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Jul 21, 2014

What’s ‘hot’ in research? Genetics

What’s the hottest area of scientific research today? Thomson Reuters Science Watch says it’s genetics.

In an article titled “The Softer Side of Genomics,” Drug Discovery & Development magazine describes how today’s data management and computational tools let researchers dig deeper into genes. The article describes JMP Genomics, emphasizing its statistical power, flexibility, expanding genomics capabilities and predictive modeling. Shannon Conners, a product manager for JMP life sciences, discusses how drug discovery and development researchers might use genomics software, and then maps those needs to the latest JMP Genomics enhancements:

The increasing complexity of genomics research also demands new ways to analyze the results. “Many studies are now conducted at the whole-genome scale," says Mindy Zhang of Genzyme, "so it becomes essential that software includes a comprehensive stats tool.”

To get that statistical power, Zhang and her colleagues use JMP Genomics from SAS (Cary, N.C.). According to Shannon Conners, a product manager for JMP life sciences, the latest JMP Genomics 5 needs to handle a range of users. "There are biologists at a bench who need genomic analysis and software to make sense of their data," she says. "There are biostatisticians who want to do even more detailed analysis." That breadth of applications creates a challenge.

As Conners explains it: "You need workflows that are simplified for nonexperts but provide enough flexibility and openness of code to satisfy biostatisticians." To help bridge that divide, SAS built JMP Genomics with an open architecture. When a biostatistician wants to look "under the hood," it's possible. For a nonexpert who just wants to "run the engine," that's possible too.

The new release of JMP Genomics includes new tools for linkage maps and other enhancements. You can read more on the JMP website or in Shannon’s recent blog posts.

1 Comment
Community Member

Doug wrote:

Next generation sequencing certainly has increased the need for more capability to process data. It would be interesting to see how third generation sequencing affects software demands.