Successful biomarker discovery projects require screening large volumes of data to distinguish clinically relevant information from normal biologic diversity. More than simply data acquisition software, ProteinChip data manager software tracks samples and manages the complex data inherent to biomarker discovery. Software analysis features provide powerful, advanced data mining and analysis capabilities for rapid, automated analysis of multiple experiments over many conditions to identify potential biomarkers. The server editions (Personal and Enterprise Editions) of the software are included as part of the respective ProteinChip SELDI systems.
The stand-alone ProteinChip data manager software, Desktop Edition provides users with all the analysis features of the server versions, and allows them to perform data analysis while separated from the instrument computer. Customers can upgrade their existing version 3.x servers by purchasing the upgrade 3.x to 4 package.
Informatics Support for the Protein Profiling Workflow
ProteinChip data manager software improves the efficiency of the ProteinChip SELDI system workflow, providing scalability from small data sets to very large experiments and enabling processing and analysis of thousands of spectra. Built-in query tools allow rapid searching of the centralized database, and the intuitive graphical user interface and folder structure facilitate data management.
Automated Sample Tracking
The Virtual Notebook feature provides an intuitive graphical user interface for fast, easy input of sample information. This electronic laboratory notebook provides the ability to enter information about sample processing conditions and to apply these properties virtually to spots on the arrays. This can be done before running arrays through wet-lab processes and can serve as a map to guide laboratory work, saving hours of manual postacquisition annotation.
Integrated Data Mining and Analysis
The software's data mining capabilities enable rapid analysis and comparison of thousands of spectra across many conditions in a single run. Analysis features include proprietary algorithms for the identification of significant changes in protein expression levels and possible biomarkers. Statistical information is then displayed in a multitude of graphical visualizations and tables. Powerful statistical tools include principal component analysis (PCA), receiver operating characteristic (ROC) plots, and hierarchical clustering with a heat map view.
Security and Traceability
ProteinChip data manager software's security implementation allows multiple groups of users to use a centralized database while working independently. The built-in audit trail feature maintains a record of changes made to the data.