Writing in the Washington Post this week, David Shaywitz highlights some of the unintended consequences of the newer mass-scale approaches to studying genes:
A pioneer of this era, MIT geneticist Eric Lander, speaks eloquently of the “global view of biology,” meaning that scientists now have extraordinary tools to study not only individual genes, but also multiple genes at the same time. Rather than immediately investing all their resources in a few favorite genes (the traditional approach), modern researchers first can survey thousands of initial candidates, then identify and ultimately direct their attention to the most important players and pivotal networks.
But we are increasingly discovering that this global perspective comes at an unexpectedly steep price: We’re making a lot more mistakes. Or, at least, we seem to be having a lot of trouble picking out the rare, meaningful signal from the deafening noise in the background.
Typically, scientists accept a result as significant if there is a 95 percent chance it is real rather than random. But the catch is that as you start to make a large number of comparisons by examining thousands of genes, the possibility of a result appearing by chance becomes progressively more likely, to the point where such false positive results are all but guaranteed.
The consequence has been a boon for scientists — most experiments yield enticing (read: publishable) results — but a bane (of sorts) for science.
Scientific journals are littered with studies reporting “disease genes” or “molecular signatures” that are likely red herrings. To make matters worse, these results are typically packaged together as a tidy narrative, a post-hoc rationalization explaining how the newly identified genes fit perfectly into the biological process under investigation.
Shaywitz is quick to point out that despite the increased level of noise in the system, “more is more.” We just to have to adjust our filters accordingly.
-Greg Dahlmann