Zaki Hasnain1, Andrew K Fraser2, Dan Georgess2, Alex Choi2, Paul Macklin3, Joel S Bader4, Shelly R Peyton5, Andrew J Ewald2,4, Paul K Newton1,6. 1. Department of Aerospace & Mechanical Engineering, University of Southern California, Los Angeles, CA 90089, USA. 2. Department of Cell Biology and Center for Cell Dynamics, Johns Hopkins University, Baltimore, MD 21218, USA. 3. Intelligent Systems Engineering, Indiana University, Bloomington, IN 47408, USA. 4. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA. 5. Department of Chemical Engineering, University of Massachusetts Amherst, Amherst, MA 01003, USA. 6. Department of Mathematics, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA.
Abstract
SUMMARY: Organoid model systems recapitulate key features of mammalian tissues and enable high throughput experiments. However, the impact of these experiments may be limited by manual, non-standardized, static or qualitative phenotypic analysis. OrgDyn is an open-source and modular pipeline to quantify organoid shape dynamics using a combination of feature- and model-based approaches on time series of 2D organoid contour images. Our pipeline consists of (i) geometrical and signal processing feature extraction, (ii) dimensionality reduction to differentiate dynamical paths, (iii) time series clustering to identify coherent groups of organoids and (iv) dynamical modeling using point distribution models to explain temporal shape variation. OrgDyn can characterize, cluster and model differences among unique dynamical paths that define diverse final shapes, thus enabling quantitative analysis of the molecular basis of tissue development and disease. AVAILABILITY AND IMPLEMENTATION: https://github.com/zakih/organoidDynamics (BSD 3-Clause License). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
SUMMARY: Organoid model systems recapitulate key features of mammalian tissues and enable high throughput experiments. However, the impact of these experiments may be limited by manual, non-standardized, static or qualitative phenotypic analysis. OrgDyn is an open-source and modular pipeline to quantify organoid shape dynamics using a combination of feature- and model-based approaches on time series of 2D organoid contour images. Our pipeline consists of (i) geometrical and signal processing feature extraction, (ii) dimensionality reduction to differentiate dynamical paths, (iii) time series clustering to identify coherent groups of organoids and (iv) dynamical modeling using point distribution models to explain temporal shape variation. OrgDyn can characterize, cluster and model differences among unique dynamical paths that define diverse final shapes, thus enabling quantitative analysis of the molecular basis of tissue development and disease. AVAILABILITY AND IMPLEMENTATION: https://github.com/zakih/organoidDynamics (BSD 3-Clause License). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Maria F Gencoglu; Lauren E Barney; Christopher L Hall; Elizabeth A Brooks; Alyssa D Schwartz; Daniel C Corbett; Kelly R Stevens; Shelly R Peyton Journal: ACS Biomater Sci Eng Date: 2017-03-13
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