iStockphoto/AlanPhilipsKevin Davies writes in Bio-IT World about an open-source platform for computational analysis:
Enter the term “galaxy” in a Web search engine, Penn State’s Anton Nekrutenko muses, and the top hits are likely to be an astrophysical entity or “a very bad soccer team.” But making fast strides up the web charts is the Galaxy open-source tool, which is coming into its own as more and more researchers seek ways to easily handle and manipulate next-gen sequencing (NGS) and other large datasets.
“Galaxy allows you to do analyses you cannot do anywhere else, without the need to install or download anything,” says Nekrutenko. “We can make genomics better, easier and more efficient. You can analyze multiple sequence alignments, compare genomic annotations, profile metagenomic samples and much, much more.” Galaxy was originally developed by Nekrutenko, who is based in the Center for Comparative Genomics and Bioinformatics at Penn State, and his former Penn State colleague James Taylor, who is now an assistant professor in biology and math and computer science at Emory University. Both are quick to cite the many contributions to Galaxy’s evolution from the genomics community.
Taylor was finishing his Ph.D. when the pair started to develop Galaxy, and they have devoted much of their time to that effort ever since. Nekrutenko is the more biologically inclined of the pair. “I can script a bit,” he says, “but Galaxy could only be developed with proper software engineering practices, which was only possible after James got involved.”
Galaxy is primarily a platform for making computational tools accessible. Nekrutenko and Taylor observed “a huge disconnect” between computer science development tools and algorithms on the one hand, and the researchers wanting to use them on the other. Galaxy is designed to fill that gap. …
Most of the Galaxy tools are in the genomics and gene evolution space, but researchers are also adapting the platform to proteomics and other areas. “When this started, NGS didn’t exist,” says Nekrutenko. “Initially, we were addressing problems with whole genome sequence, comparative genomics, etc. In reality, very few people can use this information. We’re still the only resource to meaningfully manipulate genome alignments on a large scale.”
The basic model is a Web-based platform. “We believe that’s really important for collaboration and communication,” says Taylor. “Having no barrier to using Galaxy other than a Web browser is very important.”
Read the whole article at Bio-ITWorld.com.
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