Monday, January 18, 2021

From Genotype to Phenotype: polygenic prediction of complex human traits

New paper, prepared for the book Genomic Prediction of Complex Traits, Springer Nature series Methods in Molecular Biology.
From Genotype to Phenotype: polygenic prediction of complex human traits > q-bio > arXiv:2101.05870   33 pages, 7 figures, 1 table
Timothy G. Raben, Louis Lello, Erik Widen, Stephen D.H. Hsu 
Decoding the genome confers the capability to predict characteristics of the organism (phenotype) from DNA (genotype). We describe the present status and future prospects of genomic prediction of complex traits in humans. Some highly heritable complex phenotypes such as height and other quantitative traits can already be predicted with reasonable accuracy from DNA alone. For many diseases, including important common conditions such as coronary artery disease, breast cancer, type I and II diabetes, individuals with outlier polygenic scores (e.g., top few percent) have been shown to have 5 or even 10 times higher risk than average. Several psychiatric conditions such as schizophrenia and autism also fall into this category. We discuss related topics such as the genetic architecture of complex traits, sibling validation of polygenic scores, and applications to adult health, in vitro fertilization (embryo selection), and genetic engineering.

From the introduction:
I, on the other hand, knew nothing, except ... physics and mathematics and an ability to turn my hand to new things. — Francis Crick 
The challenge of decoding the genome has loomed large over biology since the time of Watson and Crick. Initially, decoding referred to the relationship between DNA and specific proteins or molecular mechanisms, but the ultimate goal is to deduce the relationship between DNA and phenotype — the character of the organism itself. How does Nature encode the traits of the organism in DNA? In this review we describe recent advances toward this goal, which have resulted from the application of machine learning (ML) to large genomic data sets. Genomic prediction is the real decoding of the genome: the creation of mathematical models which map genotypes to complex traits. 
It is a peculiarity of ML and artificial intelligence (AI) applied to complex systems that these methods can often “solve” a problem without explicating, in a manner that humans can absorb, the intricate mechanisms that lie intermediate between input and output. For example, AlphaGo [1] achieved superhuman mastery of an ancient game that had been under serious study for thousands of years. Yet nowhere in the resulting neural network with millions of connection strengths is there a human-comprehensible guide to Go strategy or game dynamics. Similarly, genomic prediction has produced mathematical functions which predict quantitative human traits with surprising accuracy — e.g., height, bone density, and cholesterol or lipoprotein A levels in blood (see Table 1); using typically thousands of genetic variants as input (see next section for details) — but without explicitly revealing the role of these variants in actual biochemical mechanisms. Characterizing these mechanisms — which are involved in phenomena such as bone growth, lipid metabolism, hormonal regulation, protein interactions — will be a project which takes much longer to complete. 
If recent trends persist, in particular the continued growth of large genotype | phenotype data sets, we will likely have good genomic predictors for a host of human traits within the next decade. ...

Saturday, January 16, 2021

Harvard CMSA talks (video)

I recently came across this channel on YouTube, produced by CMSA at Harvard.
The new Center for Mathematical Sciences and Applications in the Faculty of Arts and Sciences will serve as a fusion point for mathematics, statistics, physics, and related sciences. Evergrande will support new professorships, research, and core programming. 
Shing-Tung Yau, Harvard’s William Caspar Graustein Professor of Mathematics, will serve as the center’s first director. 
“The Center for Mathematical Sciences and Applications will establish applied mathematics at Harvard as a first-class, interdisciplinary field of study, relating mathematics with many other important fields,” Yau said. “The center will not only carry out the most innovative research but also train young researchers from all over the world, especially those from China. The center marks a new chapter in the development of mathematical science.”
If I'm not mistaken Evergrande is a big real estate developer in China. It's nice to see them supporting mathematics and science in the US :-) 

In 2010 I accompanied S.T. Yau and a number of other US academics and technologists to visit Alibaba, which wanted to establish a center for data science in China. Unfortunately this never really got off the ground, but CMSA looks like it is off to a good start. 

Here are some talks I found interesting. There are quite a few more.

The talk on Atiyah, Geometry, and Physics led me to this poem which I like very much. Sadly, Atiyah passed in 2019. I believe we met once at a dinner at the Society of Fellows, but I hardly knew him.
In the broad light of day mathematicians check their equations and their proofs, leaving no stone unturned in their search for rigour. 
But, at night, under the full moon, they dream, they float among the stars and wonder at the mystery of the heavens: they are inspired. 
Without dreams there is no art, no mathematics, no life. 
—Michael Atiyah

Monday, January 11, 2021

Global AI Talent Flows

The illustration above describes a global population of ~5k researchers whose papers were accepted to the leading 2019 conference in deep neural nets. To be precise they looked at ~700 authors of a randomly chosen subset of papers. There is also a more select population of individuals who gave presentations at the meeting. This is certainly not the entire field of AI, but a reasonable proxy for it.

Global AI talent tracker:
For its December 2019 conference, NeurIPS saw a record-breaking 15,920 researchers submit 6,614 papers, with a paper acceptance rate of 21.6%, making it one of the largest, most popular, and most selective AI conferences on record. 
Key Takeaways 
1. The United States has a large lead over all other countries in top-tier AI research, with nearly 60% of top-tier researchers working for American universities and companies. The US lead is built on attracting international talent, with more than two-thirds of the top-tier AI researchers working in the United States having received undergraduate degrees in other countries.   
2. China is the largest source of top-tier researchers, with 29% of these researchers having received undergraduate degrees in China. But the majority of those Chinese researchers (56%) go on to study, work, and live in the United States. 
3. Over half (53%) of all the top-tier AI researchers are immigrants or foreign nationals currently working in a different country from where they received their undergraduate degrees.
Prediction: PRC share in all 3 categories will increase in coming decades as their K12, undergraduate, and graduate schools continue to improve, and their high-tech economy grows much larger. See Ditchley Foundation meeting: World Order today

Using conference papers as the filter probably misses a lot of world class work (especially implementation at scale) that is going on in PRC at tech companies. Note in the list below the only Chinese institutions are Tsinghua and Beijing universities. But I would be surprised if those were the main accumulation of top AI talent in China, compared to large tech companies.


Saturday, January 09, 2021

Spengler (Asia Times): American Democracy died on Capitol Hill

Note although this appears in the Asia Times column Spengler, the byline is Paul Muir, not David Goldman.
American democracy died on Capitol Hill 
No Russian cyberspooks, no Chinese spies, no jihadi terrorists – no external enemies of any kind could have brought as much harm to the United States as its own self-inflicted wounds. 
I spent last evening taking calls from friends around the world, including a senior diplomat of an American ally who asked me what I thought of the first evacuation of Capitol Hill since the British invaded in 1812. “I’m horrified,” I said. “So is the entire free world,” the diplomat replied. 
There are belly-laughs in Beijing this morning. The Chinese government daily Global Times taunted: 
... The world is watching ... the country that they used to admire descend into a huge mess. Chinese observers said this is a “Waterloo to US international image,” and the US has totally lost legitimacy and qualification to interfere in other countries’ domestic affairs with the excuse of “democracy” in the future.  
[[ When protestors in HK occupied their legislature, US propaganda hailed it as a victory for democracy... when the same thing happens here it is declared domestic terrorism. ]]
It’s actually worse than the Global Times editors think. 
If it were only a matter of Trump’s misbehavior, this disaster would be survivable. The trouble is that the popular belief in a vast and nefarious conspiracy has a foundation in fact: Starting before Trump’s term in office his political opponents abused the surveillance powers of the intelligence community to concoct a black legend of Russian collusion on the part of his campaign. The mainstream media, staffed overwhelmingly by Trump’s enemies, slavishly repeated this black legend until large parts of the population refused to believe anything it read in the newspapers or saw on television. 
The leadership of the Democratic Party, its allied media, and the Bush-Romney wing of the Republican Party decided to play dirty to expunge an obstreperous, incalculable outsider from the political system. And in doing so, this combination, America’s establishment, destroyed public trust in the Congress and the media. It’s no surprise that two out of five Americans now believe that a vast conspiracy rigged the 2020 presidential elections. 
The spectacle of a serving president inciting a mob against the US Congress to stop the certification of his successor held the world in morbid fascination. But the biggest problem isn’t Trump’s misbehavior, egregious as it is, but the eruption of popular rancor against the constitutional system that has made America a model of governance for the world. Leftist mobs last spring burned police stations and destroyed shopping districts in a rampage against supposed systemic racism, and Trump supporters desecrated the Holy of Holies of American democracy, the chamber of the United States Senate. 
Behind the minority of violent actors is a majority that believes the system is rigged against them – whoever “them” might be. The Democrats say that the system is rigged against African-Americans, women, and other minorities, and the Republicans say that a global elite has rigged the system against middle-income Americans. “Rigged elections” has the same resonance as “systemic racism.” These by-words imply that disagreement is prima facie proof of villainy: To deny that there is systemic racism is to be a racist, and to deny that elections are rigged is evidence of complicity in a vast plot. 
A quarter of Americans believe that Covid-19 was a planned conspiracy of one kind or another, according to the Pew Survey; just under half of Americans with a high school education or less believe this. One out of three believes that a “deep state” is trying to undermine Trump. I reject the first and believe the second: my colleagues at Asia Times and I have regular access to virologists in a number of countries with scientific credentials and no political agenda to pursue, and can sift scientific evidence and opinion. By contrast, I know personally enough of the actors in the so-called “deep state” to conclude that they are acting in concert to wreck the Trump Administration. I also know many of the writers who have exposed the “deep state,” including Andrew McCarthy and Lee Smith, to trust their bona fides. I denounced this conspiracy repeatedly in these pages, most recently in an essay entitled “The Treason of the Spooks” (Dec. 4, 2020). For details, see Andrew McCarthy’s 2019 book Ball of Collusion, which I reviewed in Asia Times, or Lee Smith’s The Plot against the President. 
Sometimes there is a conspiracy and sometimes there isn’t. But Trump’s political supporters, bombarded daily by fake news about Russian collusion and other alleged misbehavior, have come to distrust any criticism of their president. 
If Trump was right that the whole impeachment business was an extra-legal conspiracy on the part of his enemies, why shouldn’t they believe that the election was rigged? This is a lose-lose proposition. Assume that Trump is right, and the election was rigged. In that case the United States has become a banana republic and American democracy a twisted joke. Assume that he is wrong, and that nonetheless – as Sen. Ted Cruz (R-Texas) intoned to justify his refusal to accept the election outcome – 39% of Americans nonetheless believe that election has rigged, because their president told them it was rigged. In that case the public trust that makes democracy possible has collapsed. The people, as Bertolt Brecht observed after demonstrations against the Soviet puppet government in East Germany, have lost the confidence of the government, and the simplest course of action would be for the government to dissolve and for the people to elect a new one. 
... Americans are frightened for their future, with good reason. They see enormous rewards accrue to a handful of tech companies, and stagnation and decay in large parts of the rest of the country. Donald Trump gave them a frisson of hope, and the Establishment reaction against Trump confirms the popular suspicion that a malevolent global elite has seized control of their country. Trump shamefully exploited this suspicion to direct a popular storm against the Congress. 
The US is living off borrowing from the rest of the world. Its net international investment position fell by about $12 trillion during the past 10 years. And the federal deficit is now 15% of gross domestic product, the highest since World War II. What can’t go on forever, won’t (in the late Herb Stein’s famous formulation).

Thursday, January 07, 2021

YouGov on storming of capitol

I misread the last line of this when I first saw it... I thought 56% of all voters polled believed the election was stolen. Probably what it actually says is that 56% of people who believe the election was stolen think storming the capitol is OK.

These results suggest 30-40% of all voters think the election was stolen -- i.e., roughly 2x the number who approve of the storming:  0.21 / 0.56 ~ 38%

YouGov poll of 1,397 registered voters.

Wednesday, January 06, 2021

The Last Emperor

1987 seems so long ago. Watch this movie! 

Nine Academy Awards, including Best Picture, Best Director, and Best Score.

See also 

Twilight in the Forbidden City  (account of Sir Reginald Fleming Johnston, tutor to the last emperor of China)

Sunday, January 03, 2021

Two from Spengler (David Goldman at AsiaTimes)

David Goldman, a former banker, writes the Spengler column for AsiaTimes, where he is business editor. 

Huawei 5G in Germany, Japan, and S. Korea? 

Book Review: American Awakening: Identity Politics and Other Afflictions of Our Time, by Joshua Mitchell (Georgetown University) 

2. AsiaTimes tells Le Figaro why China is winning the tech war (interview)
LM: Germany just announced that it will allow Huawei 5G to be installed. What conclusions do you draw from this decision? Is this short-term logic, that will hand the control of big data to China? 
DG: To my knowledge, Germany has made no announcement, but the German media have leaked the draft law that the government will present to the Bundestag, which allows Huawei 5G. Trump’s defeat in the US election probably tipped the balance in favor of Huawei. Huawei always has viewed 5G as the core of an “ecosystem” of new technologies that 5G makes possible. ... 
LM: Obama had launched the Trans-Pacific Partnership. Now there is a China-led trade zone, the RCEP. Have Australians, South Koreans and others decided to go back to China in a realpolitik move, because they see America as a declining power, engulfed in internal wars and not to be trusted? 
DG: The Regional Comprehensive Economic Partnership will cut tariffs dramatically – by about 90% in the case of Japanese exports to China – and now China is trying to negotiate free trade areas with South Korea and Japan. Asian trade is now as concentrated within Asia as European trade is concentrated within Europe. 
The logic of the development of an Asian internal market is similar to that of the European Community, and it is not surprising that the Asians are creating a giant free trade zone. Australia is in a nasty fight with China, but it now sells a higher proportion of its exports to China than ever before. It could not afford to stay out of the RCEP. 
The American consumer for decades was the main source of demand in the world economy. Now the internal Asian market is far more important. South Korea, for example, exports twice as much to China as to the US. I am sure that the Japanese and South Koreans like the United States much better than they like China, but the economic logic behind an Asian free trade zone is overwhelming. 
An Asian free trade zone certainly is compatible with America’s role as the leading superpower, just as the European Community originally was formed with American sponsorship during the Cold War. 
The difference, of course, is that China’s economic strength makes it a magnet for all the Asian economies. In this context, it is noteworthy that Japan and South Korea politely rejected American demands to exclude Huawei from their 5G networks. 
To restore high-tech manufacturing, we would need the sort of tax credits and subsidies for capital-intensive industry that Asian governments provide; we would need the sort of support from the Defense Department that led to every important technology of the digital age, from microprocessors to the Internet; and we would need a greater emphasis on mathematics and science at every level of education. 
Above all, we would need the sense of national purpose that John Kennedy evoked with the space program or Reagan with the Strategic Defense Initiative. Considering that we have just spent several trillion dollars subsidizing incomes and supporting capital markets, another trillion dollars to support technological superiority doesn’t seem extravagant. ...

Tuesday, December 29, 2020

China CDC Director interview: vaccine progress, viroid sequencing, transmission via food/packaging


This is a recent interview with the PRC CDC head, which includes: 

1. Discussion of various vaccines. He confirms that their vaccine(s) are using the standard method (inactivated viruses), which a priori one might consider safer than the new mRNA type. Efficacy remains to be seen but he seemed to hint that they would be releasing some data/results in the next few days. 

2. He notes (at ~7m) that PRC is sequencing every new case of covid. They see all the mutant versions, and find that infections are coming both from visitors to PRC as well as from imported food/packaging! So the latter really happens. 

If anyone can find primary sources related to these topics I would be very interested.

Here is some discussion of the different vaccines: costs, ongoing validations, etc.

Thursday, December 24, 2020

Peace on Earth, Good Will to Men 2020

When asked what I want for Christmas, I reply: Peace On Earth, Good Will To Men :-)

No one ever seems to recognize that this comes from the Bible (Luke 2.14).

Linus said it best in A Charlie Brown Christmas:
And there were in the same country shepherds abiding in the field, keeping watch over their flock by night.

And, lo, the angel of the Lord came upon them, and the glory of the Lord shone round about them: and they were sore afraid.

And the angel said unto them, Fear not: for, behold, I bring you good tidings of great joy, which shall be to all people.

For unto you is born this day in the city of David a Saviour, which is Christ the Lord.

And this shall be a sign unto you; Ye shall find the babe wrapped in swaddling clothes, lying in a manger.

And suddenly there was with the angel a multitude of the heavenly host praising God, and saying,

Glory to God in the highest, and on earth peace, good will toward men.

Merry Christmas!

This has been a difficult year for many people. Please accept my best wishes and hopes for a wonderful 2021. Be of good cheer, for we shall prevail! :-) 

The first baby conceived from an embryo screened with Genomic Prediction preimplantation genetic testing for polygenic risk scores (PGT-P) was born in mid-2020.  

Genomic Prediction has now performed embryo genetic tests for almost 200 IVF clinics in many countries. Millions of embryos are screened each year, worldwide.

Five years ago on Christmas day I shared the Nativity 2050 story below. See also The Economist on Polygenic Risk Scores and Embryo Selection.

And the angel said unto them, Fear not: for, behold, I bring you good tidings of great joy, which shall be to all people.
Mary was born in the twenties, when the tests were new and still primitive. Her mother had frozen a dozen eggs, from which came Mary and her sister Elizabeth. Mary had her father's long frame, brown eyes, and friendly demeanor. She was clever, but Elizabeth was the really brainy one. Both were healthy and strong and free from inherited disease. All this her parents knew from the tests -- performed on DNA taken from a few cells of each embryo. The reports came via email, from GP Inc., by way of the fertility doctor. Dad used to joke that Mary and Elizabeth were the pick of the litter, but never mentioned what happened to the other fertilized eggs.

Now Mary and Joe were ready for their first child. The choices were dizzying. Fortunately, Elizabeth had been through the same process just the year before, and referred them to her genetic engineer, a friend from Harvard. Joe was a bit reluctant about bleeding edge edits, but Mary had a feeling the GP engineer was right -- their son had the potential to be truly special, with just the right tweaks ...

Monday, December 21, 2020


The videos below are about Lianda, a wartime university located in Kunming that was formed by the merger of Peking University, Tsinghua University, and Nankai University.
Lianda: A Chinese University in War and Revolution 
In the summer of 1937, Japanese troops occupied the campuses of Beijing’s two leading universities, Beida and Qinghua, and reduced Nankai, in Tianjin, to rubble. These were China's leading institutions of higher learning, run by men educated in the West and committed to modern liberal education. The three universities first moved to Changsha, 900 miles southwest of Beijing, where they joined forces. But with the fall of Nanjing in mid-December, many students left to fight the Japanese, who soon began bombing Changsha. 
In February 1938, the 800 remaining students and faculty made the thousand-mile trek to Kunming, in China’s remote, mountainous southwest, where they formed the National Southwest Associated University (Lianda). In makeshift quarters, subject to sporadic bombing by the Japanese and shortages of food, books, and clothing, students and professors did their best to conduct a modern university. In the next eight years, many of China’s most prominent intellectuals taught or studied at Lianda. ... 
Lianda’s wartime saga crystallized the experience of a generation of Chinese intellectuals, beginning with epic journeys, followed by years of privation and endurance, and concluding with politicization, polarization, and radicalization, as China moved from a war of resistance against a foreign foe to a civil war pitting brother against brother. The Lianda community, which had entered the war fiercely loyal to the government of Chiang Kai-shek, emerged in 1946 as a bastion of criticism of China’s ruling Guomindang party. Within three years, the majority of the Lianda community, now returned to its north China campuses in Beijing and Tianjin, was prepared to accept Communist rule. ...
My father attended this university at age 16, admitted via Tsinghua. Among its most famous alumni are the Nobel Prize winning theoretical physicists C.N. Yang and T.D. Lee. As the university only existed for 8 years, there are very few alumni still living.


I came across the 一条 Yit channel because I recently bought an Android Smart TV and it caused an increase in consumption of YouTube, etc. I got the TV to use as a big monitor but it's great for content as well. One of the most enjoyable things I do with it is watch seminars (e.g., in theoretical physics or AI)!

In case you are wondering I bought a 70inch HiSense on sale for under $400: good 4k picture and sound -- highly recommended!

Sunday, December 20, 2020

PPP and the Shanghai Girl

After PPP correction the PRC economy is significantly larger than the US economy, so it's important to understand what nominal GDP and its adjusted counterpart represent. 

This 2019 video follows a 26 year woman around during a typical weekend day. She lives in a $330 per month apartment in central Shanghai, a short walk to her office where she works as an advertising copywriter. You get a look at the apps she uses to order food and household supplies, keep up with fashion and culinary trends, pay at restaurants, etc.

Her monthly budget is about $2300 USD per month, and as far as I can tell her lifestyle would cost more than twice as much in NYC (e.g., Brooklyn), San Francisco, Chicago, or even a somewhat smaller US city. So the nominal to PPP correction of 2x may actually be conservative! Some have suggested that the PRC government deliberately understates its GDP in order to continue to claim "developing nation" status, and to not alarm US hawks (as if that were possible).

In late 2010 I was in Shanghai for a physics meeting, and blogged about dollar-yuan purchasing power parity (PPP).
Shanghai: PPP on the ground  
1 USD = 6.64 RMB. Average salary in Shanghai is reportedly 65k RMB or about USD $10k per annum. ... The IMF estimates that the PPP (purchasing power parity) vs nominal exchange rate adjustment for China is about a factor of 2 (i.e., PPP GDP is about twice nominal GDP). That doesn't sound entirely crazy to me but it's very dependent on choice of goods for the PPP basket. ... 
Haircut 10 RMB = $1.50. (My barber in Eugene = $11.) 
Dinner on campus 9 RMB = $1.35. 

Monday, December 14, 2020

The Celestial Empire

This lifestyle channel delivers daily vignettes from China (~5 minutes each), with an occasional episode from Taiwan. They have English subtitles, so offer a unique window into modern Chinese life. 

When I blogged from Beijing in the summer of 2019, some readers were surprised that I found parts of the city as aesthetically interesting as places in Tokyo or other iconic cities. 

Everything is advancing very rapidly in China, as you can tell from the videos. Below are some episodes I recommend. There are many more...

Kindergarten in renovated Beijing courtyard house.


Tibetan lodges.

Boat house in Fujian.


Struggles of an independent film maker.


Photographer documents lives of factory workers in Guangdong.


Buddha collection in Guangzhou.

See also China 1793 -- it looks like the 200 year down cycle may be over... Celestial Empire returns?

Amasa Delano was an American ship captain and distant relative of FDR who circumnavigated the globe several times as a fur trader. Most of the fur went to China in the 18th and early 19th century: Delano brought back porcelain to America. Even then there was a manufacturing trade deficit! He appears in Herman Melville's novella Benito Cereno.

Delano's book A Narrative of Voyages and Travels in the Northern and Southern Hemispheres (1817) describes his impressions of China in that era: 

China is ... the first for greatness, riches, and grandeur, of any country ever known.

Saturday, December 12, 2020

Hot and Cold Wars in the 21st Century

Both panels below are, in my opinion, realistic and focused on the key issues. Good discussion of competition in military technology is, in my experience, difficult to find for various reasons. On the US side there are strong MIC vested interests (e.g., in preserving the carrier-centric Navy) that lead to self-censorship of difficult realities. Also, very few analysts have actual technical and military expertise -- they are more likely to be "policy entrepreneurs" without deep knowledge.

See also The East Is Red, The Giant Rises and Ditchley Foundation meeting: World Order today.

See T.X. Hammes' report:  An Affordable Defense of Asia and this podcast interview with Marine Radio.


Robert Atkinson was also a guest on Manifold:

Bonus: blockchain based digital RMB?


Wednesday, December 09, 2020

Theory & Practice of Grand Strategy: Di Dongsheng, Renmin University (PRC)

Professor Di of Renmin University (a top university in Beijing, closely associated with the CCP) is now world famous, after Tucker Carlson and Donald Trump focused attention on his recent discussion of high level ties between PRC officials and US financial firms (second video below).
Di Dongsheng (LinkedIn CN) Professor Di’s research focuses on Political Economy of China’s Foreign Policy, Theories and Practices of Triangularity in International Relations, the Politics of Global Financial, Monetary and Investment Affairs, and the Theory & Practice of Grand Strategy.

Watch the first video below and decide for yourself whether he understands US politics and foreign policy better than most professors in the US.

I was more interested in the top video than the original one featured by Tucker/DJT. A few comments: 

1. He maps the US Deep State a bit too much onto government ministries in places like China or Japan, which also constitute a Deep State but are probably more meritocratically staffed. 

2. He is right that DJT's instincts lean more toward tariffs and trade deals (it often seemed he was reliving the US-Japan trade frictions of the 1980s) than towards hardcore technology and supply chain battles. 

3. Some of the really aggressive Deep State plotting against PRC came from DJT's own team -- it wasn't all pre-existing. In fact Trump's NSC green lighted a lot of nasty stuff that might now be reined in under Biden. I suppose you could argue that Trump's own NSC and cabinet were mostly Deep State people, but some like Navarro and Bannon certainly were not.

Glenn Greenwald (remember him? used to be a good guy until he started noticing too much stuff embarassing to the Left): The Hunter Biden Criminal Probe Bolsters a Chinese Scholar's Claim About Beijing's Influence With the Biden Administration Professor Di Dongsheng says China's close ties to Wall Street and its dealings with Hunter both enable it to exert more power now than it could under Trump.
... a Chinese scholar of political science and international finance, Di Donghseng, insisted that Beijing will have far more influence in Washington under a Biden administration than it did with the Trump administration. 
The reason, Di said, is that China’s ability to get its way in Washington has long depended upon its numerous powerful Wall Street allies. But those allies, he said, had difficulty controlling Trump, but will exert virtually unfettered power over Biden. That China cultivated extensive financial ties to Hunter Biden, Di explained, will be crucial for bolstering Beijing’s influence even further. 
Di, who in addition to his teaching positions is also Vice Dean of Beijing’s Renmin University’s School of International Relations, delivered his remarks alongside three other Chinese banking and development experts. Di’s speech at the event, entitled “Will China's Opening up of its Financial Sector Attract Wall Street?,” was translated and posted by Jennifer Zeng, a Chinese Communist Party critic who left China years ago, citing religious persecution [[ Falun Gong? ]], and now lives in the U.S.A source fluent in Mandarin confirmed the accuracy of the translation.
AddedWSJ Dec 10 : Barr Worked to Keep Hunter Biden Probes From Public View During Election. The attorney general knew for months about investigations into Biden’s business and financial dealings.

See also The East Is Red, The Giant Rises.

Sunday, December 06, 2020

AlphaFold 2: protein folding solved?


This is a good discussion of DeepMind's AlphaFold 2, a big breakthrough in protein folding. The details of how AlphaFold 2 works have not been published -- the video mainly discusses the January 2020 paper on the earlier version of AlphaFold, which already had world leading performance. However, it provides a good introduction both to protein folding as a physical / biological problem, as well as to AI/ML approaches.

I visited DeepMind in 2018 to give a talk on genomic prediction. I was hoping to get them interested! However, they were already focused on the protein folding problem. Most of my time there was spent discussing the latter topic with some of the AlphaFold team. They probably thought that a physicist who works on genomics might be worth talking to about protein folding, but I'm sure I learned more from them about it than vice versa...

In 2013 I blogged about a talk by Fields Medalist Stephen Smale on ML approaches to protein folding. He convinced me that ML approaches might work better than solving physics equations by brute force. 

Deep neural nets excel at learning high dimensional nonlinear functions that have some internal hierarchical structure (e.g., by length scale). Protein folding falls into this category. AlphaFold was able to utilize 170k training samples and extensive information from MSA (Multiple Sequence Alignment) which gives estimates of 3D distances: see, e.g., here.

Wednesday, December 02, 2020

Ditchley Foundation meeting: World Order today

Thursday and Friday (Dec 3 and 4) I will participate in this Ditchley Foundation event, in honor of Henry Kissinger. I'm unsure whether I'm allowed to say who the other participants are.

Unfortunately the event is entirely virtual, unlike the meeting on genetic engineering I attended there in 2019. (Slides

A big focus of this meeting will be the role of China in the World Order (their terminology). Apropos of that, see this analysis by German academic Gunnar Heinsohn. Two of his slides appear below.

1. It is possible that by 2050 the highly able STEM workforce in PRC will be ~10x larger than in the US and comparable to or larger than the rest of the world combined. Here "highly able" means roughly top few percentile math ability in developed countries (e.g., EU), as measured by PISA at age 15.

2. The trajectory of international patent filings shown below is likely to continue. Note the catch-up pattern of S. Korea vs Germany over 25 years.

See earlier post The East is Red, the Giant Rises.

Wednesday, November 25, 2020

Macroscopic Superposition States in Isolated Quantum Systems

Happy Thanksgiving! :-)
Macroscopic Superposition States in Isolated Quantum Systems   
Roman V. Buniy and Stephen D.H. Hsu 
For any choice of initial state and weak assumptions about the Hamiltonian, large isolated quantum systems undergoing Schrodinger evolution spend most of their time in macroscopic superposition states. The result follows from von Neumann's 1929 Quantum Ergodic Theorem. As a specific example, we consider a box containing a solid ball and some gas molecules. Regardless of the initial state, the system will evolve into a quantum superposition of states with the ball in macroscopically different positions. Thus, despite their seeming fragility, macroscopic superposition states are ubiquitous consequences of quantum evolution. We discuss the connection to many worlds quantum mechanics.
It may come as a surprise to many physicists that Schrodinger evolution in large isolated quantum systems leads generically to macroscopic superposition states. For example, in the familiar Brownian motion setup of a ball interacting with a gas of particles, after sufficient time the system evolves into a superposition state with the ball in macroscopically different locations. We use von Neumann's 1929 Quantum Ergodic Theorem as a tool to deduce this dynamical result. 

The natural state of a complex quantum system is a superposition ("Schrodinger cat state"!), absent mysterious wavefunction collapse, which has yet to be fully defined either in logical terms or explicit dynamics. Indeed wavefunction collapse may not be necessary to explain the phenomenology of quantum mechanics. This is the underappreciated meaning of work on decoherence dating back to Zeh and Everett. See talk slides linked here, or the introduction of this paper.

We also derive some new (sharper) concentration of measure bounds that can be applied to small systems (e.g., fewer than 10 qubits). 

Related posts:

Fun fact: Professor Buniy was a postdoc in my group at Oregon. Before coming to the US for graduate school in theoretical physics he was among the last group of young men to serve in the Soviet Army (Strategic Missile Forces IIRC!)

I suppose he has a document like this one:

Here he is in 2011, working on the null energy condition and instabilities in quantum field theories: 

Monday, November 23, 2020

Bruno Maçães on the election and Trump 2024


Post-election observations from Bruno Maçães. 

TrumpTV? Spectacle over Substance in 21st century American politics? Ivanka 2024? The Meme Industrial Complex?

If Bruno is correct the best we can hope for in the US is managed decline -- which is at least better than unmanaged decline!

Wednesday, November 18, 2020

Polls, Election Predictions, Political Correctness, Bounded Cognition (2020 Edition!)

Some analysis of the crap polling and poor election prediction leading up to Nov 2020. See earlier post (and comments): Election 2020: quant analysis of new party registrations vs actual votes, where I wrote (Oct 14)
I think we should ascribe very high uncertainty to polling results in this election, for a number of reasons including the shy Trump voter effect as well as the sampling corrections applied which depend heavily on assumptions about likely turnout. ... 
This is an unusual election for a number of reasons so it's quite hard to call the outcome. There's also a good chance the results on election night will be heavily contested.
Eric Kaufmann is Professor of Politics at Birkbeck College, University of London.
UnHerd: ... Far from learning from the mistakes of 2016, the polling industry seemed to have got things worse. Whether conducted by private or public firms, at the national or local, presidential or senatorial, levels, polls were off by wide margins. The Five Thirty-Eight final poll of polls put Biden ahead by 8.4 points, but the actual difference in popular vote is likely to be closer to 3-4 points. In some close state races, the error was even greater. 
Why did they get it so wrong? Pollsters typically receive low response rates to calls, which leads them to undercount key demographics. To get around this, they typically weight for key categories like race, education or gender. If they get too few Latinos or whites without degrees, they adjust their numbers to match the actual electorate. But most attitudes vary far more within a group like university graduates, than between graduates and non-graduates. So even if you have the correct share of graduates and non-graduates, you might be selecting the more liberal-minded among them. 
For example, in the 2019 American National Election Study pilot survey, education level predicts less than 1% of the variation in whether a white person voted for Trump in 2016. By contrast, their feelings towards illegal immigrants on a 0-100 thermometer predicts over 30% of the variation. Moreover, immigration views pick out Trump from Clinton voters better within the university-educated white population than among high school-educated whites. Unless pollsters weight for attitudes and psychology – which is tricky because these positions can be caused by candidate support – they miss much of the action. 
Looking at this election’s errors — which seems to have been concentrated among white college graduates — I wonder if political correctness lies at the heart of the problem
... According to a Pew survey on October 9, Trump was leading Biden by 21 points among white non-graduates but trailing him by 26 points among white graduates. Likewise, a Politico/ABC poll on October 11 found that ‘Trump leads by 26 points among white voters without four-year college degrees, but Biden holds a 31-point lead with white college graduates.’ The exit polls, however, show that Trump ran even among white college graduates 49-49, and even had an edge among white female graduates of 50-49! This puts pre-election surveys out by a whopping 26-31 points among white graduates. By contrast, among whites without degrees, the actual tilt in the election was 64-35, a 29-point gap, which the polls basically got right.
See also this excellent podcast interview with Kaufmann: Shy Trump Voters And The Blue Wave That Wasn’t 

Bonus (if you dare): this other podcast from the Federalist: How Serious Is The 2020 Election Fraud?

Added: ‘Shy Trump Voters’ Re-Emerge as Explanation for Pollsters’ Miss
Bloomberg: ... “Shy Trump voters are only part of the equation. The other part is poll deniers,” said Neil Newhouse, a Republican pollster. “Trump spent the last four years beating the crap out of polls, telling people they were fake, and a big proportion of his supporters just said, ‘I’m not participating.’” 
In a survey conducted after Nov. 3, Newhouse found that 19% of people who voted for Trump had kept their support secret from most of their friends. And it’s not that they were on the fence: They gave Trump a 100% approval rating and most said they made up their minds before Labor Day. 
Suburbanites, moderates and college-educated voters — especially women — were more likely to report that they had been ostracized or blocked on social media for their support of Trump. ... 
... University of Arkansas economist Andy Brownback conducted experiments in 2016 that allowed respondents to hide their support for Trump in a list of statements that could be statistically reconstructed. He found people who lived in counties that voted for Clinton were less likely to explicitly state they agreed with Trump. 
“I get a little frustrated with the dismissiveness of social desirability bias among pollsters,” said “I just don’t see a reason you could say this is a total non-issue, especially when one candidate has proven so difficult to poll.”

Tuesday, November 17, 2020

The East Is Red, The Giant Rises

Apologies for my recent inactivity. I've been busy finishing several projects and also distracted by our recent election.

Possibly the biggest global impact of this election is on US-China relations.

It seems likely that Biden will be our next president (although I am interested to see what closer inspection of the election reveals), and based on this I think odds have shifted in favor of a continued rise of the PRC in global economic and military power. I now think that the US lacks the will to counter China's continued rise: their main potential failure mode over the next 20 years is internal, not likely a consequence of external pressure. (Although of course there is still a chance the US and China will blunder into a war, with terrible consequences for the whole world.) 

Note I am not saying the US-China cold war or supply chain decoupling are off, just that the US is unlikely to put sufficient pressure on China to significantly retard its development over the next 20 years. This will have to be re-evaluated in 2024, of course, but we may pass the tipping point.

In 2004 I made some forecasts of where China would be in 2020. These forecasts were met with skepticism then but have mostly been correct. See

Benchmarks in China development: emergence of a middle class

Sustainability of China economic growth

My main assumptions were that the differential in growth rates between China and developed countries would average about 5 percent per year -- e.g. 7% vs 2%, and that China would largely close the technology gap.

A growth differential of +2-3% between now and 2050 would lead to a PRC economy which is about twice as large as the US economy (PPP). In 2004 I expected the PPP and nominal measures of Chinese GDP to narrow (I said over the next ~30 years, so I still have about 15 years for that to happen). If that occurs by 2050 then the PRC economy would be about twice as large as the US economy in nominal terms as well. GDP per capita in China would still be only half that of the US, but a 2-1 total GDP ratio has huge implications for geopolitics, the military balance of power, etc. (Note I am not even factoring in COVID-related impacts on the two economies, which are strongly in favor of PRC.) 

Another metric which should be carefully monitored is the ratio of STEM human capital between the two countries, which will continue to move significantly in China's favor.

I displayed the IMF figures below in my 2004 post on sustainability of Chinese economic growth. I felt that +20y along the trajectories described was realistic for PRC, and I was correct.

It would be interesting to see updated 2020 versions.


See also 

In my earlier post on Beijing I emphasized the issue of scale in China -- massive scale that is evident in the video above. 
I traveled in SE Asia before the 1997 currency / economic crisis. At that time there was plenty of evidence of a bubble in those countries -- unused infrastructure and real estate built on spec, few signs of real technological or productive capability, etc. China had aspects of that 10 years ago, but now it's apparent that earlier infrastructure investment is being put to good use. 
As I walked around Beijing I strained to find things around me -- buildings, solar panels, batteries, cars, high speed trains, electronics, software infrastructure, even airplanes -- that couldn't be sourced in China. Other than a few specific tech stacks that will get serious attention in coming years (e.g., CPUs) I was not able to think of many areas in which China has not caught up technologically. 
See Can the US derail China 2025?
There is a consistent Western cognitive bias concerning China: a severe underestimate of her capabilities and the capabilities of her people. This bias persists and analysts should carefully recalibrate in light of their previous predictions and the actual outcomes. Separate from this bias is an overall lack of knowledge and a willingness to accept lazy generalizations...

Saturday, October 31, 2020

Precision Embryo Genotyping and CRISPR Chromosome Deletions (Genomic Prediction)

This recent Cell paper received a lot of attention as it suggests that CRISPR editing can result in chromosome loss. It was cited in the recent National Academies report Heritable Human Genome Editing (2020) as an example of unexpected consequences / side-effects from CRISPR.
Allele-Specific Chromosome Removal after Cas9 Cleavage in Human Embryos  
Correction of disease-causing mutations in human embryos holds the potential to reduce the burden of inherited genetic disorders and improve fertility treatments for couples with disease-causing mutations in lieu of embryo selection. Here, we evaluate repair outcomes of a Cas9-induced double-strand break (DSB) introduced on the paternal chromosome at the EYS locus, which carries a frameshift mutation causing blindness. We show that the most common repair outcome is microhomology-mediated end joining, which occurs during the first cell cycle in the zygote, leading to embryos with non-mosaic restoration of the reading frame. Notably, about half of the breaks remain unrepaired, resulting in an undetectable paternal allele and, after mitosis, loss of one or both chromosomal arms. Correspondingly, Cas9 off-target cleavage results in chromosomal losses and hemizygous indels because of cleavage of both alleles. These results demonstrate the ability to manipulate chromosome content and reveal significant challenges for mutation correction in human embryos. 
BioRxiv preprint 

My Genomic Prediction colleagues Jia Xu, Diego Marin, and Nathan Treff are co-authors of the paper. GP's precision embryo genotyping capabilities were necessary to determine that a paternal chromosome is sometimes deleted in the embryo due to CRISPR. In GP's standard embryo testing process both parents are genotyped as well as the embryo. The parental genotypes are used to error correct the embryo genotype: DNA amplification starting from just a few biopsied cells introduces noise, but it can be removed. GP can determine whether specific alleles from a parent are present in the embryo. Detection of the deletion of an entire chunk of chromosome would be fairly straightforward.

Thursday, October 29, 2020

Othram helps solve cold case: killer of Siobhan McGuinness (age 5) identified after 46 years

Othram, a DNA forensics company I co-founded, has helped to solve another cold case. 

Montana Girl, 5, Was Abducted Near Home and Found Dead in Drain — and Killer ID'd 46 Years Later 
For 46 years, the family of Siobhan McGuinness waited to find out who killed the spunky 5-year-old back in 1974 
On a frigid February afternoon in 1974, Siobhan McGuinness was walking the short distance home from a friend’s house in Missoula, Montana, when she vanished. Two days later, the 5-year-old’s body was found in a snow-covered drain culvert near the exit for Turah on I-90, just outside the city limits. She had been sexually assaulted. She also sustained trauma to her head and stab wounds to her chest, according to the FBI. 
Detectives at the time searched tirelessly for the little girl’s killer, but came up empty. The case went cold for decades. 
On Monday, authorities announced that after 46 years, the Missoula County Sheriff’s Office Cold Case Squad, detectives from the Missoula Police Department and others had finally identified the man who took the life of the spunky child who was always smiling. Richard William Davis was 32 when he was traveling through the area at the time of Siobhan’s murder, Missoula Police Chief Jason White said at a press conference on Monday. ... 
Using DNA left behind at the crime scene, specialists at private technology company Othram Inc. were able to create a genealogical profile of the suspect, which led them to Davis, the company says in a press release.

See Othram: the future of DNA forensics

The existing FBI standard (CODIS) for DNA identification uses only 20 markers (STRs -- previously only 13 loci were used!). By contrast, genome wide sequencing can reliably call millions of genetic variants. 

For the first time, the cost curves for these two methods have crossed: modern sequencing costs no more than extracting CODIS markers using the now ~30 year old technology. 

What can you do with millions of genetic markers? 

1. Determine relatedness of two individuals with high precision. This allows detectives to immediately identify a relative (ranging from distant cousin to sibling or parent) of the source of the DNA sample, simply by scanning through large DNA databases. ...

If you have contacts in law enforcement, please alert them to the potential of this new technology.

Sunday, October 25, 2020

David Goldman (Spengler): China's Plan to Sino-Form the World

The latest from the always entertaining David Goldman, who writes (wrote?) the Spengler column at Asia Times.

In the lecture below, Goldman summarizes the main themes of his new book You Will Be Assimilated: China’s Plan to Sino-Form the World.


In this next interview (on the China-Iran deal of summer 2020) Goldman drops his guard a bit and waxes poetic with anti-Chinese rhetoric, as he discusses Israel, Iran, and China.

He refers to the Chinese (speaking broadly) as philo-semitic, but then jokes that this means anti-semites who like jews! In light of that remark I wonder how one should characterize Goldman's views on China and the Chinese: philo-sinic or just plain anti-Chinese?

Saturday, October 24, 2020

Composite Polygenic Risk Score predicts longevity

The paper below (senior author at Johns Hopkins University) builds a composite polygenic risk score for mortality (longevity). Outliers (top vs bottom 5%) differ by about 5 years in life expectancy. 

I expect longevity prediction to improve considerably with more and better data to analyze. See also Live Long and Prosper: Genetic Architecture of Complex Traits and Disease Risk Predictors:
We found that genetic risks are largely uncorrelated for different conditions. This suggests that there can exist individuals with, e.g., low risk simultaneously in each of multiple conditions, for essentially any combination of conditions. There is no trade-off required between different disease risks ... One could speculate that a lucky individual with exceptionally low risk across multiple conditions might have an unusually long life expectancy.

If I read the graph below correctly, in their late 70s a positive outlier (male) has ~90% chance of surviving (not sure of timescale, might be next few years? See comments), whereas for a negative outlier the odds are only ~75%.
Combined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality 
Allison Meisner, Prosenjit Kundu, Yan Dora Zhang, Lauren V. Lan, Sungwon Kim, Disha Ghandwani, Parichoy Pal Choudhury, Sonja I. Berndt, Neal D. Freedman, Montserrat Garcia-Closas, Nilanjan Chatterjee 
The American Journal of Human Genetics doi: 10.1016/j.ajhg.2020.07.002 
While genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry. The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.

Thursday, October 22, 2020

Replications of Height Genomic Prediction: Harvard, Stanford, 23andMe

These are two replications of our 2017 height prediction results (also recently validated using sibling data) that I neglected to blog about previously.

1. Senior author Liang is in the Deptartments of Epidemiology and Biostatistics at Harvard.
Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes 
Wonil Chung, Jun Chen, Constance Turman, Sara Lindstrom, Zhaozhong Zhu, Po-Ru Loh, Peter Kraft and Liming Liang 
Nature Communications volume 10, Article number: 569 (2019) 
We introduce cross-trait penalized regression (CTPR), a powerful and practical approach for multi-trait polygenic risk prediction in large cohorts. Specifically, we propose a novel cross-trait penalty function with the Lasso and the minimax concave penalty (MCP) to incorporate the shared genetic effects across multiple traits for large-sample GWAS data. Our approach extracts information from the secondary traits that is beneficial for predicting the primary trait based on individual-level genotypes and/or summary statistics. Our novel implementation of a parallel computing algorithm makes it feasible to apply our method to biobank-scale GWAS data. We illustrate our method using large-scale GWAS data (~1M SNPs) from the UK Biobank (N = 456,837). We show that our multi-trait method outperforms the recently proposed multi-trait analysis of GWAS (MTAG) for predictive performance. The prediction accuracy for height by the aid of BMI improves from R2 = 35.8% (MTAG) to 42.5% (MCP + CTPR) or 42.8% (Lasso + CTPR) with UK Biobank data.

2. This is a 2019 Stanford paper. Tibshirani and Hastie are famous researchers in statistics and machine learning. Figure is from their paper.

A Fast and Flexible Algorithm for Solving the Lasso in Large-scale and Ultrahigh-dimensional Problems 
Junyang Qian, Wenfei Du, Yosuke Tanigawa, Matthew Aguirre, Robert Tibshirani, Manuel A. Rivas, Trevor Hastie 
1Department of Statistics, Stanford University 2Department of Biomedical Data Science, Stanford University 
Since its first proposal in statistics (Tibshirani, 1996), the lasso has been an effective method for simultaneous variable selection and estimation. A number of packages have been developed to solve the lasso efficiently. However as large datasets become more prevalent, many algorithms are constrained by efficiency or memory bounds. In this paper, we propose a meta algorithm batch screening iterative lasso (BASIL) that can take advantage of any existing lasso solver and build a scalable lasso solution for large datasets. We also introduce snpnet, an R package that implements the proposed algorithm on top of glmnet (Friedman et al., 2010a) for large-scale single nucleotide polymorphism (SNP) datasets that are widely studied in genetics. We demonstrate results on a large genotype-phenotype dataset from the UK Biobank, where we achieve state-of-the-art heritability estimation on quantitative and qualitative traits including height, body mass index, asthma and high cholesterol.

The very first validation I heard about was soon after we posted our paper (2018 IIRC): I visited 23andMe to give a talk about genomic prediction and one of the PhD researchers there said that they had reproduced our results, presumably using their own data. At a meeting later in the day, one of the VPs from the business side who had missed my talk in the morning was shocked when I mentioned few cm accuracy for height. He turned to one of the 23andMe scientists in the room and exclaimed 

I thought WE were the best in the world at this stuff!?

Blog Archive