Skip to Main Content
Gene mapping is a statistical method used to localize human disease genes to particular regions of the human genome. When performing such analysis, a genetic likelihood space is generated and sampled, which results in a multidimensional scalar field. Researchers are interested in exploring this likelihood space through the use of visualization. Previous efforts at visualizing this space, though, were slow and cumbersome, only showing a small portion of the space at a time, thus requiring the user to keep a mental picture of several views. We have developed a new technique that displays much more data at once by projecting the multidimensional data into several 2D plots. One plot is created for each parameter that shows the change along that parameter. A radial projection is used to create another plot that provides an overview of the high dimensional surface from the perspective of a single point. Linking and brushing between all the plots are used to determine relationships between parameters. We demonstrate our techniques on real world autism data, showing how to visually examine features of the high dimensional space.