Abstract
SummaryHere we present EpiGraph, an image analysis tool that quantifies epithelial organization. Our method combines computational geometry and graph theory to measure the degree of order of any packed tissue. EpiGraph goes beyond the traditional polygon distribution analysis, capturing other organizational traits that improve the characterization of epithelia. EpiGraph can objectively compare the rearrangements of epithelial cells during development and homeostasis to quantify how the global ensemble is affected. Importantly, it has been implemented in the open-access platform Fiji. This makes EpiGraph very user friendly, with no programming skills required.Availability and implementationEpiGraph is available at https://imagej.net/EpiGraph and the code is accessible (https://github.com/ComplexOrganizationOfLivingMatter/Epigraph) under GPLv3 license.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
How tissues modulate and maintain their organization during development and homeostasis is an important question that remains unsolved
EpiGraph goes beyond the traditional polygon distribution analysis, capturing other organizational traits that improve the characterization of epithelia
EpiGraph can objectively compare the rearrangements of epithelial cells during development and homeostasis to quantify how the global ensemble is affected
Summary
How tissues modulate and maintain their organization during development and homeostasis is an important question that remains unsolved. Summary: Here we present EpiGraph, an image analysis tool that quantifies epithelial organization. This is what we call a ‘CVT path’ (Supplementary Box), which was used as a scale to compare the organization of different packed tissues.
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