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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Published in | bioRxiv |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
12.04.2024
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Online Access | Get full text |
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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. |
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ISSN: | 2692-8205 |