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ABSTRACT: 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.
SUBMITTER: Neal ML
PROVIDER: S-EPMC11269463 | biostudies-literature | 2024 Jul
REPOSITORIES: biostudies-literature
Neal Maxwell L ML Shukla Nandini N Mast Fred D FD Farré Jean-Claude JC Pacio Therese M TM Raney-Plourde Katelyn E KE Prasad Sumedh S Subramani Suresh S Aitchison John D JD
Bioinformatics (Oxford, England) 20240713
<h4>Summary</h4>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 pe ...[more]