Predictive Patterns Releases GeneLinker(TM) Gold and Platinum Version 4.5

Predictive Patterns Software Inc. (PPS) today announced the release of GeneLinker(TM) Gold and Platinum 4.5, a new version of the award-winning Gene Expression and Proteomics Analysis Software.

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(PRWEB) June 1, 2004

Predictive Patterns Software Inc. (PPS) today announced the release of GeneLinker(TM) Gold and Platinum 4.5, a new version of the award-winning Gene Expression and Proteomics Analysis Software.

"The new releases address needs and workflows that are a high priority for our customers. For example, we have made it far easier to do more advanced statistical analysis by providing the Bonferroni corrected p-values and False Discovery Rate numbers that many researchers have requested. We have also added a feature that targets Pathways and Gene Networks by allowing users to Export their data to Ariadne Genomics' PathwayAssist application with a single mouse click. This will allow users to take experiments created with GeneLinker and see how these data fit into existing pathway models" said Dr. Tom Radcliffe, President of PPS.

"The new external scripting is very powerful and makes it incredibly easy to add proprietary algorithms (e.g. normalizations) to extend GeneLinker Platinum." added PPS Vice-President Mark Chatterley.

The main features in both Platinum 4.5 and Gold 4.5 that differentiate them from the previous versions are:

  • Export data and gene lists to Ariadne Genomics' PathwayAssist application. This feature allows users to easily export expression data from GeneLinker into PathwayAssist and color pathways using expression data from GeneLinker. This is particularly valuable for time series experiments as users can visually see activity in the network by walking through individual samples.
  • Filter by variable. This gives users an easy way of excluding one or more samples from further analysis within the application. It can be used to remove bad samples or restrict further analysis to a subset of the data.
  • Create variables. This allows users to easily create new variables within the application. Variables can be created from scratch or based on other variables. Variables can also be randomized, making further statistical analysis easier.
  • False discovery rate. The F-test and Kruskal-Wallis viewers now include a False Discovery Rate calculation. The FDR is the fraction of genes with p-values this small or smaller that would be expected based on chance.
  • Bonferroni corrected p-values. The F-test and Kruskal-Wallis viewers now include Bonferroni corrected p-values. They represent the number of genes in the dataset that you would expect to have p-values that small based on chance.
  • Improved data import scripts, including Quantarray merge replicates and support of Quantarray unicode files.
  • Support for multiple user repositories. On start-up users can select which repository they want to use. This feature is particularly valuable for users with multiple large projects, customers that are sharing the software between multiple users and site license holders.

The additional feature that has been added to GeneLinker(TM) Platinum 4.5 is:

  • Support for external scripting (XScripts). This gives users a way of integrating their own proprietary analysis techniques (e.g. custom normalizations) into GeneLinker. This allows users to extend the capabilities of GeneLinker even further, allowing customization for individual needs.

GeneLinker Gold is the entry level product that is well suited to researchers just entering the area of genomics or proteomics research, while GeneLinker Platinum offers powerful feature detection, committees of neural networks, committees of SVMs and committees of Bayesian classifiers that are more suitable to the intermediate or advanced researcher.

"This new release illustrates our commitment to supporting and advancing the GeneLinker products. The feature sets in either product cannot be matched by any of our competitors at their respective price points," said Radcliffe. "It also demonstrates our commitment to serving user needs--improved statistics, support for multiple repositories and better support of pathways were the most frequent user-requested features, and we have responded to those requests."


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