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linus: Conveniently explore, share, and present large-scale biological trajectory data from a web browser

Johannes Waschke, Mario Hlawitschka, Kerim Anlas, View ORCID ProfileVikas Trivedi, Ingo Roeder, Jan Huisken, View ORCID ProfileNico Scherf
doi: https://doi.org/10.1101/2020.04.17.043323
Johannes Waschke
1Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, 04103 Leipzig, Germany
2Faculty of Computer Science and Media, Leipzig University of Applied Sciences, 04277 Leipzig, Germany
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Mario Hlawitschka
2Faculty of Computer Science and Media, Leipzig University of Applied Sciences, 04277 Leipzig, Germany
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Kerim Anlas
3EMBL Barcelona, C/ Dr. Aiguader 88, 08003 Barcelona, Spain
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Vikas Trivedi
3EMBL Barcelona, C/ Dr. Aiguader 88, 08003 Barcelona, Spain
4EMBL Heidelberg, Developmental Biology Unit, 69117 Heidelberg, Germany
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  • ORCID record for Vikas Trivedi
Ingo Roeder
5National Center of Tumor Diseases (NCT), Partner Site Dresden, 01307 Dresden, Germany
6Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, School of Medicine, TU Dresden, 01307 Dresden, Germany
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Jan Huisken
7Morgridge Institute for Research, Madison, Wisconsin 53715, USA
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Nico Scherf
1Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, 04103 Leipzig, Germany
6Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, School of Medicine, TU Dresden, 01307 Dresden, Germany
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  • ORCID record for Nico Scherf
  • For correspondence: nscherf@cbs.mpg.de
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Abstract

In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data is often a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise package 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 and enriches them with additional features, such as edge bundling or custom axes and generates an interactive web-based visualisation that can be shared offline and online. The goal of linus is to facilitate the collaborative discovery of patterns in complex trajectory data.

Competing Interest Statement

The authors have declared no competing interest.

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  • This is an extended version

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 08, 2021.
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linus: Conveniently explore, share, and present large-scale biological trajectory data from a web browser
Johannes Waschke, Mario Hlawitschka, Kerim Anlas, Vikas Trivedi, Ingo Roeder, Jan Huisken, Nico Scherf
bioRxiv 2020.04.17.043323; doi: https://doi.org/10.1101/2020.04.17.043323
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linus: Conveniently explore, share, and present large-scale biological trajectory data from a web browser
Johannes Waschke, Mario Hlawitschka, Kerim Anlas, Vikas Trivedi, Ingo Roeder, Jan Huisken, Nico Scherf
bioRxiv 2020.04.17.043323; doi: https://doi.org/10.1101/2020.04.17.043323

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