Public data repositories like the Gene Expression Omnibus have been a boon for researchers, who are using the information they store to study genetic associations to diseases without ever having to go near a microarray, says Nature News' Monya Baker. For example, in May, Stanford School of Medicine's Atul Butte identified a new drug target for diabetes by downloading data from 130 gene-expression studies in mice, rats, and humans that were done by other researchers and doing a meta-analysis to look for a common link. One of Butte's postdocs, Purvesh Khatri, tells Baker that a wet lab is no longer needed for discovery. Butte adds that wet lab experiments are more for validating hypotheses than making discoveries. "The beauty of analyzing data from multiple experiments is that biases and artifacts should cancel out between data sets, helping true relationships to stand out," Baker says. Or as Butte puts it to her, "There is safety in numbers."
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