Physicist, Startup Founder, Blogger, Dad

Wednesday, November 14, 2018

London / DeepMind photos

I've been very lucky with the London weather on this trip -- in the 50s and sunny.

These were taken from the roof terrace of the Google building that houses DeepMind:

These are from the nearby area: St. Pancras, Granary Square, in King's Cross.

More photos from the area.

Photos below from The Economist (also rooftop views of London, but not as posh as GOOG) and BBC visits.

This Economist article on Genomic Prediction has been in waiting for weeks, to appear in The World in 2019 special issue. I spent a couple hours briefing their science team on what is coming in AI and genomics -- I would guess there will be more coverage of polygenic scores and health care in the future.

See also this New Scientist article on GP.

2019 may be the Year of the Designer Baby, if journos are to be believed ;-)  Of course, this is sensationalism. It is more accurate to say that 2019 will see the first deployment of advanced genetic tests which can be used to screen against complex disease and health risks. Already today ~1 million IVF embryos per year are screened worldwide using less sophisticated genetic tests for single gene disease mutations and chromosomal abnormality.

The Economist:
In 2019, ... those with the cash to do so will have an opportunity to give their offspring a greater chance of living a long and healthy life.

"Expert" opinion seems to have evolved as follows:
1. Of course babies can't be "designed" because genes don't really affect anything -- we're all products of our environment!

2. Gulp, even if genes do affect things it's much too complicated to ever figure out!

3. Anyone who wants to use this technology (hmm... it works) needs to tread carefully, and to seriously consider the ethical issues.

Only point 3 is actually correct, although there are still plenty of people who believe 1 and 2   :-(
BBC wanted me for their Radio 4 Today show. I went in and recorded some clips, but the broadcast may be delayed due to all the Brexit excitement -- Theresa May has finally revealed the proposed EU-UK agreement her administration negotiated. Angry Brexiteer Tory MPs may vote her out. I had a ringside seat to all this thanks to my friend Dominic Cummings!

Friday, November 09, 2018

DeepMind Talk: Genomic Prediction of Complex Traits and Disease Risks via Machine Learning

I'll be at DeepMind in London next week to give the talk below. Quite a thrill for me given how much I've admired their AI breakthroughs in recent years. Perhaps AlphaGo can lead to AlphaGenome :-)

Hope the weather holds up!
Title: Genomic Prediction of Complex Traits and Disease Risks via Machine Learning

Abstract: After a brief review (suitable for non-specialists) of computational genomics and complex traits, I describe recent progress in this area. Using methods from Compressed Sensing (L1-penalized regression; Donoho-Tanner phase transition with noise) and the UK BioBank dataset of 500k SNP genotypes, we construct genomic predictors for several complex traits. Our height predictor captures nearly all of the predicted SNP heritability for this trait -- actual heights of most individuals in validation tests are within a few cm of predicted heights. I also discuss application of these methods to cognitive ability and polygenic disease risk: sparsity estimates (of the number of causal loci), combined with phase transition scaling analysis, allow estimates of the amount of data required to construct good predictors. We can now identify risk outliers for conditions such as heart disease, diabetes, breast cancer, hypothyroidism, etc. using inexpensive genotyping. Finally, I discuss how these advances will affect human reproduction (embryo selection for In Vitro Fertilization (IVF); gene editing) in the coming decade.

Bio: Stephen Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Action Photos!

Wednesday, November 07, 2018

Validation of simultaneous preimplantation genetic testing (PGT) for aneuploidy, monogenic, and polygenic disorders (Dr. Nathan Treff, Genomic Prediction, Inc.)

Dr. Nathan Treff, co-founder of Genomic Prediction, at the 2018 American Society of Reproductive Medicine meeting. His talk introduces Expanded Pre-Implantation Genomic Testing (EPⓖT):
EPⓖT allows the routine, inexpensive evaluation of hundreds of thousands of genetic variants, implementing a novel combination of embryo genotyping methods not previously combined into a reproductive genetics application.

Universal coverage of common single-gene disorders, such as Cystic Fibrosis, Thalassemia, BRCA, Sickle Cell Anemia, and Gaucher Disease.

Complex disorders whose risk can be predicted include:
Type 1 Diabetes, Type 2 Diabetes, Coronary Artery Disease, Atrial Fibrillation, Breast Cancer, Hypothyroidism, Mental Disability, Idiopathic Short Stature, Inflammatory Bowel Disease
At the American Society of Human Genetics (ASHG) meeting last month in San Diego, several people recognized me and came over to marvel at Genomic Prediction.
"Look at all these people walking around, with no idea what is happening right now...  You guys are Creating the Future!"

From Comments:
John C. • 11 hours ago
What could be the use of predicting atrial fibrillation, coronary artery disease and Type 2 diabetes risk be? Tell people to not gain weight as they age?

Bobdisqus • 3 hours ago
Well as someone who had an ablation for AFIB, two stents in my RCA, and a family history that includes a brother with first heart attack at 38, and my father at 43 I would say the value is immense. Beyond that the extended family on both sides is rife with such. The number of men in my ancestry that made it past 70 is tiny. My children now have the option with a couple of rounds of egg harvesting which is well advised for my brood of daughters anyway given the human fertility curve and their plans for education to filter the worst of this scourge from our line going forward. Their sons can then anticipate fine old ages into their 90s much like the people of their Mother's line.

Tuesday, November 06, 2018

1 In 4 Biostatisticians Surveyed Say They Were Asked To Commit Scientific Fraud

In the survey reported below, about 1 in 4 biostatisticians were asked to commit scientific fraud. I don't know whether this bad behavior was more prevalent in industry as opposed to academia, but I am not surprised by the results.

I do not accept the claim that researchers in data-driven areas can be ignorant of statistics. It is common practice to outsource statistical analysis to people like the "consulting biostatisticians" surveyed below. But scientists who do not understand statistics will not be effective in planning future research, nor in understanding the implications of results in their own field. See the candidate gene and missing heritability nonsense the field of genetics has been subject to for the last decade.

I cannot count the number of times, in talking to a scientist with limited quantitative background, that I have performed -- to their amazement -- a quick back of the envelope analysis of a statistical design or new results. This kind of quick estimate is essential to understand whether the results in question should be trusted, or whether a prospective experiment is worth doing. The fact that they cannot understand my simple calculation means that they literally do not understand how inference in their own field should be performed.
Researcher Requests for Inappropriate Analysis and Reporting: A U.S. Survey of Consulting Biostatisticians

(Annals of Internal Medicine 554-558. Published: 16-Oct-2018. DOI: 10.7326/M18-1230)

Of 522 consulting biostatisticians contacted, 390 provided sufficient responses: a completion rate of 74.7%. The 4 most frequently reported inappropriate requests rated as “most severe” by at least 20% of the respondents were, in order of frequency, removing or altering some data records to better support the research hypothesis; interpreting the statistical findings on the basis of expectation, not actual results; not reporting the presence of key missing data that might bias the results; and ignoring violations of assumptions that would change results from positive to negative. These requests were reported most often by younger biostatisticians.
This kind of behavior is consistent with the generally low rate of replication for results in biomedical science, even those published in top journals:
What is medicine’s 5 sigma? (Editorial in the Lancet)... much of the [BIOMEDICAL] scientific literature, perhaps half, may simply be untrue. Afflicted by studies with small sample sizes, tiny effects, invalid exploratory analyses, and flagrant conflicts of interest, together with an obsession for pursuing fashionable trends of dubious importance, [BIOMEDICAL] science has taken a turn towards darkness. As one participant put it, “poor methods get results”. The Academy of Medical Sciences, Medical Research Council, and Biotechnology and Biological Sciences Research Council have now put their reputational weight behind an investigation into these questionable research practices. The apparent endemicity of bad research behaviour is alarming. In their quest for telling a compelling story, scientists too often sculpt data to fit their preferred theory of the world. ...
More background on the ongoing replication crisis in certain fields of science. See also Bounded Cognition.

Blog Archive