Open Accesslinus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser
Author(s) -
Johannes Waschke,
Mario Hlawitschka,
Kerim Anlaş,
Vikas Trivedi,
Ingo Roeder,
Jan Huisken,
Nico Scherf
Publication year - 2021
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1009503
Subject(s) - computer science , python (programming language) , visualization , data visualization , trajectory , world wide web , human–computer interaction , data science , process (computing) , information retrieval , data mining , programming language , physics , astronomy
In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data can be a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise packet that makes it straightforward to create and test hypotheses collaboratively. To address these challenges, we have developed a tool, linus , which makes the process of exploring and sharing 3D trajectories as easy as browsing a website. We provide a python script that reads trajectory data, enriches them with additional features such as edge bundling or custom axes, and generates an interactive web-based visualisation that can be shared online. linus facilitates the collaborative discovery of patterns in complex trajectory data.