Tag: replicability


Replication and validation in -omics studies - just as important as reproducibility

The psychology/social psychology community has made replication a huge focus over the last year. One reason is the recent, public blow-up over a famous study that did not replicate. There are also concerns about the experimental and conceptual design of these studies that go beyond simple lack of replication. In genomics, a similar scandal occurred due to what amounted to “data fudging”. Although, in the genomics case, much of the blame and focus has been on lack of reproducibility or data availability

I think one of the reasons that the field of genomics has focused more on reproducibility is that replication is already more consistently performed in genomics. There are two forms for this replication: validation and independent replication. Validation generally refers to a replication experiment performed by the same research lab or group - with a different technology or a different data set. On the other hand, independent replication of results is usually performed by an outside laboratory. 

Validation is by far the more common form of replication in genomics. In this article in Science, Ioannidis and Khoury point out that validation has different meaning depending on the subfield of genomics. In GWAS studies, it is now expected that every significant result will be validated in a second large cohort with genome-wide significance for the identified variants.

In gene expression/protein expression/systems biology analyses, there has been no similar definition of the “criteria for validation”. Generally the experiments are performed and if a few/a majority/most of the results are confirmed, the approach is considered validated. My colleagues and I just published a paper where we define a new statistical sampling approach for validating lists of features in genomics studies that is somewhat less ambiguous. But I think this is only a starting point. Just like in psychology, we need to focus not just on reproducibility, but also replicability of our results, and we need new statistical approaches for evaluating whether validation/replication have actually occurred. 


Replication, psychology, and big science

Reproducibility has been a hot topic for the last several years among computational scientists. A study is reproducible if there is a specific set of computational functions/analyses (usually specified in terms of code) that exactly reproduce all of the numbers in a published paper from raw data. It is now recognized that a critical component of the scientific process is that data analyses can be reproduced. This point has been driven home particularly for personalized medicine applications, where irreproducible results can lead to delays in evaluating new procedures that affect patients’ health. 

But just because a study is reproducible does not mean that it is replicable. Replicability is stronger than reproducibility. A study is only replicable if you perform the exact same experiment (at least) twice, collect data in the same way both times, perform the same data analysis, and arrive at the same conclusions. The difference with reproducibility is that to achieve replicability, you have to perform the experiment and collect the data again. This of course introduces all sorts of new potential sources of error in your experiment (new scientists, new materials, new lab, new thinking, different settings on the machines, etc.)

Replicability is getting a lot of attention recently in psychology due to some high-profile studies that did not replicate. First, there was the highly-cited experiment that failed to replicate, leading to a show down between the author of the original experiment and the replicators. Now there is a psychology project that allows researchers to post the results of replications of experiments - whether they succeeded or failed. Finally, the Reproducibility Project, probably better termed the Replicability Project, seeks to replicate the results of every experiment in the journals Psychological Science, the Journal of Personality and Social Psychology,or the Journal of Experimental Psychology: Learning, Memory, and Cognition in the year 2008.

Replicability raises important issues for “big science” projects, ranging from genomics (The Thousand Genomes Project) to physics (The Large Hadron Collider). These experiments are too big and costly to actually replicate. So how do we know the results of these experiments aren’t just errors, that upon replication (if we could do it) would not show up again? Maybe smaller scale replications of sub-projects could be used to help convince us of discoveries in these big projects?

In the meantime, I love the idea that replication is getting the credit it deserves (at least in psychology). The incentives in science often only credit the first person to an idea, not the long tail of folks who replicate the results. For example, replications of experiments are often not considered interesting enough to publish. Maybe these new projects will start to change some of the perverse academic incentives.