TY - JOUR
T1 - CShaperApp: Segmenting and analyzing cellular morphologies of the developing Caenorhabditis elegans embryo
T2 - Segmenting and analyzing cellular morphologies of the developing Caenorhabditis elegans embryo
AU - Cao, Jianfeng
AU - Hu, Lihan
AU - Guan, Guoye
AU - Li, Zelin
AU - Zhao, Zhongying
AU - Tang, Chao
AU - Yan, Hong
N1 - This work is supported by the Hong Kong ITC (InnoHK Project CIMDA), China, and Hong Kong Research Grants Council (11204821), China, to H.Y.; and by the National Natural Science Foundation of China (12090053 and 32088101) to C.T.; and by the Hong Kong Research Grants Council (N_HKBU201/18, HKBU12101520, HKBU12101522, and HKBU12101323), China, and Hong Kong Innovation and Technology Commission (GHP/176/21SZ), China, to Z.Z.
Publisher Copyright:
© 2024 The Authors. Quantitative Biology published by John Wiley & Sons Australia, Ltd on behalf of Higher Education Press.
PY - 2024/9
Y1 - 2024/9
N2 - Caenorhabditis elegans has been widely used as a model organism in developmental biology due to its invariant development. In this study, we developed a desktop software CShaperApp to segment fluorescence-labeled images of cell membranes and analyze cellular morphologies interactively during C. elegans embryogenesis. Based on the previously proposed framework CShaper, CShaperApp empowers biologists to automatically and efficiently extract quantitative cellular morphological data with either an existing deep learning model or a fine-tuned one adapted to their in-house dataset. Experimental results show that it takes about 30 min to process a three-dimensional time-lapse (4D) dataset, which consists of 150 image stacks at a ∼1.5-min interval and covers C. elegans embryogenesis from the 4-cell to 350-cell stages. The robustness of CShaperApp is also validated with the datasets from different laboratories. Furthermore, modularized implementation increases the flexibility in multi-task applications and promotes its flexibility for future enhancements. As cell morphology over development has emerged as a focus of interest in developmental biology, CShaperApp is anticipated to pave the way for those studies by accelerating the high-throughput generation of systems-level quantitative data collection. The software can be freely downloaded from the website of Github (cao13jf/CShaperApp) and is executable on Windows, macOS, and Linux operating systems.
AB - Caenorhabditis elegans has been widely used as a model organism in developmental biology due to its invariant development. In this study, we developed a desktop software CShaperApp to segment fluorescence-labeled images of cell membranes and analyze cellular morphologies interactively during C. elegans embryogenesis. Based on the previously proposed framework CShaper, CShaperApp empowers biologists to automatically and efficiently extract quantitative cellular morphological data with either an existing deep learning model or a fine-tuned one adapted to their in-house dataset. Experimental results show that it takes about 30 min to process a three-dimensional time-lapse (4D) dataset, which consists of 150 image stacks at a ∼1.5-min interval and covers C. elegans embryogenesis from the 4-cell to 350-cell stages. The robustness of CShaperApp is also validated with the datasets from different laboratories. Furthermore, modularized implementation increases the flexibility in multi-task applications and promotes its flexibility for future enhancements. As cell morphology over development has emerged as a focus of interest in developmental biology, CShaperApp is anticipated to pave the way for those studies by accelerating the high-throughput generation of systems-level quantitative data collection. The software can be freely downloaded from the website of Github (cao13jf/CShaperApp) and is executable on Windows, macOS, and Linux operating systems.
KW - C. elegans embryogenesis
KW - cellular morphology
KW - cellular segmentation
KW - deep learning
KW - desktop software
UR - http://www.scopus.com/inward/record.url?scp=85193545069&partnerID=8YFLogxK
U2 - 10.1002/qub2.47
DO - 10.1002/qub2.47
M3 - Journal article
AN - SCOPUS:85193545069
SN - 2095-4689
VL - 12
SP - 329
EP - 334
JO - Quantitative Biology
JF - Quantitative Biology
IS - 3
ER -