main suspect. This definitely has that kind of cosy writing. We've got a lot of humour in it. We've got a main character who we can kind of sympathize for and root for. I didn't love this as much but I think I didn't love it as much because I found it quite obvious and perhaps that's because I've read a lot of mysteries now but I think if you're just beginning this is going to be a great place to start as well. The next category that I want to recommend is mixed media. I think mixed media murder mysteries are super fun, super quick, super fast paced, super accessible to people who are just starting in the genre. The main one of these that has come out and this can definitely be classed under like cosy crime as well is the appeal by Janice Hallett. This is told through text messages but predominantly all emails. These are all email conversations so this one there's been a murder at this kind of quaint English town. You're going back in time and you're reviewing all of the emails that this cast, it's a cast of like a small town play, have emailed back and forth to try and figure out who the murder is through the emails. Now I remember saying I was a bit disappointed by this but that's only because I wanted to be 5 stars, 5 stars, 5 stars, beyond 5 stars and it wasn't that. But I did still really enjoy it and I would 100% recommend this as a place to start. I think you could probably read this in like a day. I know it looks big but it's like emails so you're just reading it so fast. I'm so excited to read Janice Hallett's next book. I've got the Twyford code which I think is told. Oh yeah like audio files, this one is. I'm going to hopefully read this soon and then I don't know what her next book is going to be told through because I seem it's going to be mixed media but I know it's going to be to do with a cult so I'm really excited that's coming out at the start of next year. So I think this would be a fantastic place to start if you're wanting to get into murder mysteries. I also just want to give a quick honorable mention to a good girl's guide to murder here but I did give this as a book recommendation in the previous video so I can't really recommend it here but this is mixed media as well. Pip is solving a cold case from her town and it's told through. This has got a larger mix of mixed media than the appeal that's just emails whereas we have interviews, audio files, web pages, like so many different types of mixed media in this. This is a five stuff for me. I love it but I've already recommended it to you in that other video. Now in the last video a recommendation I gave was obviously to start with Agatha Christie. I think starting with Ag Christie is a great place to begin, particularly her big name books. Since that video I have read Death of the Nile which I think again would be a great place to start. I'd still probably recommend Murder on the Orient Express and Murder of Roger Acroyd over this though. I think this one's a bit more complex with the characters that it deals with. It's a bit more later Christie than those ones and I think those are good to start with because they're kind of like classic Christie. This still is but it kind of has some more like moral teachings I would say than those two but since I can't recommend something like Christie again what I recommend you start with is books that obviously take a lot of inspiration from Agatha Christie. Now one that I did not love I think I gave it three stars but I think it would still be a good place to start is A Fatal Crossing by Tom Hindle. So Tom Hindle definitely takes a lot of inspiration from Agatha Christie. I'm really excited to read his next release which I think is like a stately home like locked room murder mystery but this one is set on a ship. It's set on the Endeavour in 1924 and there's a murder on the ship and there's an investigator and the ship's officer who investigate the crime together and I went on his cruise Tom Hindle and he reads a lot of non-fiction about Agatha Christie. He has a lot of non-fiction that I have about her use of poisons or her her methods and like stuff like that. He's obviously a big fan of Agatha Christie. I think you can see the influence a lot in this work so yeah I didn't love this. I think it was a debut. Do you know what I mean? I think for a debut it's not that bad. Like when I think of a mysterious affair style which Agatha Christie's first book I don't love it so. Don't say that. Mona don't ever say that. Tom Hindle still has a lot of possibility I feel like yeah this is a fun if you want one on a ship you want one like in an interesting location I think this would be a good recommendation and then another recommendation I have is The Paris Apartment by Lucy Foley. I think Lucy Foley is one of the closest writers we have to a modern day Agatha Christie not in terms of writing style. I don't think their writing styles are at all similar but in terms of having a really great location I feel like Agatha often has a very atmospheric, vivid, tangible location that you're set in. This one's set in a Paris apartment and like the architecture and the layout and like the secret parts of the apartment are all very cool and it's set in Paris as well but I think also they both do very well at having a small cast of characters who you know are your suspects that have a lot of interesting dynamics to them. So Lucy Foley always has like six characters or so who you know are your suspects. You know that they're who you're like targeting and on the back there's always like the archetypes that they are so you have the socialite, the nice guy, the alcoholic, the girl on the verge, the concierge. I really like the kind of archetypal characters that Lucy Foley has that have like a very strong identity that we can begin to pick apart and see holes in and see lies in. Also this is I will say more of a missing person mystery but very early on in the book it's a very large probability that that person is dead so it's like kind of is a murder mystery in a way I would say. My next recommendation way to start perhaps if you read more classics or older books is to read other classic crimes so not Agatha Christie but she's like the number one classic crime person. But my recommendation is the Winchingham Mystery by Anthony Berkeley. I read this for a video where I solved it which was so much fun like well I tried to solve it. No spoilers but like you're going to fail miserably. Well I kind of like took you through the book with me and I was actually surprised at how much I loved this. I think it had great humor, a great cast of characters again, a great setting, a great mystery and it's made me really excited to read more classic crime. This is from the Collins Crime Club and I'm really excited to maybe get some more in this collection and read them. In this one our protagonist is this guy who he comes from a rich background. He inherited a lot of money from his uncle but he's spent it all so he has to go work as like a butler. The St. Lee home he's there, there's a dinner party going on and one of the guests disappears and they're trying to find out what's happened to her. Actually more than I think about it not really a murder mystery but I did tell a bit of a lie there but of course the possibility is there. I'd say less of a murder mystery than anything else in this video I've only just thought of that but less of I've included it now so it's too late. Then my last recommendation would be to start with if you perhaps read a lot of fantasy a book with some speculative elements. My recommendation would be The Broken Girls by Simone St James. I love this, this is one of my favourites I've read this year. So this has two timelines in the present day we've got a girl trying to come to terms with the murder of her sister that happened I think like 20 years ago. Renovations are happening to the school, the old school, the abandoned school on which grounds she was found and during the renovations another old body is found hidden in a way that makes it clear it was a murder like that was not a normal death and we're also in the 1950s following perspectives of some girls who went to the school at that time and I love this. I'm so excited to read more at Simone St James because I just adored this. I thought the speculative elements in this, they're not a massive part of the book I'd say the majority of it is like a murder mystery or two murder mysteries really perhaps with more of a thriller edge to it with amazing writing I loved the writing in this but the speculative elements are there and it's just it's done in such a good way that I love in my mysteries horror fans like whatever has a speculative element to it if it's set in our world it kind of like leaves the door open and doesn't shut it or open it more do you know what I mean I don't want to spoil anything but like the speculative door is open ajar we're not shutting it and saying nothing exists you know I mean it was just some like there's some real world excuse for it and we're not opening it up and getting fully into like how is that possible we're just leaving them open a bit letting the speculativeness seep through a bit do you know what I mean so I loved this I think if you read fantasy or if you read a lot of thrillers this would be a great place to start so there we have it that is my murder mystery recommendations for beginners I hope you found something helpful here I hope you found a book that you would be excited to read let me know what you would recommend to murder mystery for beginners or recommend to beginners for murder mystery I am like incapable of any thought anymore but yeah let me know that down below thank you guys so much for watching and I'll see you very soon in another video bye


So, let's move into the discussion phase. So, I'm going to start off with taking off on something that Callum had mentioned, and there's a bit of a discussion around this this morning, and it's just something I hadn't stopped to think about carefully until your slide about the fact that we've got only 10 to the fourth clinical phenotypes. In your final slide, you said, okay, we need to come up with a minimal data set. So I'd like to have a little bit of a stark conversation around that, because a little bit of, I'm not sure how we solve that problem, since disease is defined around these phenotypes for better or for worse, that's what we have. So maybe you can talk a little bit more about how you see that going. Well, I think some of it is using the information we already have better, and it's worth pointing out that obviously we're sort of constrained by having to map everything back to existing data sets, but I think that itself is a constraint that we've allowed to occur. I think just to give you some simple examples, so for example, one of the things I started doing was asking our MRI guys to actually, on the scans of my patient, because I can't make it uniform yet, to include the John and the pharynx in the MRI, so it's about six extra slices, so that we can actually begin to use this as an integral of the phenotypes that might be part of outflow tract abnormalities that are subclinical, which are seen in every one of the animal models for all the diseases that affect the right ventricle. There are rarely penetrant phenotypes, for example, even in the case of NQ1 loss of function mice in the pharynx and in the jaw, as well as in the stomach, so things that we could begin to do just by changing the way that we think about standardizing the traits that we routinely measure, beginning to analyze existing data sets using non-subjective strategies. So electrocardiography, as I mentioned, everything, we have all of the fundamental signal noise characteristics are incorporated in every single EKG, yet we're still completely dependent on subjective terminology that was introduced in 1947 by a committee, and so actually saying, well, why don't we use machine learning to try and understand what we could actually pull out of the electrocardiogram would be a sort of tiny first step in that trait, but I think to get back to this morning's discussion, I think thinking about it from the standpoint of what are the extant data that we have for all of the pathways that we know and love for model organism data, how could we then begin to characterize cellular phenotypes or physiologic phenotypes, whatever resolution we can get from those data sets, and then say, okay, can we actually map, let's say, the entire psyllium onto a set of peripheral phenotypes that were recorded in everybody, you know? That's a real possibility. There's almost certainly with all of those, I mean, if you want to look at the gene list and you can see that it would be very tough to imagine that somebody who had a really powerful perturbation of that entire network has completely normal peripheral lymphocyte function as a starting point. Now, they might have a baseline, but if we find the right perturbation, maybe we would then be able to say this is somebody's entire psyllium network is perturbed in a fundamental way, gets back to some of the things we were talking about with Cricket's congenital heart disease sequencing effort. So I don't argue that it's a straightforward thing to do, but I think it requires an active effort as well as also an unbiased strategy, which I think will emerge as was mentioned earlier from patients. I think there's a huge movement in our patients and beyond to begin to collect data in a rigorous and quantifiable way that would actually impact this. So I think, as I said earlier, the scale of what we need to do here is so substantial that I think we need to think about all of those approaches and use them in a coordinated fashion. We'll do Mark, Rax, Dan, Liz, Bob. I know that Callum was being a bit hyperbolic in his presentation about saying, well, there's not a single datum in the electronic health record that I would use, because what you're talking about there is not only the standardization of the element but the standardization of how we measure the element. And I think that while it's true, and certainly if we look at blood pressure where there's sort of an accepted way that you're supposed to take a blood pressure that's at least in some sense reproducible, the number of times that that actually happens in clinical practice is minimal. However, if you have 70 blood pressure measurements across a variety of different ways of measurement that consistently show, you know, somebody with a blood pressure of 150 over 90, you can probably be relatively confident of at least getting some sort of a gross type of phenotype. So I think part of the thing is to say, out of those things that are represented on the electronic health record, is it a number of measurements? Is it measurements over time that would allow us a certain level of confidence to mine those elements to be able to do the type of work that we're doing? I agree. I think you need to standardize measurement and stimulus. And as you point out, a lot of this is just thinking carefully about what the dynamics are that you're going to time series instead of single cross-sectional data points. Those types of things are, as Les mentioned earlier, thinking about proximate phenotypes that are actually fundamentally definable in a way that's linear over five log orders. And by the way, you know what a panel of 100 drugs does to each one of them so that if you did that, you could imagine you'd probably record half of what you need from a single skin sensor. You know, that's the type of thing that I think is emerging in clinical phenotyping but has not been connected very directly with genomics. And ultimately, I think it needs to be. So when you said there were 10 to the fourth clinical phenotypes, is that because you're just looking at the number of ICD-9 or 10 codes? Or how did you come up with that number? So we looked at every single billable component of a trait that is, every single billable test, and then looked at every reported component of that test in clinical practice. But certainly as, certainly the Emerge Network, for example, has learned is you gather a large amount by data mining of problem lists and the patient and then the physician notes and all those sorts of things. And actually wanted to contrast that 10 to the fourth number. So HPL, how many terms are there in HPL? 1.1 times 10 to the fourth. They're the same ones. So Callum has touched on what I think is a really interesting and important part of this challenge that faces us today and tomorrow. And that's sort of, you know, we're obsessed by the genome and the transcriptome and the psyllium. And we haven't talked much about the phenome yet. And I'm a big believer in the idea that if we curate the phenome and organize it and write that it'll be as powerful if not more powerful an input to these sort of multi-omic analyses that we all think will yield useful information. So the problem is that I, like Rex, think that the electronic medical record is a place to do this. And the more granular the phenotype, the less likely it is that it's going to be captured by your average clinician using the EMR in the course of clinical practice. So you sort of have this paradox that you want them to record more information along the way, or you want some mechanism to record more information. And at the same time, they're under pressures by their chief of their clinical division, for example, to see more patients and not waste their time doing all the things that their chief of their clinical division wants them to do. So the phenome is hard. I can't resist following up also on Mark Williams' example that if you want to diagnose hypertension, my friends in bioinformatics. Oh, and by the way, my sign is wrong because I'm now a professor of bioinformatics as well as all the other titles I have. So now I'm an expert, Mark.  And the 25-year-old with a broken leg who doesn't have hypertension has a high blood pressure. So I think that there's this problem that we think the electronic medical record is a giant resource waiting to be mined, and we think we need more ways and more creative ways of mining it. I really like the idea of this idea of unsupervised machine learning to find new phenotypes, let the data talk to us instead of us telling the data what we want it to say. And hopefully we'll get, for example, clusters of hypertensives or clusters of type 2 diabetics or clusters of whatever that will then enable the kind of things that you want to do in model organisms. Same thing? Yeah. So one thing I really liked that I heard from Callum was the idea that we have certain aspects of the data that we collect that have a richness to them that is not captured in reports. The EKG data is one, and certainly imaging data. And there's plenty of information, or plenty of studies that have gone back and re-looked at these sorts of things. But again, I'm not aware of projects that have looked at this in an unsupervised machine learning way to try and do discovery. That would be something that would be really interesting to do, particularly if we tied it to some particular measure of interest, whether it be in the cardiac realm or neuroimaging or whatever. So I think there are projects, many of them funded by NIH, to try and do things like this. I think they are not at scale necessarily, and they've not been implemented in parallel with genomic efforts. But obviously, that's the direction, that's the reason for meetings like this, is how do these things come together in a way that actually is integrated around the shared angle? Bob, are you on the same topic or different? Okay, so Peter, did you want to jump in? Yeah, I mean, I think another thing to say is yes, there are now maybe 10 to the fourth phenotype. I think the HPO will probably land at about 20 or 30,000. But what hasn't been discussed yet are sort of clusters of phenotypes. And just as an example of how powerful this is, three groups have used human phenotype ontology and large cohorts of 10 to 40,000 patients, I think, and they'd first try to find binary new genes. So they compared ICD-9 codes failed, compared to individual HPO terms failed, and then they used machine learnings to co-find clusters of phenotypes that correlated with genotypes, and each of these groups discovered between, I think, four and six genes now. And I think if we start to apply this to electronic health records, well, you can also imagine temporal developments of phenotypes that in the combination would really also give us 10 to hundreds of possible phenotype clusters. So I mean, I think the phenotype landscape, even with the things that we're measuring now could be a lot richer than it is, and it's going to require a software engineering to actually get this data out of electronic medical records and put it into a data structure that bioinformaticians can compute over. That's not really happening much enough now. Liz, then Bob, then Cricket. And just to follow up on that point, one of the things that's gonna be important is to have the phenotype data reside within the EHR. The minute you move that data out of the EHR, start gathering it somewhere else. You lose that connection to the patient. You lose the ability to update it the next time you want to mine it. So we need to work out, of course, how to get that data collected better in the EHR, along with the genomic data. And that's what we have to mine. We don't want to put it all somewhere else because then you lose the ability to update it. Bob. So with respect to the LongQT, for example, just as an example, I think of the EKG abnormalities as a biomarker of the disorder. And even when you have that biomarker, you're not absolutely going to have a catastrophic event. So how do we, so I guess my question is, does the deep phenotyping of the model organisms permit you to explore the possibility that there are other biomarkers or other phenotypes which you can score in vivo in a human that might replace the classical biomarker and have a greater predictive value? Crooked. So I really like the electronic medical record, but I'm very worried about two aspects of it. The first is that increasingly we are using some platforms that allow, if I may be so blunt, dumbing down of the detail and smart phrases that allow as a busy clinician to insert phenotypic information without the level of traditional thoughtful consideration and nuance. And I think that if we're going to really have these phenotypes matter, it would be wonderful to have some input in terms of these prefab and expensive electronic medical record platforms. Alternatively, and I think one of our speakers this morning said this or perhaps last night on the plane, no one is more interested in the person, the patient than the patient him or herself. And the other way to do this would be to buttress that with an opportunity for patients to provide that data in a relatively well-defined platform that really could allow them, could allow more searchability than natural language processing. So I want to touch back on something that Bob said and tied into Cecilia's discussion. So one of the interesting parts about, so if your saturation mutagenesis for the congenital heart disease is right, that there's 272 potential genes that are going to play a role, that does kind of change the, that does kind of change some boundaries around on that. So I'm just curious as to Cricket, would you buy into the mouse as being a potential saturation mutagenesis that we're going to go screening for and looking to see if we can put some boundaries around this? Because I think to your point, Bob, if we're going to have alternatives, we have to put some definition around what does that mean in addition to these other biomarkers. And that's a potential way to do that. So I would only comment that Cecilia's work is recessive. And when we do the same kind of analysis of dominant, let alone polygenic, we get 400 dominance. So we've already up the ante to 600. And I think that mice are wonderful for being able to get homozygous variants. We all know that. And the phenotypes are expected to be more profound. But unfortunately, it's probably the lower estimate rather than the upper estimate. I don't know how much ENU can really hit every gene. I don't know that you've even considered if there's some genes that are ENU resistant. But in the course of human experience, I suspect anything could be hit. So it's a minimum of 600, maybe 250, 300 recesses, and at least 400 dominant. Liz? Just a quick question on that. Do you think the maximum is also close to 600 in the multigenic will be milder hits in those same genes? No one's looked at it. What's your guess? You know, in multi gen, I mean, so I actually believe there are polygenic contributors to congenital heart disease. And we know this from when you look at the offspring of people in whom we think there is a mutation. And it's either incomplete, dare I say the word, penetrance, or exposures or something, or there are more modifying genes that we even have begun to think about. And how penetrant those modifiers are, at what point do they become a component of a polygenic model? I don't have an answer. I'm sorry. Yeah, I'm just gonna say that it's possible that among some of the 400, maybe some of our genes as well represented. I don't know. I've never looked actually to be honest. I think that would be worth looking to see whether there's any overlap. But suffice it to say it's a larger number. But I think it's not an impossible number of genes, right? I mean, I think it's, if we put resources, it's definitely something that's doable. I mean, so I just wanna put that out there. I don't know if there's a will to do that, but I think that that is potentially feasible. It's not, we're not talking about 10,000 genes or even 1,000 genes. But if we're in the range of 500, I think it's potentially a feasible project that one can pursue. So I just wanna put that out there as something maybe NIH may have to think about on a higher level. Scott, I'm glad that we finally have gotten around to this topic of systems, genomics, and systems biology because I think for complex traits, it's very relevant. And I think it does, what I haven't heard yet, and I think it's worth discussing because I think it changes your perspective somewhat, is if it really is whatever, 200, 400, 600, whether it's even 100 for asthma or 200 for hypertension or whatever the disease is, we're talking about a different way of presenting this data clinically to clinicians. And if really the ultimate answer here is systems biology, it's not the question you raised in your talk, am I gonna put this variant in the chart? It's where does this variant sit relative to the other 200 variants? And what does the clinician really need to know to make an informed clinical decision about treatment with a patient? So I think it's, when you talk about the translational aspect of this, I think it changes the game because genetics is deterministic for sure in the Mendelian disorders, some percentage of complex traits, how determined it is depends on the penetrance, the pleotropy, et cetera, et cetera.  And so giving that information, it still comes back to what information are you gonna give people and how are you gonna give it to them and I'm not sure if you believe in systems biology, we haven't answered to that yet. So I was actually gonna comment that for congenital heart disease, it's one of the few areas where the genetic architecture is quite well studied. So there, the familial recurrence risks are the order of 70 to 90 fold. And in addition to that, there's also some reasonable population studies looking at clustering around dioxin plants, for example, for hypoplastic left heart. So both of those are actually consistent with a very unusual model, which is a very small number of genes in the individual patient. Once you get above 10, you're asymptotically approaching one single gene disorder, but with perhaps stochastic and environmental contributors. And so I suppose the question is, if we still aren't able to resolve to reduce to simplicity a field like that, how are we ever going to do it for fields where we just have no idea what the fundamental architecture of the traits really is? Carol? So I'm hoping, so Cecilia, you started to raise something in your talk and I wanna build on that and ask you and Kaelin to both address. So getting back to the basic theme about bridging between basic science and clinical science as it relates to phenotype. So describing phenotype in model systems, zebrafish, mouse, whatever, and translating those phenotypes into the human clinical phenotypes, whether they're in electronic health records or not. I would like your perspectives or your experience in sort of trying to do that. How easy, how difficult is that? Is that one of the addressable barriers in connecting basic science and clinical science and genomic medicine? Is that an opportunity here? I'm just interested in your experience and your thoughts on that. So we tried to do that by cross-referencing terminologies. So with the MPO, the mouse phenotype ontology terms, we really use clinical terms to describe these mouse phenotype. At the same time, we use the Fowler codes, that's the Boston Children's Hospital, Kinshaw Heart Disease Code, so that every animal we coded both ways. We use MPO terms as well as the Fowler codes that describe the phenotype. And our hope is that clinicians who may come searching for cross-referencing, whether to see the disease model, that they would be able to actually find what they're looking for. I mean, I think that that, I know for Kinshaw Heart Disease, that clearly can be done. And I would assume that across different phenotypes, there would be some parallels. So, but I don't think that's being done systematically. I think that's one of the problems. And I wonder whether MGI, when you curate information from lines, whether it's possible to have clinicians that are part of that process that could then provide curation of terminologies that are used clinically, then it becomes more clinically useful. I mean, so I'm very mouse centric, so obviously this is broader than that, but that's my own experience. So the short answer is yes, we have clinical geneticists on our advisory board, Gail being a good example that are helping us do that. But again, I think it's larger than there's a lot of work left to do, right? And probably some better ways to do it so that it is more systematic and scalable. And I should just mention, even amongst cardiologists, right, there's disagreement about terminologies. So there was this big effort, international effort to come up with a standardized terminology between European consortia and the US and Canada, and even now that's not been resolved. So I think the problem is much deeper because there's not even uniform agreement on the clinical side, and I think that's probably true in other fields as well. I think that's the subjective component to the EHR. I mean, so much of what, it's not that the EHR is a bad place to put stuff, it's just a function of what stuff you put there. It's worth pointing out that EHRs, as Crick had said, are designed around billing. There's one billing code for every single congenital heart disease, all of the above. There's no subset, it doesn't matter whether you have a cortician or a hyperplastic left heart, it's the same billing code. But so when we've tried to do this systematically in fish, we only did it in a couple of phenotypic areas. It's actually interesting, you can very quickly map out what goes from a 48-hour-old fish larva onto an adult human or into a pediatric human or an adolescent human. And in fact, that type of thing has, again, is something that we would need to systematically do as a community across all of the model organisms. Some of the work has already been done in some manner of organizing it. I think one of the nice things about functional genomics phenotypes is that they're immediately translatable. But there are other phenotypes that we will have to actually build assays for in humans or build assays for in model organisms. You can imagine that there are some things that are so well-conserved that it doesn't matter which organism you look at. On the other hand, we'd be foolish to try and model male pattern baldness in the zebrafish. So there are some obvious things, but there are some other things that are not quite so obvious that I don't think we would ever get round without having a systematic mapping effort along the lines of the ontologies that Peter and Melissa and others are driving for. Peter or Jupe? Yeah, I just wanted to, oh, sorry, I mentioned, we've heard a lot about prediction algorithms, machine learning. I don't think that's gonna work that well in the clinic. I think that there's a new area in translational bioinformatics that's explanatory algorithms. So why actually did the computer come to a certain prediction that all comes down to the difference of whether we're making expert systems, maybe like Watson, which I don't think are going to work in our lifetime, or systems for experts, and that's something which I don't think has been considered enough yet. Oh, Jupe, you may. We've been talking for a long time in this sort of community about how there must be sort of unrecognized structure within the EMR, there must be unrecognized patterns. I certainly have been saying that for a long time, but at the end of the day, there's very few examples of that. So that may speak to your point, or it may be that we're just not going about it the right way, or it may be that we need to stick more structured information into the electronic medical record so there's this whole push that we'll be seeing a more of a push to include sociocultural determinants of health in a systematic way. You go to the doctor and you fill out a questionnaire and you sort of tell them what your diet's been for the last week and how far from the grocery store do you live. Those kinds of things that are as important for health as the things that we've been talking about today. So it sounds like it should work, but it hasn't yet come to fruition. And maybe the data sets aren't big enough or maybe the computers aren't programmed right or maybe it's all just a hallucination. I hope not the latter. But it's also, I think it's also the way the data are entered into the HR. As I said, I mean I was not being hyperbolic. There is almost no single standardized, because you're the division director. So I wanted to come back to another one of your slides, Callum, which was around and it stays in line with the phenotyping that we're talking about and it comes down to longitudinal data. So one of the things I've seen in some of these complex cases that even if you think it's a single gene and you have all of this longitudinal data, sometimes the noise and that longitudinal data across all the different phenotypes makes it quite difficult to get at the phenotype itself. So what is the actual causal phenotype? For some of these syndromes, you see a lot of manifestations on that. So I want more data, because I think that's important. How do we put some structure around this in a way that we can get to what is the important data? Because I think that's a huge problem and as we get into the EHR information, that's where you start diluting out in many cases what is the most important information. So what are your ideas around that? I mean, I think it's exactly what we talked about this morning, it's proximate phenotypes that are at the resolution that allows us to connect them mechanistically to whatever the causes are. I think that's one of the problems with most of the phenotypes we measure are things that we decided to measure as a community based on historical happenstance.  I mean, that's literally why we pick it. There's so many different factors that go into that that it beggars description to be able to rationalize why we would then 300, 400 years later still be completely focused on it and have it be the only residual phenotype for which we are able to manage risk in the syndromes that present that have hypertension as a manifestation. So I think what we need to do is begin to start in the areas that we understand well and progressively standardize what we do and move out. This is partly why I think it can only happen in the context of existing healthcare. We're gonna have to get everybody to change over time. I don't think we're gonna have a parallel project of a scale that is sufficient to identify the major determinants of colon disease if we don't have it built into the electronic health record and the whole healthcare system, the whole healthcare acquisition and delivery system. And just even obviously one of the traits that I think is very important, which we have really never systematically studied, the drug responses. So why is it that decades after some of the early work in pharmacogenomics, there's still not even an effort to record first drug response or what the Delta is in a particular trait when you add a drug on a large scale across the population. We never do any of those things. There are no epidemiologic studies, for example, that incorporate a dynamic perturbation using the small molecule. So, and that's something that you could immediately take to yeast the following day. So I think that type of understanding what the anchors are. So genomics is a powerful anchor because the language goes all the way from top to bottom. We need phenotypes to do the same and many of those are by definition going to be at the cellular level and ideally the best way of thinking about them is to organize them around stimuli that can also be applied across every level. I think, I'm sure it's not the only way to do it. We have to get, the difficulty is getting from here to there as you point out. So, Calmy, that also mentioned next generation phenotyping. I think it was you. So what were you thinking in terms of what in your average patient you would like to have measured as sort of the next generation phenotyping in an EMR? So we've begun to do this in very low throughput in our clinic, thinking two things and sort of aggregating some of the conversations that you've heard this morning. That we need perturbations that the traditional clinical data input is relatively random and poorly organized. And so beginning to have patients come and actually spend some time in the clinic where they're actually undergoing systematic perturbation and measuring things that we would not traditionally measure. Some, for example, as Dan pointed out, some symptom scales, but also we started measuring, partly thanks to Cricket's insights from her work, started measuring neurological phenotypes in patients who came with cardiac disorders. And so we literally, there are lots of clinically available nerve conduction, chloride transit times that you can measure in literally a minute and a half as people are checking in and begin to use those to stratify clinical disorders. That's a small scale in already genotype populations. I don't know, and I think you'd have to have some sort of unbiased strategy to begin to imagine how this would be feasible across the entire population. But thinking about existing data sets that inform risk of subsequent disease, there's everything from grocery purchases, which are being recorded by every advertising agency on the planet at unbelievably granular resolution, which is a whole set of exposures that we've never really measured, all the way through to ambient phenotyping, using remote sensors for example, one of the things we're about to implement is a near-infrared camera that picks fiduciary points in the skeleton and so can map in a clinic waiting room gate abnormalities. So that type of thing, because it's associated with cardiomyopathy, makes a huge amount of sense to implement in a cardiomyopathy clinic. It's obviously not necessarily of such relevance in an OBGYN clinic, but if you imagine how the entire healthcare system could be turned towards this type of thing if it was properly insented, you might actually have a very powerful set of tools. I mean, one of the examples I always quote because it's trite and simplistic, is if you look at diabetes, it looks like a very complex trait. If you add one or two variables like height and shoe size, you can pull out the several of the major Mendelian forms because they're dwarfisms or gigantisms. So those are actually, because they're standardized measurements for which there are even international scales of cross-reference. You can begin to imagine if we'd recorded that type of information, we might actually have at least one standardized, one additional standardized phenotype in the electronic health record. So shoe size may be the first next generation phenotype. Yeah. Yeah. Gail. Yeah, I think the other thing we've heard it mentioned, some is that when we see a child, we would love to get measurements on parents. Now, some things I can do, but if they're gonna see a pediatric ophthalmologist, he ought to be able to examine the parents and getting echoes on parents can be incredibly problematic and part of it, a lot of it's financial, but it's also burden the hand. If you could do it right when they were there, because they're too busy to come back and do it on their own and all, I think that would help us sort out again some of the genetics because if you can't measure the trait in other members of the family, it's hard to know what to do if they have the variant or not. Just one other facet to add, not to make it more depressing, but most of our clinical research and much of our care and I know clinical decision making is biased because of this cognitive error. We are currently wedded to a phenotypic taxonomy of disease and phenotypic ascertainment of the people that we study, which means that we are biasing our understanding of the relationship between genomic variation and phenotype based on our presuppositions of what we think these diseases are. And the only way we will ever be able to do prediction from genomic variation is if we understand that full spectrum and compliment our phenotypic based research with genotypic ascertainment research is ascertained people by their genomic attribute and then ask the question, what is the spectrum of the phenotype that is associated with these variants and make the information go both ways and then we can begin to put the pieces of the puzzle together. And that our natural history too. Yes, absolutely. Bob and then Cricut. One of the types of information that you can get from the EHR that's fairly binary is what was actually done rather than what the result of what you did was, which can often is not binary, which is to say was an echocardiogram done? Was a referral to an endocrinologist done? Was a CBC done? Those are sort of binary questions that are basically ursats for what is the clinician thinking and what's the diagnostic pathway they're going down. It's not perfect, but it's something that is more computable than trying to read what the clinician wrote. So I just wanted to add to Les's thoughts because I think that this idea of longitudinal phenotyping with genotyping is absolutely essential. And I would only add that this to me is where academic health care centers belong, that we have longitudinal record. We have perhaps been the earliest and most invested adopters in having an electronic medical record that works for better or for worse. And we have experts in those disease phenotypes.  So integrating the genotype in terms of those longitudinal medical records. And I think around the room, many of the institutions here represented here have created these biobanks that allow for broad-based genotyping. And I think that's something that should be endorsed and frankly supported by NIH because it's so powerful for having all of the information in one place about a disease that there is a focused expert cadre of investigators, scientists, PhD scientists, clinical scientists and the like to gather around. The only other thing I would add to it is sometimes we forget that as geneticists, we like extremes, okay? And we've heard a lot about Cecilia and our early extremes, but the flip side of that should be, we should think about the really healthy older cohort. You know, those individuals who get through all of this stuff and are alive and well and can tell us about it. And I think that it would be very worthwhile to have genotype and phenotyping of those individuals. Now, I frankly don't believe that anybody is completely healthy, but I'm struck. And I think all of you have relatives who have, as I do, individuals who have maybe bad diseases below the neck, but above the neck, they are as sharp as can be. And what does that try to teach us about what are the genetic drivers of diseases as well as phenotype and compensatory responses? So I just think that normal controls are something we never see supported at the NIH level. And I think increasingly we need normal, or if you will, healthy people that we really understand their genotypes and phenotypes. Mark? Ben Callum? Yeah, a couple of responses to that. First of all, and again, maybe the argument is whether or not Geisinger is an academic medical center. We don't consider ourselves to be an academic medical center, but I would take issue with academic medical centers being the best source of longitudinal data since the experience that we've had is that most of them have episodic data associated with more acute illness and that the care, the majority of care is being provided outside of academic centers. And related to that last comment is that we have individuals in our my code bio-repository who are between 90 and 100 years old that we have all their data from the time they were born until now. Now, granted, the 80% of it is not in a computable form, but it's there. So I think that's the power of having more of an embedded approach of associating genotypic information with a range of things. And to Les's point, I think we're beginning to see how a FIWAS type of an approach can yield some data, but it makes Callum's point even more important, which is if we're going to do a genome first after attainment, to be able to understand what the range of phenotypes is, we have to have way better phenotypes to be able to assess that. Because the advantage that you have with phenotyping is at least you kind of know what you're looking for. And so you can torture the data to give you something that is a reasonable proxy for what it is that you're actually looking for. Whereas if you're doing a genome first approach, you don't necessarily have the luxury of being able to understand what the electronic health record is actually telling you. So I think in some ways what we're saying is that these two aspects are inextricably linked if we want to move this forward. We have to be able to do both. Callum, and I was just going to emphasize in response to Krig's point that exactly if you have quantitative traits, you capture both ends of the spectrum, as well as all the information in the middle. This is fundamentally an information content problem. And I have to tell you that one other thing I would say is I think this will be solved outside traditional biomedicine long before we solve it. There are huge movements in quantified self-movement, in commercial health movements, and in commercial activities of other sorts where there's actually a vested interest in improving the information content on the individuals for a variety of different ends. So I think if we think about this is only going to happen in academic medicine. I mean, I agree with Krig that there's good that is in academic medicine. But I think fundamentally, this has to even from the standpoint of scale has to operate in a much different fashion. Steven, last comment?  I'll pay you back later. There is Chair Progat, I'm just saying. So I have to disagree somewhat with the tone of this conversation. In the studies which have been performed to date with really crude phenotypes coming out of unstructured EMRs with disparate, not necessarily academic clinicians, we're finding very high rates of diagnosis today and things which are clearly scalable. And so I agree that from a basic research standpoint, you want infinitely beautiful, precise phenotypes. But from the standpoint of implementing genomic medicine at scale, we have to understand that we're aiming to use conventional medical records, conventional imprecision measures, and that we don't understand the phenotypic diversity of most genetic diseases. And so precise phenotypes sometimes are our enemy and lead us up the wrong ballpark. So I think that even with several thousand phenotypic features, not even 10,000, and all of the imprecision in our medical records today, the field is still incredibly ripe for us to do the pivotal studies to start to measure phenotypic heterogeneity, variability, dynamics, topography, and I'll stop there. Well, I think that's a great close. I will add one other thing is that maybe genome 10, although we haven't got there yet, should be a meeting on what is a healthy genome.