Scalable, Dynamic Analysis and Visualization for Genomic Datasets

A challenge in data analysis and visualization is to build new-generation software tools and systems to truly accelerate scientific discoveries. The recent focus of Princeton’s next-generation software project is to investigate how to develop new-generation data analysis and visualization capabilities for genomic scientists to analyze high-throughput genomic datasets. This paper describes the software tools we have recently developed to enable dynamic, large-scale data analysis and visualization of multiple datasets on large-scale, highresolution display wall systems. Our initial experience with the deployed tools at Princeton’s Lewis-Sigler Institute for Integrative Genomics is very encouraging. Scientists can effectively learn new knowledge from multiple datasets, find new insights, and generate new hypotheses that are not possible with current methods.

• Type: Conference
• Year: 2007
• Where: IPPS
• Authors: Grant Wallace, Matthew A. Hibbs, Maitreya J. Dunham, Rachel S. G. Sealfon, Olga G. Troyanskaya, Kai Li
• Keywords: Data Analysis, Distributed And Parallel Computing, IPPS 2007, Large-scale Data Analysis, Multiple Datasets