Assessing 2D visual encoding of 3D spatial connectivity - Baldi, Benedetta F.; Vuong, Jenny; O’Donoghue, Seán I. (Frontiers in Bioinformatics, 2024)
When visualizing complex data, the layout method chosen can greatly affect the ability to identify outliers, spot incorrect modeling assumptions, or recognize unexpected patterns. Additionally, visual layout can play a crucial role in communicating results to peers. In this paper, we compared the effectiveness of three visual layouts -the adjacency matrix, a half-matrix layout, and a circular layout -for visualizing spatial connectivity data, e.g., contacts derived from chromatin conformation capture experiments. To assess these visual layouts, we conducted a study comprising 150 participants from Amazon's Mechanical Turk, as well as a second expert study comprising 30 biomedical research scientists. The Mechanical Turk study found that the circular layout was the most accurate and intuitive, while the expert study found that the circular and half-matrix layouts were more accurate than the matrix layout. We concluded that the circular layout may be a good default choice for visualizing smaller datasets with relatively few spatial contacts, while, for larger datasets, the half-matrix layout may be a better choice. Our results also demonstrated how crowdsourcing methods could be used to determine which visual layouts are best for addressing specific data challenges in bioinformatics.