PyScratch: an ease of use tool for analysis of Scratch assays

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.