Automated, image-based quantification of peroxisome characteristics with 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 quan...

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Bibliographic Details
Published inbioRxiv
Main Authors Neal, Maxwell L, Shukla, Nandini, Mast, Fred D, Farré, Jean-Claude, Pacio, Therese M, Raney-Plourde, Katelyn E, Prasad, Sumedh, Subramani, Suresh, Aitchison, John D
Format Journal Article
LanguageEnglish
Published United States 12.04.2024
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Summary: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 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.
ISSN:2692-8205