Background and objective: Image acquisition has greatly benefited from the automation of microscopes and has been followed by an increasing amount and complexity of data acquired. Here, we present the PyScratch, a new tool for processing spatial and temporal information from scratch assays. PyScratch is an open-source software implemented in Python that analyses the migration area in an automated fashion.
Methods: The software was developed in Python. Wound healing assays were used to validate its performance. The images were acquired using Cytation 5™ during 60 h. Data were analyzed using One-Way ANOVA.
Results: PyScratch performed a robust analysis of confluent cells, showing that high plating density affects cell migration. Additionally, PyScratch was approximately six times faster than a semi-automated analysis.
Conclusions: PyScratch offers a user-friendly interface allowing researches with little or no programming skills to perform quantitative analysis of in vitro scratch assays.
Keywords: Migration assay; Python; Scratch assay; Wound healing assay.
Copyright © 2020 Elsevier B.V. All rights reserved.