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