Abstract
Background and objectiveImage 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. MethodsThe 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. ResultsPyScratch 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. ConclusionsPyScratch offers a user-friendly interface allowing researches with little or no programming skills to perform quantitative analysis of in vitro scratch assays.
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