Web-based tools, called 'Galaxy,' simplify genomic analysis

Research News

With tremendous advances in DNA sequencing and the advent of microarray technology in the 1990s, biology embarked on a new age of discovery. Researchers suddenly had access to unprecedented amounts of data -- and faced unprecedented complexity in its analysis.

Necessity sparked the rise of a whole new field: the hybrid of biology and computer science now known as bioinformatics. But as sequencing technologies continue to evolve more and more rapidly, the challenge has grown more and more acute.
"Biology is in a state of shock,” says Anton Nekrutenko, assistant professor of biochemistry and molecular biology at Penn State. "What we have is biochemistry and biology labs that are generating mountains of data, and then they say, ‘What do we do now?‘"

"Computational biologists write the programs they need to solve their own problems,” Nekrutenko said, "but they are generally not interested in providing interfaces for experimental biologists.”

That’s where Galaxy comes in. Developed by Nekrutenko and others at Penn State, along with James Taylor at Emory University, Galaxy is a Web-based framework that pulls together a variety of tools that allow for easy retrieval and analysis of large amounts of data, simplifying the process of genomic analysis. As described in one of the team’s early papers, Galaxy "combines the power of existing genome annotation databases with a simple Web portal to enable users to search remote resources, combine data from independent queries, and visualize the results.”

"Essentially we are providing a unified interface to many different tools,” Nekrutenko explains. As a trade review puts it, Galaxy "amplifies the strengths of existing resources.”

The response has been gratifying, to say the least. "Since last year the project has really taken on legs,” Nekrutenko said. The Galaxy website at Penn State now has 10,000 registered users, and many more who are not registered. It runs 4-5,000 analyses daily. "It’s also available as software, so that people can download it and to run it anywhere, on their own hardware. We encourage this, in fact, because there’s a limit to how much data our computers can handle.

"Our goal is proliferation,” Nekrutenko said, "and right now we don’t have much competition. We are really the only genomic solution. We allow biologists to do various very complicated analyses quite easily. And we have all sorts of cool features,” including an automated workflow management tool and a host of short video tutorials. "There’s even an iPhone app so you can check your analysis as it’s running,” he said.