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Automated, image-based quantification of peroxisome characteristics with perox-per-cell.
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.
Afiliação
  • Neal ML; Seattle Children's Research Institute, Center for Global Infectious Disease Research, Seattle, WA USA.
  • Shukla N; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA USA.
  • Mast FD; Seattle Children's Research Institute, Center for Global Infectious Disease Research, Seattle, WA USA.
  • Farré JC; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA USA.
  • Pacio TM; Seattle Children's Research Institute, Center for Global Infectious Disease Research, Seattle, WA USA.
  • Raney-Plourde KE; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA USA.
  • Prasad S; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA USA.
  • Subramani S; Department of Molecular Biology, School of Biological Sciences, University of California, San Diego, La Jolla, CA USA.
  • Aitchison JD; Seattle Children's Research Institute, Center for Global Infectious Disease Research, Seattle, WA USA.
Bioinformatics ; 2024 Jul 13.
Article em En | MEDLINE | ID: mdl-39001800
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.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article