INSPIRE: An integrated web based informatics infrastructure for automated analysis of laboratory and clinical data
Philip Roy Quinlan, Chris Reed, Lee Baker, Alastair Thompson
University of Dundee, Dundee, UK
Background
Multiple analyses of biochemical, molecular and immunohistological markers on tissue samples generate large and complex data sets to compare with clinical and pathological parameters. Automated data analysis could identify novel associations between parameters in a web accessible user-friendly interface.
Method
A database solution has been developed to build on the existing tissue tracking systems. The datasets have been extended to allow the storage of laboratory-driven data and integrated web services to interrogate an Aperio digital pathology database. The system pools the data from the various sources and then commences Fisher’s exact, Kaplan-Meier, log rank and Wilcoxon tests on all parameters. To highlight significant results the system relies on a traffic light system to represent the results. At the extremes, bright green shows results with p values less than 0.01 and red for greater than 0.1. For example, the horizontal axis will show the various scores of an antibody and the vertical axis all of the other clinical and pathological parameters. Bright green colours anywhere within this table will signify a strong correlation between the antibody score and one of the other parameters. Further staining results can be overlaid to find common significance between antibodies.
Conclusion
Inspire allows for the quick identification of significant results amongst the noise created from the sheer volume of tests. This results in a more streamlined research process, which makes large cohort, multi-variant projects easier to manage in a secure, user friendly, web-based data management system.
