Summary: perox-per-cell automates cumbersome, image-based data collection tasks often encountered in peroxisome research. The software processes microscopy images to quantify peroxisome features in yeast cells. It uses off-the-shelf image processing tools to automatically segment cells and peroxisomes and then outputs quantitative metrics including peroxisome counts per cell and spatial areas. In validation tests, we found that perox-per-cell output agrees well with manually quantified peroxisomal counts and cell instances, thereby enabling high-throughput quantification of peroxisomal characteristics.
Availability and implementation: The software is coded in Python. Compiled executables and source code are available at https://github.com/AitchisonLab/perox-per-cell.
Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author(s) 2024. Published by Oxford University Press.