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ANDA: An open-source tool for automated image analysis of neuronal differentiation

BACKGROUND: Imaging of in vitro neuronal differentiation and measurements of cell morphologies has led to novel insights into neuronal development. Live-cell imaging techniques and large datasets of images has increased the demand for automated pipelines for quantitative analysis of neuronal morphol...

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Detalles Bibliográficos
Autores principales: Wæhler, Hallvard Austin, Labba, Nils-Anders, Paulsen, Ragnhild Elisabeth, Sandve, Geir Kjetil, Eskeland, Ragnhild
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168306/
https://www.ncbi.nlm.nih.gov/pubmed/37162841
http://dx.doi.org/10.1101/2023.04.27.538564
Descripción
Sumario:BACKGROUND: Imaging of in vitro neuronal differentiation and measurements of cell morphologies has led to novel insights into neuronal development. Live-cell imaging techniques and large datasets of images has increased the demand for automated pipelines for quantitative analysis of neuronal morphological metrics. RESULTS: We present ANDA, an analysis workflow for quantification of various aspects of neuronal morphology from high-throughput live-cell imaging screens. This tool automates the analysis of neuronal cell numbers, neurite lengths and neurite attachment points. We used rat, chicken and human in vitro models for neuronal differentiation and have demonstrated the accuracy, versatility, and efficiency of the tool. CONCLUSIONS: ANDA is an open-source tool that is easy to use and capable of automated processing from time-course measurements of neuronal cells. The strength of this pipeline is the capability to analyse high-throughput imaging screens.