Related Experiment Video
Updated: Jun 21, 2025
Monitoring Stub1-Mediated Pexophagy
Published on: May 12, 2023
Automated, image-based quantification of peroxisome characteristics with perox-per-cell
Maxwell L Neal1, Nandini Shukla2, Fred D Mast1
1Seattle Children's Research Institute, Center for Global Infectious Disease Research, Seattle, WA USA.
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.
