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[Preprint]. 2024 Apr 12:2024.04.08.588597. [Version 1] doi: 10.1101/2024.04.08.588597

Automated, image-based quantification of peroxisome characteristics with perox-per-cell

Maxwell L Neal, Nandini Shukla, Fred D Mast, Jean-Claude Farré, Therese M Pacio, Katelyn E Raney-Plourde, Sumedh Prasad, Suresh Subramani, John D Aitchison
PMCID: PMC11030360  PMID: 38645222

ABSTRACT

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. The software is available at https://github.com/AitchisonLab/perox-per-cell

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