Posts about replication study

Evaluating Reproducibility in Computational Biology Research

For my Honors Senior Project, I read five research papers in the field of computational biology and attempted to reproduce the results. However, for the most part, this proved a challenge, as many details vital to utilizing relevant software and data had been excluded. Using Geir Kjetil Sandve's paper "Ten Simple Rules for Reproducible Computational Research" as a guide, I discuss how authors of these five papers did and did not obey these rules of reproducibility and how this affected my ability to reproduce their results.

Cancer studies pass reproducibility test

A high-profile project aiming to test reproducibility in cancer biology has released a second batch of results, and this time the news is good: Most of the experiments from two key cancer papers could be repeated. The latest replication studies, which appear today in eLife, come on top of five published in January that delivered a mixed message about whether high-impact cancer research can be reproduced. Taken together, however, results from the completed studies are “encouraging,” says Sean Morrison of the University of Texas Southwestern Medical Center in Dallas, an eLife editor. Overall, he adds, independent labs have now “reproduced substantial aspects” of the original experiments in four of five replication efforts that have produced clear results.

Need to find a replication partner, or collaborator? There’s an online platform for that

Do researchers need a new "Craigslist?" We were recently alerted to a new online platform called StudySwap by one of its creators, who said it was partially inspired by one of our posts. The platform creates an "online marketplace" that previous researchers have called for, connecting scientists with willing partners – such as a team looking for someone to replicate its results, and vice versa. As co-creators Christopher Chartier at Ashland University and Randy McCarthy at Northern Illinois University tell us, having a place where researchers can find each other more efficiently "is in everyone’s best interest."