chrisamiller

People are living longer and age is a dominant risk factor for cancer. In a world where cancer care wasn't improving, we'd expect to see massive increases in deaths due to cancer. What's also not captured by that number are the years of life after cancer diagnosis, which for many cancers has gone up dramatically. It's a tough problem, but the curves are bending in the right direction.

If you want a more punctuated example, how about gene therapy, which is doing things like restoring (partial) vision to the blind. https://www.smithsonianmag.com/smart-news/new-gene-therapy-p... Early days still, but we've laid the foundation for a really exciting next decade or so in genomic medicine.

Maybe your car hasn't changed, but your cancer care sure as hell has. The medical and biological sciences are where a lot of innovation has taken place, and the pace of technological advancement in things like DNA sequencing (as one example) is breathtaking.

I firmly agree that we've crossed several tipping points and that adaptation is a large and necessary part of our response. You seem to ignore that there are degrees of badness here, though!

Limiting warming to 2 or 3 degrees C is going to result in a situation that's a heck of a lot better than what 6 or 7 degrees C looks like. When asked if we should adapt or spend money on renewables/carbon capture/etc, the answer should be "Yes". We should be doing all of these things.

LastPass costs $36 per year. Operating on the principle of being the customer and not the product, that seems very reasonable for a secure way to store and share the keys to my digital life.

That said, it does make it a little bit harder for me to onboard my friends and family when they ask. One of the selling points has always been "Yes, you can use it on your phone and laptop" and "no, it doesn't cost anything".

That all depends what you want to do with the data. For assembling new genomes, they produce very long reads that are essential for "scaffolding". They're also great for structural variant detection (large rearrangements of DNA). DNA sequencing is not a monolith and there's room for lots of different complimentary technologies.

The economy cares very much about this virus. The stock market does not. The disconnect between the two is yet another sign of how vast the inequality gap is at the moment.

I'm sure this is abnormal for the Bay Area, but insane seems kind of overblown - this doesn't sound out of the ordinary for the midwest at all. Thunderstorms, hail, and occasional tornados are routine in the summer.

Just last week, the windspeed equivalent of a category 2 hurricane rolled through IA/MO/IL, destroying homes, business, and billions of dollars of crops: https://twitter.com/coldbrewedtool/status/129407960042804429...

Preprint servers have been an amazing boost to the speed at which science is able to progress. The benefits unambiguously outweigh the small number of cons, in nearly everyone's opinion.

The fact that the press can't help sensationalizing things and can't be half-assed to understand that this is not peer-reviewed doesn't change it's utility. I mean ffs, there is a giant banner at the top of the page that says:

"bioRxiv is receiving many new papers on coronavirus SARS-CoV-2. A reminder: these are preliminary reports that have not been peer-reviewed. They should not be regarded as conclusive, guide clinical practice/health-related behavior, or be reported in news media as established information."

Ignoring that is just shitty journalism.

This thread from another virologist casts some doubt about the claims of selective advantage proposed in this preprint: https://twitter.com/trvrb/status/1257825352660877313?s=19

Science in action, folks. It's sometimes messy, but usually converges on the truth

FWIW, I have this same BoA issue and have been trying for months to escalate it to someone who can actually do something about it. It's frustrating, to say the least.

Unfortunately, there still is no such thing as "basic" analysis of DNA. :)Ewan Birney has a great quote about this:

Sequencing, analysing and interpreting genomes is ‘routine’ in the same way the US Navy ‘routinely’ lands planes on aircraft carriers. It might happen regularly by well trained crew with the right equipment but it is not an easy thing to do. https://twitter.com/ewanbirney/status/1040144488948281344

That said, an Oxford Nanopore sequencer + a laptop is probably the closest thing to what you want.

> How would such a mutation help her lineage? But that same question, more broadly, how do mutations that benefit people past their child bearing age factor into human evolution?

To oversimplify a bit, you can think of most mutations as neutral, in terms of reproductive fitness. People (and populations) accumulate them all the time, just by chance. Occasionally, one that was previous neutral becomes beneficial when the environment changes - say, when it confers immunity to a virus, or helps with synthesizing an amino acid that's in short supply. This is why having a big population with lots of variation is beneficial and why bottlenecks hurt the viability of a species.

All the time! People propose hypotheses, supported by some preliminary data, and then they need to be tested. Some problems are easy, some take years or decades to be overturned. It's messy sometimes, but that's how science is supposed to work!

I often recommend Aaron Quinlan's excellent course if people want to learn a more hands-on and practical set of skills related to computational genomics and bioinformatics.

https://github.com/quinlan-lab/applied-computational-genomic...

Very few places, but there's no reason that it couldn't be. Such a plan would have to come with some substantial changes/restrictions on colleges to help rein in the ballooning costs (e.g. lazy rivers, gourmet cuisine) that are pushing costs up dramatically.

So you get an education for free, then pay back into the system after you're in the workforce? Congratulations, silicon valley, you've just re-invented public education!

Imagine what our public universities could look like with solid funding increases (which would be a fraction of that 17% that this group wants to take). They could be both free and amazing.

The biggest difference between academic tools and those in industry is that they're sinking major funds into producing (expensive, hard to produce at scale) training data. That, in theory, should allow them to develop better algorithms for actually predicting which mutations in the tumor are going to be the best (immunogenic) targets. This tool, and several others like it, are modular enough to allow you to plug in whatever prediction algorithm you like, while still getting the benefit of all the other steps.

Not sure why this is grey - many animals adapt to their environments very quickly. If all the drones are doing is buzzing the birds, they may very well learn to ignore them.

Those of us in academia are (mostly) pushing hard for open access policies. We want our work to be disseminated as widely as possible! What makes it difficult is that publications and journal reputation are still used as a measure of success for promotions, tenure, grants, etc. If you have a finding that can be published in Nature or NEJM, it's really hard to go elsewhere out of principle, when you know that it may hurt your future prospects.

This thinking is slowly beginning to change, and the rapid growth of preprints in biology is helping a lot as well. There is growing recognition that journals in their traditional form may not be a great thing for science. There are a lot of different ideas about what the future of publishing and scholarly communication look like, and lots of experiments are being done right now.

Yeah the desktop web version is a massively better experience (though not stellar either, tbh). It says something that it's still a good tool despite those shortcomings

It's a SNP chip and only covers a few common mutations.

To anyone who wants to know for sure whether you're at increased risk of breast cancer, you'll want to get a test that sequences all the known mutations, along with another half-dozen or so genes that can have essentially the same effect as a damaging mutation in BRCA. I'd also urge you to find a genetic counselor, who can help explain the diagnosis in detail, as well as the limitations of the each kind of test.

I'd urge you to be cautious when interpreting those data. The effect size of most of these SNPs is tiny, often explaining (at most) only very small amounts of the variability observed between groups. This is especially true for things like personality traits, which have a huge environmental component.

So, if finding out the empathy thing is fun, then by all means, keep poking around in your data! Promethease is probably the best of the bunch, and I've run my data through it. Just be mindful of the evidence level and effect size!

It might be marginally more feasible to build an enormous space tether (https://www-istp.gsfc.nasa.gov/Education/wtether.html). By dragging it through Earth's magnetic field (which extends out past the moon on the "downstream" side of the solar wind), you could: 1) generate large quantities of electricity, which would be extracted by orbital energy 2) use that electricity in some useful way to further slow momentum (like powering some of the ion engines they talk about in the article).

Anyone with a stronger physics background want to do the math and tell me why this won't work (or at least be marginally better than the proposal in the article?)

It's really comparing apples and oranges. If you want a 30x whole genome for genotyping, you'll use short read technologies and it'll be way less expensive.

The enormous reads offer a different window into genomes, by spanning repetitive regions where short reads can't be accurately placed. For lots of applications, the sweet spot is to use long reads for "scaffolding", then build up coverage with short reads.

Culturing is the problem, though, right? Many types of bacteria (including some pathogens) really do not like to grow on most media. There's no doubt that sequencing is the future of infection diagnosis. It's just a matter of how long it takes to get there (cost and complexity both have to drop).

It far outstrips Moore's law :)

https://www.researchgate.net/profile/Orit_Shaer/publication/...

Niche uses where long-read sequencing is required (denovo assembly, reference improvement, bacterial genomes, whole-isoform transcriptomes. Nanopore is starting to eat into that market, though.

Be careful about defining "high coverage" as 30x. Many applications (especially cancer) really require 100x or more to overcome purity and ploidy, or to identify subclonal populations.

It's definitely a good starting place for people from a CS background, but if you really want to learn biology, don't get too attached! As you get deeper, you'll quickly discover the limitations of that analogy.

And the public reference genome is about 2/3 from a single African American individual from Buffalo, New York!