Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
Summary
Visual analytics (VA) is a new approach of analyzing data interactively. In this video, we discuss the data overload problem brought on by high-throughput biological experiments, and propose VA as a solution to such problem. The video demonstrates analysis within and between immunological datasets using a VA tool called Tableau.
Abstract
Visual analytics (VA) has emerged as a new way to analyze large dataset through interactive visual display. We demonstrated the utility and the flexibility of a VA approach in the analysis of biological datasets. Examples of these datasets in immunology include flow cytometry, Luminex data, and genotyping (e.g., single nucleotide polymorphism) data. Contrary to the traditional information visualization approach, VA restores the analysis power in the hands of analyst by allowing the analyst to engage in real-time data exploration process. We selected the VA software called Tableau after evaluating several VA tools. Two types of analysis tasks analysis within and between datasets were demonstrated in the video presentation using an approach called paired analysis. Paired analysis, as defined in VA, is an analysis approach in which a VA tool expert works side-by-side with a domain expert during the analysis. The domain expert is the one who understands the significance of the data, and asks the questions that the collected data might address. The tool expert then creates visualizations to help find patterns in the data that might answer these questions. The short lag-time between the hypothesis generation and the rapid visual display of the data is the main advantage of a VA approach.
Protocol
Discussion
The advent of high-throughput technology in modern biomedical research led to an explosion of research data that requires a more efficient way of analysis. Visual analytics (VA) is the science of analytical reasoning facilitated by interactive visual interfaces (1). The VA approach restores the analytical power in the hands of human analyst, contrary to the traditional approach to detect patterns by computer. Visual analytics has been applied to research in various fields, such as defense research (1) and hurricane tren…
Declarações
The authors have nothing to disclose.
Acknowledgements
We would like to thank the members of Vancouver Institute of Visual Analytics (VIVA) for offering comments and advice for the project. In particular, we would like to thank John Dill, Brian Fisher, and David Darvill. We would also like to thank the members of the Kollmann lab for their support and helpful discussions. This work was supported in part by National Institute of Allergy and Infectious Diseases, National Institute of Health Grant N01 AI50023; AllerGen NCE Grants 07-A1A and 07-B2B; and the Michael Smith Foundation for Health Research. T.R.K. is supported in part by a Career Award in the Biomedical Science from the Burroughs Wellcome Fund ad by a Canadian Institutes for Health Research Training Grant in Canadian Child Health Clinician Scientist Program, in partnership with Sick-Kids Foundation, Child and Family Research Institute (British Columbia), Women and Children’s Health Research Institute (Alberta), and Manitoba Institute of Child Health.
Referências
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