PhD Proposal: Epiviz: Interactive Visual Analytics for Functional Genomics Data

Data visualization through genome browsers is an integral aspect of the analysis of genomic experimental results. Commonly, the data visualized in these tools is the output of analyses performed in powerful computing environments like R/Bioconductor or Python. Two essential aspects of data analysis are usually distinct and disjoint: algorithmic analysis and visualization, which in current technologies are not integrated within one tool, but rather, one precedes the other. Recent technological advances in web-based data visualization have made it possible for interactive visualization tools to tightly integrate with powerful algorithmic tools.
We introduce functional genomics data visualization methods for providing tight-knit integration with computational and statistical modeling and data analysis. These methods are implemented over Epiviz (http://epiviz.cbcb.umd.edu), a web application featuring an interactive, open-ended integration with computing environments. Combined with an interactive web-based design, this facilitates the reproducible dissemination of interactive data analyses of high-throughput functional genomics experiments, in a user-friendly platform. Given the novelty of our methods in genomics visualization, evaluation and validation of such methods is also in its early stages. We propose a series of evaluation strategies that will enhance user experience and productivity in data analysis and dissemination through visualization.
Examining Committee:
Committee Chair: - Dr. Hector Corrada Brav
Dept's Representative - Dr. Amitabh Varshney
Committee Members: - Dr. Mihai Pop
- Dr. Niklas Elmqvist