CellTracksColab is a platform that enables compilation, analysis, and exploration of cell tracking data.

IF 9.8 1区生物学 Q1 Agricultural and Biological Sciences

PLoS Biology Pub Date : 2024-08-08 eCollection Date: 2024-08-01 DOI:10.1371/journal.pbio.3002740

Estibaliz Gómez-de-Mariscal, Hanna Grobe, Joanna W Pylvänäinen, Laura Xénard, Ricardo Henriques, Jean-Yves Tinevez, Guillaume Jacquemet

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引用次数: 0

Abstract

In life sciences, tracking objects from movies enables researchers to quantify the behavior of single particles, organelles, bacteria, cells, and even whole animals. While numerous tools now allow automated tracking from video, a significant challenge persists in compiling, analyzing, and exploring the large datasets generated by these approaches. Here, we introduce CellTracksColab, a platform tailored to simplify the exploration and analysis of cell tracking data. CellTracksColab facilitates the compiling and analysis of results across multiple fields of view, conditions, and repeats, ensuring a holistic dataset overview. CellTracksColab also harnesses the power of high-dimensional data reduction and clustering, enabling researchers to identify distinct behavioral patterns and trends without bias. Finally, CellTracksColab also includes specialized analysis modules enabling spatial analyses (clustering, proximity to specific regions of interest). We demonstrate CellTracksColab capabilities with 3 use cases, including T cells and cancer cell migration, as well as filopodia dynamics. CellTracksColab is available for the broader scientific community at https://github.com/CellMigrationLab/CellTracksColab.

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CellTracksColab 是一个可对细胞追踪数据进行编译、分析和探索的平台。

在生命科学领域，通过电影追踪物体，研究人员可以量化单个粒子、细胞器、细菌、细胞甚至整个动物的行为。虽然现在有很多工具可以自动追踪视频，但在编译、分析和探索这些方法产生的大型数据集方面仍然存在巨大挑战。在此，我们介绍 CellTracksColab，这是一个专为简化细胞追踪数据的探索和分析而定制的平台。CellTracksColab 方便了对多个视场、条件和重复的结果进行编译和分析，确保了数据集的整体概览。CellTracksColab 还能利用高维数据缩减和聚类的功能，使研究人员能够无偏差地识别独特的行为模式和趋势。最后，CellTracksColab 还包括专门的分析模块，可以进行空间分析（聚类、与特定兴趣区域的接近性）。我们用 3 个用例演示了 CellTracksColab 的功能，包括 T 细胞和癌细胞迁移以及丝状体动力学。CellTracksColab 可在 https://github.com/CellMigrationLab/CellTracksColab 网站上供广大科学界使用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

PLoS Biology BIOCHEMISTRY & MOLECULAR BIOLOGY-BIOLOGY

CiteScore

15.40

自引率

2.00%

发文量

359

审稿时长

3-8 weeks

期刊介绍： PLOS Biology is the flagship journal of the Public Library of Science (PLOS) and focuses on publishing groundbreaking and relevant research in all areas of biological science. The journal features works at various scales, ranging from molecules to ecosystems, and also encourages interdisciplinary studies. PLOS Biology publishes articles that demonstrate exceptional significance, originality, and relevance, with a high standard of scientific rigor in methodology, reporting, and conclusions. The journal aims to advance science and serve the research community by transforming research communication to align with the research process. It offers evolving article types and policies that empower authors to share the complete story behind their scientific findings with a diverse global audience of researchers, educators, policymakers, patient advocacy groups, and the general public. PLOS Biology, along with other PLOS journals, is widely indexed by major services such as Crossref, Dimensions, DOAJ, Google Scholar, PubMed, PubMed Central, Scopus, and Web of Science. Additionally, PLOS Biology is indexed by various other services including AGRICOLA, Biological Abstracts, BIOSYS Previews, CABI CAB Abstracts, CABI Global Health, CAPES, CAS, CNKI, Embase, Journal Guide, MEDLINE, and Zoological Record, ensuring that the research content is easily accessible and discoverable by a wide range of audiences.

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