A Plea

Please, please, please, please... document your data.

It's not fun to get a matrix without any column or row labels. Like my old physics teacher used to say when somebody proudly proclaimed that the answer to an exercise was 5.029, "5.029 what? Elephants?". In physics, a quantity is not meaningful without a unit, and in data management, a matrix is not useful without labels.

It's not fun to know nothing about any preprocessing of the data. Has it been normalised? I guess I can check the mean and standard deviation, but what if it's only close to 0 and 1, but not exactly so? Was that some special normalisation method? Hell if I know.

It's not fun to know nothing about the experimental setup. Maybe you told me every second data point is a wildtype. Does that mean that these were results from two-colour arrays? Or two singe-colour arrays? Are the wildtypes from the same time point as the mutants? Come to think of it, are these even time-course data?

It's not fun to know nothing about what the biologists* want you to find. Are they looking for similarly expressed genes or for regulators? Would they rather have a network of the knocked-out genes or of all genes? Is it worse if I give them false positives or false negatives?

So please, please, please, document your data. Maybe some time in the future I will tell you about fun things called wikis and databases, but for now even a text file would do.

*Or insert other applied science here.

Research is Easier if You Make It Up

Yes, I know I haven't written in a good few months. In my defence, I have been kept quite busy by the research for my MSc project. Now that it is done, however, I'd like to share a few thoughts on my first real experience with research.

For this first post, I want to talk about what was perhaps the most humbling experience, and that was how tempting it was to cheat.

Like many research projects, my research was beset with problems. There were contradictory results, vague results, results that were the opposite of what we expected, without any indication why this happened. And often, when I got these results, I would think: "Gee, wouldn't it be nice if I could make up the results I wanted instead."

Now before you cast the first stone, let me be very clear: I did not fake any results, nor will I hopefully ever do so. But it got me thinking. How easy would it really be to fake results? For my MSc project, it would have been really easy. We do not have to hand in the code (although it is possible that the markers may ask for the code if they smell a rat, but let's assume for the sake of the argument that the faked results are completely convincing), so I would not even have to write the programs. I knew how the different experiments were supposed to work, so generating some convincing results would have been easy. The only people to see the results are my supervisor and a second marker. Of those two, only my supervisor could possibly spot fake results, because the second marker is not an expert in the field. If I had gotten any fake results past my supervisor, I would basically be home free.

You might be thinking that that's all very well for a Masters project, but surely in real research faked data would be spotted. But would it really? I agree that you would probably have difficulty faking a whole project: You'd be hard-pressed to answer questions from reviewers of your paper, and anyone trying to repeat the experiments would obviously get very different results. But what about just tweaking that one experiment that's poking a hole in your theory? That would again be very easy and would probably not be spotted unless somebody decides to repeat that exact experiment. If somebody later disproves your theory, well, you got a paper out of it, and nobody can really blame you for not spotting the flaw when all of your experiments were confirming the hypothesis.

Cheating can get even more subtle (choosing your experiments, skimping on controls, omitting results) and harder to spot. So the question is, given how easy it would be to cheat, what, other than personal integrity, is keeping scientists honest?

I believe curiosity and ambition are big factors. If you get results that contradict your hypothesis, you don't just say "Aw, crud", you get excited, because there's another problem to solve. Maybe this new problem will lead to an even bigger discovery than the one you were hoping to make. If you just fake the result, you'll probably never do really ground-breaking science. Worse yet, you might set back other scientists who will not pursue their theories because your "results" seem to have disproved them.

There's also training and your research environment. Never underestimate social conformity, which in this case is a good thing. If everybody around you is excited about research, as most scientists will be, you'll find it very hard to be the cheater, even if you're the only one who knows that your results weren't real. You'll want to be just as good as the rest, and if they can deal with contradictory results, then so can you.

Of course, this only applies if people the people in your research environment let you know about the problems they were having. They may be competitive people who feel that talking about struggling with research is equivalent to showing weakness. If that is the case, I recommend reading some of the many excellent blogs from scientists who are not afraid to talk about their research issues.

One thing that is clear is that you cannot just assume that every result that is published is automatically set in stone. If you think you have a better theory, test it, and if necessary repeat an experiment that has already been done. If enough people do that there might actually be a chance of demasking the cheaters. And that would be another great incentive not to cheat in the first place.