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JMP® Genomics 3.0 Features Whole-Genome SNP Analysis, Predictive Modeling
Product News

JMP® Genomics 3.0 Features Whole-Genome SNP Analysis, Predictive Modeling

JMP® Genomics 3.0 Features Whole-Genome SNP Analysis, Predictive Modeling
Product News

JMP® Genomics 3.0 Features Whole-Genome SNP Analysis, Predictive Modeling


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JMP Genomics 3.0 from SAS sets itself apart with capabilities for predictive modeling and whole-genome SNP analysis. This software version, which begins shipping to customers, also features 3-D graphics and the ability to distill vital research findings from huge volumes of data. Its release was announced by SAS.

This desktop software dynamically links powerful statistical analysis with advanced graphics to provide a complete and comprehensive picture of research results.

Biologists, chemists and biostatisticians in research organizations around the world use JMP Genomics to uncover meaningful patterns in whole-genome SNP (single nucleotide polymorphism), expression microarray and proteomics data.

Since its launch in March 2006, more than 200 users across pharmaceutical, academic, governmental, nonprofit and biotechnology organizations have adopted JMP Genomics.

Richard P. Beyer, PhD, a Research Scientist in the University of Washington’s School of Public Health, first saw JMP Genomics in action at a conference he attended with Russ Wolfinger, PhD, Director of Scientific Discovery and Genomics for SAS. “I said, ‘Yeah, we’ve got to have that; it’s really cool,’” Beyer recalled. “I’m really happy with it and will continue to use it.”

Beyer was a beta tester for JMP Genomics 3.0. “One of the great things about JMP Genomics and SAS is that every time I e-mail for help I get an instant reply,” Beyer said. “You get A-plus on customer support.” Beyer said JMP Genomics developers also respond quickly to suggestions for new features.

Collaborative development is a JMP hallmark. For this version, developers evaluated feedback from users to design new features and enhancements, and also drew on advances in the JMP platform.

“JMP Genomics 3.0 takes advantage of beautiful new 3-D JMP graphics, including the 3-D PCA [principal components analysis] plots and markers that users requested,” said Shannon Conners, JMP Genomics Product Manager.

With advanced graphics also come advanced analytics. JMP Genomics 3.0 users can perform PCA on huge SNP data sets to visually identify sample groupings. This and other enhancements support very large whole-genome association studies and new SNP-SNP and SNP-trait interaction discovery capabilities. Users of JMP Genomics 3.0 can perform whole-genome SNP analysis for at least 4,000 samples with 1 million SNPs each.

Other features in JMP Genomics 3.0 include:

• Tutorials, which guide users through the import process for all supported data types.

• Estimate Builder, which allows point-and-click creation of estimate statements for use with ANOVA and Mixed Model processes.

• Workflow Builder, which lets users link sets of commonly used analysis settings into reusable workflows.

• UCSC Genome Browser Link, which creates link tables and custom tracks to display JMP Genomics statistical results in genomic context.

Through its JMP Genomics software, SAS has developed partnerships with leaders in array platform and genomic software development, including Affymetrix, Illumina and Ingenuity Systems.

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