linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser
Fig 2
Configurable filters allow deep data exploration.
The user can choose from a range of several visualisation methods directly in the browser interface to highlight aspects of interest in the data (zebrafish tracking results from [2] as an example). (a) The line data is visualised using a range of options for shading and colour mapping. (b-c) From the full dataset (top), the user can filter parts of the data concerning specific attributes, such as time intervals (bottom) or (c) a specific range of signals (marker expression in cells in this case). (d) The user can further create subselections of the tracks in space using cutting planes or refinable spatial selections. The visual attributes can be defined separately for the selected focus region and the non-selected context region. (e-g) The web interface can blend seamlessly between different states of the data. This feature can be used to map between (e) original tracks and their edge-bundled version, to visualise planar projections of the 3D data (f) locally on a definable (oblique) plane or (g) globally using a Mercator projection (with definable parameters).