chrisamiller

The short answer is that it was useful! The parameter space of things that have been tried in uncountable organisms over _billions_ of years is vast.

And proprioception is incredibly useful, even in small doses. Imagine you're a single-celled organism:

At the simplest level, some vague sensory input about your surroundings so that you can avoid the predator/find the food gives you a massive advantage over other organisms that can't. Every random mutation that improves this ability, even a tiny bit, is rewarded, as you can grow faster/die less and ultimately, reproduce more. (this is what we call "fitness" - how many of your genes get passed on).

If you get a mutation that hurts this ability, you're going to be massively penalized - eat less, grow slower, reproduce less.

In pretty short order, the organisms with higher fitness are going to take over.

Mutations occur all the time. In humans, the rate is very low - about 3 new mutations during every cell division. In many bacteria, the fidelity rate is much lower, and the reproduction rate is much higher, and so they are _constantly_ exploring new combinations of parameters. Most are neutral, many are disasterous, a few give a slight advantage.

Pile up these small advantages over millions or billions of years, and gradually, in fits and starts, very complex abilities evolve.

The senior author has a long history of bad science on autism and is funded by an anti-vax group. There's a [complete takedown of this bad science here]((https://respectfulinsolence.com/2017/11/29/christopher-exley...)

There is a reason that this is published in the "Journal of Trace Elements in Medicine and Biology", and not in something more reputable.

The US has a ludicrous amount of sparsely settled farmland in the interior. Why not just build more windfarms there? That dramatically reduces the cost and technical challenges. Yes, there are transmission losses to factor in, but at least based on the wikipedia article it seems like those aren't necessarily dealbreakers.

https://en.wikipedia.org/wiki/Electric_power_transmission#Lo...

Is there anyone with expertise in the subject that can weigh in?

Most estimates I'm familiar with are substantially lower than that - between 0.1 and 3 errors per cell division.

Right - It's not so much algorithmic development as development of the toolchains that will enable such representations to be actually useful for downstream analyses.

You're right, and the next frontier in genome assembly and mapping algorithms is using graph-based genomes, where differences between individuals or populations can represented as different paths through a sequence graph. (There are lots of better explanations with pretty pictures out there with a little searching)

I am likewise a staff scientist by choice. I'm confident that I have abilities and track record that would allow me to start my own lab if I wanted to, but I value being able to do science instead of writing grants full time. Our current system excels at taking bright scientific minds and turning them into middle managers.

Indeed. The lack of continuity is killer, not just for the people working in that lab, but for science as a whole. That model is how we get shitty unsupported bioinformatics packages, experiments that no one can replicate, etc.

Cancer genomics researcher here. I agree wholeheartedly about getting sequencing done if you have cancer - it's what I would do for myself or my family. Two minor quibbles about your thoughts:

1) Exome sequencing is below $1000, but analyzing that data adds a non-negligible cost. Still, even 2 or 3 grand is way cheaper than wasting time on treatments that won't work. Whole-genome sequencing is even better (for a little more cost) because of the extra types of information it adds about structural variants and copy number changes.

2) We're reasonably sure that most cancer causing variants are in the coding space, but there are undoubtedly some in non-coding regions (and classes of large structural events like duplications or deletions that affect both).

It's the best time in the history of the world to have cancer, and it is only getting better. Survival curves are slowly bending, and new classes of treatments like immunotherapies are helping to bend them even more.

The bottom line is, If you get cancer, fight like hell to get your tumor sequenced. Most insurers cover at least some kind of genomic test for cancer these days.

There are lots of companies in the immunotherapy space. Don't limit yourself to industry, though - lots of academic labs working on this that are in desperate need of good coders and data scientists.

Boy, there are an awful lot of assumptions made there. In a senate race decided by 312 votes, there are dozens of factors that could have swung that outcome. Traffic, the weather, a bad batch of lettuce keeping some people home with food poisoning, etc. To chalk that win up to non-citizen voting requires ignoring an awful lot of other pieces of the puzzle.

Medical research is generally aimed at the most pressing problems facing a society. Infectious disease was a focus for a long time, cancer is one of the biggest targets now. Aging has not been a priority yet, because the vast majority of people die of something else (infections, heart attacks, cancer, etc) before they die of the problems specific to extreme old age.

When we develop treatments capable of reducing the incidence of more common diseases, then focus will shift towards aging and the curve may very well start to bend towards longer lifespans.

If you want this to occur sooner, support more overall scientific funding through your donations, your votes, and your advocacy.

I came in to say exactly this. Google Scholar alerts are incredibly useful.

I can vouch that the hammerlab is legit and doing solid science! I've had great interactions with members of their lab and have been impressed by their work, as well as their committment to open source and open science (preprints, etc).

To piggyback, if you are interested in personalized cancer vaccines, we're also hiring at WashU for a senior scientist position that will be working at least part time on immunotherapy and personalized cancer vaccines. If you're an interdisciplinary person, who knows cancer and can code, drop me a line (c.a.miller at wustl.edu)

Any paper I peer review better have source code available or they will hear about it. That said, yes, there isn't time (or funding) to actually re-run the entire analysis.

Our genomics workflows use dozens of packages even before I get the data and start really doing analysis, statistics, and plots. It's just not feasible to cite every bit of code we use (though we certainly point people to the higher level routines, which they can use to see what was run/how to reproduce the results).

Exactly. Mosh for instantly resuming my connection, screen for resuming my sessions (and adding scrollback and such)

This article is a little bit breathless. In the academic circles that I run (genomics, computational biology, cancer), bioArxiv is not "going rogue". It's becoming pretty common, and will continue to increase in popularity as the FUD surrounding preprints and high-impact journals begins to dissipate. i.e. Nature won't accept my paper if it's on bioArxiv! (Yes they will).

This is my concern as well.

My privacy threshold is pretty low (my username across most of the web is my real name, for example). This, though, is an always-listening device in your home, that connects directly to a company who's stated goal is to sell you more things. That, combined with the potential for abuse/hacks/subpoenas, crosses a line for me.

It feels a lot like the GPS trackers that insurance companies want to put in your car, which I also think is a bridge too far.

I assume that under the hood, they've just set up Gmail as an IMAP client that accesses your other account?

Here: - Stop smoking, - keep active and at a healthy weight range - reduce red meat consumption (and barbecued/charred food) - reduce your alcohol intake - wear sunscreen.

Boom - you've just covered most of the risks that you can control.

Many cancers really aren't avoidable, as there's a spectrum of causes. The mutations that cause cancer can come from many sources - carcinogen exposure, UV light/radiation, inherited defects, or unavoidable errors that occur when cells divide (on average, around 3 errors per cell division).

Getting cancer is a lot like playing the lottery (or perhaps more accurately, Russian Roulette). It requires an accumulation of mutations in two or more key genes, and these mutations occur more or less randomly throughout the genome, regardless of cause. So maybe your first hit happens from a chest X-ray, and the second hit comes from smoking. Or maybe you just get old and the replication errors pile up in blood stem cells, giving you leukemia.

The point is that it's all probablistic, and that's why some smokers live to be 100 cancer-free, and some health-nut marathoners get cancer. In general, though, these external factors can bend the odds one way or the other.

This exists and has been used successfully in a number of large consortia, like the Cancer Genome Atlas. It essentially says that the data goes live immediately, but the researchers who generated the data have exclusive publishing rights for 6 months from that date. After that, it's fair game for anyone.

You're right, of course. BRAF mutations alone don't cause cancer. They're caused by the accumulation of key mutations coupled with clonal expansion. I oversimplified a bit while making a point about basket trials.

Your points are right on - I oversimplified while trying to explain the concept.

I don't agree with much that Tom Coburn says, but he's right that 'data silos' are a big problem in cancer research. To elaborate on a few points:

- While enrolling 500 people with breast cancer in a study might be easy enough at one academic hospital, there are lots of rare cancer types. It's fiendishly hard to gather enough cases to do real research on these, and samples are like gold, so people are resistant to sharing.

- There's lots of duplication of effort. While studies funded by the NIH are required to deposit their data, what's being deposited is raw sequence data, which requires lots of computation, disk, and skill to turn back into useful information about the mutations in cancer.

- The clinical data (phenotype) that is released with studies is often incomplete or vague enough to be useless

- Getting data into and out of these access-controlled repositories is, to put it mildly, a pain in the ass.

We do need to protect people's privacy, but removing some of these hurdles would go a long way towards accelerating the field.

I'm sorry that you think academia isn't "with the program". There's lots of great basic and translational research going on in the academic sphere. Can you at least elaborate, if you're going to paint us all with a broad brush?

Mutations in the BRAF gene, to name one druggable example, are a cause of many different types of cancer - melanoma, some breast, small-cell lung cancer, etc. Under the current paradigm, each type of cancer is treated as a different disease and requires a different clinical trial. This is bad.

What should happen (and is beginning to happen, with "basket trials") is that cancers are grouped by their genetic profile, instead of their tissue of origin. The BRAF V600E mutation is targetable with Vemurafenib, and so that drug should be used regardless of whether you have breast cancer or lung cancer.

This has no business even being reported on. It's preliminary data, not peer-reviewed, very small sample-size, etc. To say that the jury is still out would be premature - the jury hasn't even been convened yet!

The service mentioned here (Paribus) seems great, but there is no way in hell I'm giving them unfettered access to my mailbox to scan for receipts. I understand that the balance between privacy and convenience is different for everyone, but this is way beyond my comfort level.