Growing Pains for Field of Epigenetics | Hacker News Reader

Growing Pains for Field of Epigenetics

nytimes.com

43 pointstosseraccount11 comments

Demethylating agents, HDAC inhibitors, and their like can induce powerful effects on malignancies via (purportedly) primarily epigenetic mechanisms. I've seen patients with astronomically high leukemic counts return to normal blood counts on a few weeks of romidepsin, for instance.

But when groups use epigenetics to study poverty related stress, risk of depression, etc, there is a very different political structure than when comparing drugs to see what kills cancer cells in a dish. The trend seems to be to publish borderline findings with a nature vs nurture argument to explain differences as environmental, not genetic, and call for action as well as more funding to expand the research and find ways to environmentally or behaviorally prevent the problem. Optimistically, it's trying to solve problems. The issue is that important findings will be mixed in with a lot of questionable results that sound appealing to liberal academic journal editors and get a free pass at publication in top journals, a process which feeds back into the SJW gravy train of getting more academic grants to do more of the same. And with sciency techniques and big data approaches, what could be more fashionable? It really does a disservice to the subset of epigenetic research which is well conducted and reproducible. If the epigenetics bubble pops a bit, good. Other fields could use the attention.

Your argument was cogent and reasonable until you used the term "SJW". It's a useless term, meaning different things to different people.

The point you seem to be arguing could also be applied to the funding of string theory, and is one that I agree with. You won't find people like Lee Smolin saying that the disparity in research funding in these areas is due to "SJWs", rather they would point to the short term vision of those who provide the funding (amongst other factors).

I agree, SJW is a pretty useless term. You're right. And I don't know much about string theory funding. I can only postulate. Regarding short term vision, medical research funding has consequences on huge outlays of public resources outside of the short-term vision of research funding you mentioned. Maybe string theory has very close parallels, but for example when it was recommended everyone get interval colonoscopies at certain ages, hundred of millions of dollars of government money suddenly shifted to this purpose yearly for just one procedure (in this case a heavily vetted evidence backed decision). When, in contrast, attention is cast on politically popular issues with questionable research methods and publish-bait articles, it siphons funding away from less hot-topic issues that stagnate or die (for example, the defunding of even the best state psychiatric programs, which are popularly are associated with horror movies and don't get much too love by activists). The impact is immediate and severe outside of the world of researchers, and enormously politicized throughout the nation/media. I'd love to hear the string theory side of this though!

This has a lot to do with PR and how it relates to research and development funding. The root problem is that, with regards to funding (as far as I can tell), a headline in a popular newspaper or popular-science magazine is worth orders of magnitude more than a peer-reviewed paper in a journal. This will be a problem for all of the sciences in the near future, as long as there are differing tracks of research being explored.

The scientific method dictates that something should be ideally explored until it's dis-proven. Unfortunately, the realities of limited R&D funding dictate that only the most popular, or public, research tracks tend to attract the funding. This has a carry-on effect in that new students in these fields are forced to go into the most popular fields of study, lest they not get funding.

WRT string theory, have a look at https://en.wikipedia.org/wiki/The_Trouble_with_Physics . I'm not sure I 100% agree with Lee Smolin on this (he has a definite axe to grind), but the points he raises are equally applicable to any field of contentious, or cutting edge research.

Solving this is difficult. Obviously education of the general populous will help, but in lieu of this, perhaps we need mandated percentages of funding to each viable research track (a solution rife with problems of it's own).

In any case, this is a hard problem to solve, and will certainly cause problems in many areas of fundamental research in the future.

What's interesting is that this is the most up voted comment. If this volume of negativity was directed at a SV tech sector it would be downvote city. Heck, even mentioning "SJW" should have greyed out this post. From a biologist, congrats for beating the system!

As I see it pretty much from inside, this is not a general problem but just the evolution of science, as we are able to determine more and more things which lead to better and better conclusions. The problem in what is cause and effect comes from the sheer amount of data you create (for a current study we have whole genome methlaytion data for 19 cell populations in mice, all in triplicates and at medium coverage), which is obviously prone to many false positives. And as we are now approaching single cell level (which will dramatically improve results), this number is only going up. And of course it is hard to check all these positives extensively. But yeah, this is sciece and we are only getting better, so no pain but just an opportunity. A problem is rather the amount of data we create (we are speaking about Petabytes) that have to be stored and made accessible for decades so we can later recheck our conclusions. Nobody wants to pay for that

Im interested in chatting on versioning in this data ( and possibly by extension, compression ) . Happen to have a method to contact you ?

Not in this case as the data I described is on embargo. The problem is more general for all genomic data that has already been made public but were funding runs out after 5 years or so. I happend to chat to a postdoc the other day who is involved in the ICGC cancer consortium and had already some thoughts about the problem. If you want I can ask him whether he wants to contact you.

Would love to chat with him!

I don't really think, except in the case that you are legally required to store the raw data for decades, that there is any reason to store petabytes of data to recheck your conclusion. I'm not aware of any retention policy generally required of scientists to do that- nor do I think the value of being able to recheck a conclusion by investigating this kind of raw data is really required.

If it was required, you'd be willing to pay the (large, but economically justified) cost of archiving the data.

I am working with some epigenetics data right now (chip-seq on histone modifications). The main problem I see is that there doesn't seem to be any mature framework for analyzing the data. There are a bunch of disparate methods for different aspect of the data analysis that all seem to give different results.

From the data generation perspective, there are so many possible sources of biases from preparing the biological sample to sequencing of the sample, it can be difficult to control for all these variables in the down-stream analysis.

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