Polarity-JaM: an image analysis toolbox for cell polarity, junction and morphology quantification
Abstract Cell polarity involves the asymmetric distribution of cellular components such as signalling molecules and organelles within a cell, alterations in cell morphology and cell-cell contacts. Advances in fluorescence microscopy and deep learning algorithms open up a wealth of unprecedented oppo...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-56643-x |
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| author | Wolfgang Giese Jan Philipp Albrecht Olya Oppenheim Emir Bora Akmeriç Julia Kraxner Deborah Schmidt Kyle Harrington Holger Gerhardt |
| author_facet | Wolfgang Giese Jan Philipp Albrecht Olya Oppenheim Emir Bora Akmeriç Julia Kraxner Deborah Schmidt Kyle Harrington Holger Gerhardt |
| author_sort | Wolfgang Giese |
| collection | DOAJ |
| description | Abstract Cell polarity involves the asymmetric distribution of cellular components such as signalling molecules and organelles within a cell, alterations in cell morphology and cell-cell contacts. Advances in fluorescence microscopy and deep learning algorithms open up a wealth of unprecedented opportunities to characterise various aspects of cell polarity, but also create new challenges for comprehensible and interpretable image data analysis workflows to fully exploit these new opportunities. Here we present Polarity-JaM, an open source package for reproducible exploratory image analysis that provides versatile methods for single cell segmentation, feature extraction and statistical analysis. We demonstrate our analysis using fluorescence image data of endothelial cells and their collective behaviour, which has been shown to be essential for vascular development and disease. The general architecture of the software allows its application to other cell types and imaging modalities, as well as seamless integration into common image analysis workflows, see https://polarityjam.readthedocs.io . We also provide a web application for circular statistics and data visualisation, available at www.polarityjam.com , and a Napari plug-in, each with a graphical user interface to facilitate exploratory analysis. We propose a holistic image analysis workflow that is accessible to the end user in bench science, enabling comprehensive analysis of image data. |
| format | Article |
| id | doaj-art-80a2b16625de4aa3bb5326f07dd9d0a6 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-80a2b16625de4aa3bb5326f07dd9d0a62025-02-09T12:44:02ZengNature PortfolioNature Communications2041-17232025-02-0116111310.1038/s41467-025-56643-xPolarity-JaM: an image analysis toolbox for cell polarity, junction and morphology quantificationWolfgang Giese0Jan Philipp Albrecht1Olya Oppenheim2Emir Bora Akmeriç3Julia Kraxner4Deborah Schmidt5Kyle Harrington6Holger Gerhardt7Max Delbrück Center for Molecular Medicine in the Helmholtz AssociationMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationMax Delbrück Center for Molecular Medicine in the Helmholtz AssociationAbstract Cell polarity involves the asymmetric distribution of cellular components such as signalling molecules and organelles within a cell, alterations in cell morphology and cell-cell contacts. Advances in fluorescence microscopy and deep learning algorithms open up a wealth of unprecedented opportunities to characterise various aspects of cell polarity, but also create new challenges for comprehensible and interpretable image data analysis workflows to fully exploit these new opportunities. Here we present Polarity-JaM, an open source package for reproducible exploratory image analysis that provides versatile methods for single cell segmentation, feature extraction and statistical analysis. We demonstrate our analysis using fluorescence image data of endothelial cells and their collective behaviour, which has been shown to be essential for vascular development and disease. The general architecture of the software allows its application to other cell types and imaging modalities, as well as seamless integration into common image analysis workflows, see https://polarityjam.readthedocs.io . We also provide a web application for circular statistics and data visualisation, available at www.polarityjam.com , and a Napari plug-in, each with a graphical user interface to facilitate exploratory analysis. We propose a holistic image analysis workflow that is accessible to the end user in bench science, enabling comprehensive analysis of image data.https://doi.org/10.1038/s41467-025-56643-x |
| spellingShingle | Wolfgang Giese Jan Philipp Albrecht Olya Oppenheim Emir Bora Akmeriç Julia Kraxner Deborah Schmidt Kyle Harrington Holger Gerhardt Polarity-JaM: an image analysis toolbox for cell polarity, junction and morphology quantification Nature Communications |
| title | Polarity-JaM: an image analysis toolbox for cell polarity, junction and morphology quantification |
| title_full | Polarity-JaM: an image analysis toolbox for cell polarity, junction and morphology quantification |
| title_fullStr | Polarity-JaM: an image analysis toolbox for cell polarity, junction and morphology quantification |
| title_full_unstemmed | Polarity-JaM: an image analysis toolbox for cell polarity, junction and morphology quantification |
| title_short | Polarity-JaM: an image analysis toolbox for cell polarity, junction and morphology quantification |
| title_sort | polarity jam an image analysis toolbox for cell polarity junction and morphology quantification |
| url | https://doi.org/10.1038/s41467-025-56643-x |
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