FLICKR, MCKAYSAVAGEA growing body of research has highlighted scientists’ inability to reproduce one another’s results, including a 2012 study that found only 11 percent of “landmark” cancer studies investigated could be independently confirmed. This dismally low reproducibility figure is estimated to be even lower for large-scale omics studies because outside reviewers are often stymied by a lack of detailed protocols and access the resources needed to perform the analyses.
“Some communities have standards requiring raw data to be deposited at or before publication, but the computer code is generally not made available, typically due to the time it takes to prepare it for release,” explained Victoria Stodden, an assistant professor of statistics at Columbia University.
The inability to validate is particularly troubling because omics studies are understood to be error-prone. Given the sheer size of most data sets, it is not uncommon for even highly unusual events to occur by chance. On top of that, the increasingly complex computational tools used for high-throughput analyses are often subject to biases and errors.
While some journals have tried to make the research process more transparent—Nature and Science, for example, require authors to make their data available ...
