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

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...

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Autores principales:	Johannes Waschke, Mario Hlawitschka, Kerim Anlas, Vikas Trivedi, Ingo Roeder, Jan Huisken, Nico Scherf
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/eec9dbd763bb49459c9332f2f527001e
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id	oai:doaj.org-article:eec9dbd763bb49459c9332f2f527001e
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spelling	oai:doaj.org-article:eec9dbd763bb49459c9332f2f527001e2021-11-18T05:51:58Zlinus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser1553-734X1553-7358https://doaj.org/article/eec9dbd763bb49459c9332f2f527001e2021-11-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8584757/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358In 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. Author summary Many of the processes that we study in biology are dynamic or interconnected. We can represent most of them as trajectories, being it connections between neurons in a brain or species in an ecosystem or motion traces of animals, cells or molecules. Modern experiments allow researchers to generate such trajectory data at unprecedented scales: think the parallel tracking of thousands of cells in a developing embryo over hours or days. However, visualising large-scale trajectory data is a challenge: the typical static visualisations result in excessive overplotting and often resemble the infamous hairballs. Simplification and interactivity are crucial strategies to deal with this problem. We present the lightweight tool linus that enables researchers to explore and share their trajectory data in an engaging way in web browsers from almost any device.Johannes WaschkeMario HlawitschkaKerim AnlasVikas TrivediIngo RoederJan HuiskenNico ScherfPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Johannes Waschke Mario Hlawitschka Kerim Anlas Vikas Trivedi Ingo Roeder Jan Huisken Nico Scherf linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser
description	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. Author summary Many of the processes that we study in biology are dynamic or interconnected. We can represent most of them as trajectories, being it connections between neurons in a brain or species in an ecosystem or motion traces of animals, cells or molecules. Modern experiments allow researchers to generate such trajectory data at unprecedented scales: think the parallel tracking of thousands of cells in a developing embryo over hours or days. However, visualising large-scale trajectory data is a challenge: the typical static visualisations result in excessive overplotting and often resemble the infamous hairballs. Simplification and interactivity are crucial strategies to deal with this problem. We present the lightweight tool linus that enables researchers to explore and share their trajectory data in an engaging way in web browsers from almost any device.
format	article
author	Johannes Waschke Mario Hlawitschka Kerim Anlas Vikas Trivedi Ingo Roeder Jan Huisken Nico Scherf
author_facet	Johannes Waschke Mario Hlawitschka Kerim Anlas Vikas Trivedi Ingo Roeder Jan Huisken Nico Scherf
author_sort	Johannes Waschke
title	linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser
title_short	linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser
title_full	linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser
title_fullStr	linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser
title_full_unstemmed	linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser
title_sort	linus: conveniently explore, share, and present large-scale biological trajectory data in a web browser
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/eec9dbd763bb49459c9332f2f527001e
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linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser

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