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


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

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Publications

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

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]

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