The study of cellular and developmental processes in physiologically relevant three-dimensional (3D) systems facilitates an understanding of mechanisms underlying cell fate, disease and injury. While cutting-edge microscopy technologies permit the routine acquisition of 3D datasets, there is currently a limited number of open-source software packages to analyse such images. Here we describe GIANI (General Image Analysis of Nuclei-based Images; https://djpbarry.github.io/Giani), new software for the analysis of 3D images. The design primarily facilitates segmentation of nuclei and cells, followed by quantification of morphology and protein expression. GIANI enables routine and reproducible batch-processing of large numbers of images and comes with scripting and command line tools. We demonstrate the utility of GIANI by quantifying cell morphology and protein expression in confocal images of mouse early embryos and by segmenting nuclei from light sheet microscopy images of the flour beetle embryo. We also validate the performance of the software using simulated data. More generally, we anticipate that GIANI will be a useful tool for researchers in a variety of biomedical fields.
GIANI: open-source software for automated analysis of 3D microscopy images
- Award Group:
- Funder(s): Cancer Research UK
- Award Id(s): FC001120
- Funder(s):
- Award Group:
- Funder(s): UK Medical Research Council
- Award Id(s): FC001120
- Funder(s):
- Award Group:
- Funder(s): Wellcome Trust
- Award Id(s): FC001120
- Funder(s):
Currently Viewing Accepted Manuscript - Newer Version Available
David J. Barry, Claudia Gerri, Donald M. Bell, Rocco D'Antuono, Kathy K. Niakan; GIANI: open-source software for automated analysis of 3D microscopy images. J Cell Sci 2022; jcs.259511. doi: https://doi.org/10.1242/jcs.259511
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