OrgDyn: feature- and model-based characterization of spatial and temporal organoid dynamics

Author:

Hasnain Zaki1,Fraser Andrew K2,Georgess Dan2,Choi Alex2,Macklin Paul3,Bader Joel S4,Peyton Shelly R5,Ewald Andrew J24,Newton Paul K16

Affiliation:

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

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.

Funder

Breast Cancer Research Foundation

Jayne Koskinas & Ted Giovanis Foundation

JKTG

Jayne Koskinas Ted Giovanis

Foundation for Health and Policy and the Breast Cancer Research Foundation

Postdoctoral Fellowship

Susan G. Komen Foundation

National Institutes of Health

National Cancer Institute

NIH

National Institute of General Medical Sciences

NIGMS

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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