Irreproducible research

Have you ever heard that between 51% and 89% of published biomedical research studies cannot be replicated by other scientists? Assuming an average of 50% irreproducibility, a 2015 report estimated that only in the United States, around $28 billion every year is used to produce experiments and results that might not be reproducible in other labs around the world. This is a serious concern that not only impacts our trust in science or the perception that the public has about science, but also strongly affects translation of basic research into clinical data, which ultimately can impact human health.

The term irreproducibility accounts for the inability to replicate or reproduce results already published. The reasons behind this problem are numerous and it still continues a topic of debate, but one cause is the inadequate reporting and analysis of published and generated data. And this is an actual problem across almost all scientific journals, mainly due the lack of expert technical reviewers during the peer-review phase and standardized guidelines as we from MiSet are developing.

With the expansion of single cell analysis and the development of equipment able to measure many parameters (>40 and growing) in a single cell, the use of flow cytometry is becoming more and more popular. A quick search in Pubmed using the terms “flow cytometry OR cell sorting” shows that more than 15,000 papers were published only in 2019 using these techniques. Assuming that the irreproducibility ratio is around 50% and inadequate reporting accounts for 10%, almost one out of ten articles using flow cytometry are expected to not be reproducible.

Several strategies are currently being implemented to increase reproducibility of published data. In MiSet we want to contribute to this process by defining a standardized method to design, analyze, and report flow cytometric data, which will allow other scientists to understand and reproduce published data.

Be part of the change and start changing the way we publish scientific data!

Be reproducible! Be MiSet!

Irreproducibility in the news