Tasks, Techniques, and Tools for Genomic Data Visualization
This addresses the need for better visualization tools in genomics to support data-driven research, but it is incremental as it primarily organizes and reviews existing work.
The paper tackles the challenge of discovering patterns and generating hypotheses from vast genomic data by proposing taxonomies for data, visualization, and tasks, and reviewing existing tools based on these taxonomies.
Genomic data visualization is essential for interpretation and hypothesis generation as well as a valuable aid in communicating discoveries. Visual tools bridge the gap between algorithmic approaches and the cognitive skills of investigators. Addressing this need has become crucial in genomics, as biomedical research is increasingly data-driven and many studies lack well-defined hypotheses. A key challenge in data-driven research is to discover unexpected patterns and to formulate hypotheses in an unbiased manner in vast amounts of genomic and other associated data. Over the past two decades, this has driven the development of numerous data visualization techniques and tools for visualizing genomic data. Based on a comprehensive literature survey, we propose taxonomies for data, visualization, and tasks involved in genomic data visualization. Furthermore, we provide a comprehensive review of published genomic visualization tools in the context of the proposed taxonomies.