Interactive Visualization for Patient-to-Patient Comparison - Quang Vinh Nguyen; Guy Nelmes; Mao Lin Huang; Simeon Simoff; Daniel Catchpoole (Genomics & Informatics)
A visual analysis approach and the developed supporting technology provide a comprehensive solution for analyzing large and complex integrated genomic and biomedical data. This paper presents a methodology that is implemented as an interactive visual analysis technology for extracting knowledge from complex genetic and clinical data and then visualizing it in a meaningful and interpretable way. By synergizing the domain knowledge into development and analysis processes, we have developed a comprehensive tool that supports a seamless patient-to-patient analysis, from an overview of the patient population in the similarity space to the detailed views of genes. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, and gene comparison. We demonstrate our approach with medical scientists on a case study of childhood cancer patients on how they use the tool to confirm existing hypotheses and to discover new scientific insights.