Division of Cancer Biology, The Institute of Cancer Research, London SW3 6JB, UK.
Department of Computational Systems Medicine, Imperial College, South Kensington Campus, London SW7 2AZ, UK.
Bioinformatics. 2017 Oct 15;33(20):3320-3322. doi: 10.1093/bioinformatics/btx404.
Live imaging studies give unparalleled insight into dynamic single cell behaviours and fate decisions. However, the challenge of reliably tracking single cells over long periods of time limits both the throughput and ease with which such studies can be performed. Here, we present NucliTrack, a cross platform solution for automatically segmenting, tracking and extracting features from fluorescently labelled nuclei. NucliTrack performs similarly to other state-of-the-art cell tracking algorithms, but NucliTrack's interactive, graphical interface makes it significantly more user friendly.
NucliTrack is available as a free, cross platform application and open source Python package. Installation details and documentation are at: http://nuclitrack.readthedocs.io/en/latest/ A video guide can be viewed online: https://www.youtube.com/watch?v=J6e0D9F-qSU Source code is available through Github: https://github.com/samocooper/nuclitrack. A Matlab toolbox is also available at: https://uk.mathworks.com/matlabcentral/fileexchange/61479-samocooper-nuclitrack-matlab.
Supplementary data are available at Bioinformatics online.
实时成像研究为动态单细胞行为和命运决策提供了无与伦比的深入了解。然而,可靠地跟踪单细胞很长一段时间的挑战限制了这些研究的通量和易用性。在这里,我们提出了 NucliTrack,这是一个用于自动分割、跟踪和提取荧光标记核的跨平台解决方案。NucliTrack 的性能与其他最先进的细胞跟踪算法相似,但 NucliTrack 的交互式图形界面使其更具用户友好性。
NucliTrack 是一个免费的跨平台应用程序和开源 Python 包。安装详细信息和文档可在以下网址获得:http://nuclitrack.readthedocs.io/en/latest/。在线观看视频指南:https://www.youtube.com/watch?v=J6e0D9F-qSU。源代码可通过 Github 获得:https://github.com/samocooper/nuclitrack。Matlab 工具箱也可在以下网址获得:https://uk.mathworks.com/matlabcentral/fileexchange/61479-samocooper-nuclitrack-matlab。
补充数据可在生物信息学在线获得。