ICOBA: A highly customizable iterative imagej macro for optimization of image co-localization batch analysis
Co-localization analysis is pivotal for understanding protein interactions in biomedical research, yet existing ImageJ and FIJI plug-ins often lack automated multi-channel capabilities, impeding throughput and introducing potential user bias. We introduce ICOBA (Iterative Channel Overlay Batch Analy...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-05-01
|
| Series: | SoftwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711025000615 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849762047513853952 |
|---|---|
| author | Tyler J. Rolland Emily R. Hudson Luke A. Graser Brian R Weil |
| author_facet | Tyler J. Rolland Emily R. Hudson Luke A. Graser Brian R Weil |
| author_sort | Tyler J. Rolland |
| collection | DOAJ |
| description | Co-localization analysis is pivotal for understanding protein interactions in biomedical research, yet existing ImageJ and FIJI plug-ins often lack automated multi-channel capabilities, impeding throughput and introducing potential user bias. We introduce ICOBA (Iterative Channel Overlay Batch Analysis), a freely available ImageJ macro designed to streamline and standardize co-localization workflows across large image datasets. As a demonstration of the workflow and to validate its performance, cardiac fibroblasts were immunostained and imaged on a Leica DMi8 microscope, with .tiff files exported for processing. Compared to traditional manual approaches, ICOBA demonstrated significantly faster single-channel and two-channel processing times without sacrificing quantitative accuracy. By leveraging ImageJ's built-in “record” functionality and a customizable macro script, ICOBA accommodates variable staining conditions and threshold parameters, ensuring both reproducibility and flexibility. These attributes make ICOBA a versatile solution for high-throughput, multi-channel co-localization analyses across diverse research fields, from routine lab applications to advanced tissue-imaging studies. |
| format | Article |
| id | doaj-art-b12f7e27dc0e4882950f317fe5bc73cf |
| institution | DOAJ |
| issn | 2352-7110 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj-art-b12f7e27dc0e4882950f317fe5bc73cf2025-08-20T03:05:50ZengElsevierSoftwareX2352-71102025-05-013010209410.1016/j.softx.2025.102094ICOBA: A highly customizable iterative imagej macro for optimization of image co-localization batch analysisTyler J. Rolland0Emily R. Hudson1Luke A. Graser2Brian R Weil3Department of Physiology & Biophysics at the University at Buffalo and the VA WNY Healthcare System, Buffalo, NY, USADepartment of Physiology & Biophysics at the University at Buffalo and the VA WNY Healthcare System, Buffalo, NY, USADepartment of Pharmacology & Toxicology at the University at Buffalo, Buffalo, NY, USADepartment of Physiology & Biophysics at the University at Buffalo and the VA WNY Healthcare System, Buffalo, NY, USA; Corresponding author at: Department of Physiology and Biophysics, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Clinical Translational Research Center, Suite 7030, 875 Ellicott Street, Buffalo, NY 14203.Co-localization analysis is pivotal for understanding protein interactions in biomedical research, yet existing ImageJ and FIJI plug-ins often lack automated multi-channel capabilities, impeding throughput and introducing potential user bias. We introduce ICOBA (Iterative Channel Overlay Batch Analysis), a freely available ImageJ macro designed to streamline and standardize co-localization workflows across large image datasets. As a demonstration of the workflow and to validate its performance, cardiac fibroblasts were immunostained and imaged on a Leica DMi8 microscope, with .tiff files exported for processing. Compared to traditional manual approaches, ICOBA demonstrated significantly faster single-channel and two-channel processing times without sacrificing quantitative accuracy. By leveraging ImageJ's built-in “record” functionality and a customizable macro script, ICOBA accommodates variable staining conditions and threshold parameters, ensuring both reproducibility and flexibility. These attributes make ICOBA a versatile solution for high-throughput, multi-channel co-localization analyses across diverse research fields, from routine lab applications to advanced tissue-imaging studies.http://www.sciencedirect.com/science/article/pii/S2352711025000615ICOBAImageJ macroCo-localizationImage analysis |
| spellingShingle | Tyler J. Rolland Emily R. Hudson Luke A. Graser Brian R Weil ICOBA: A highly customizable iterative imagej macro for optimization of image co-localization batch analysis SoftwareX ICOBA ImageJ macro Co-localization Image analysis |
| title | ICOBA: A highly customizable iterative imagej macro for optimization of image co-localization batch analysis |
| title_full | ICOBA: A highly customizable iterative imagej macro for optimization of image co-localization batch analysis |
| title_fullStr | ICOBA: A highly customizable iterative imagej macro for optimization of image co-localization batch analysis |
| title_full_unstemmed | ICOBA: A highly customizable iterative imagej macro for optimization of image co-localization batch analysis |
| title_short | ICOBA: A highly customizable iterative imagej macro for optimization of image co-localization batch analysis |
| title_sort | icoba a highly customizable iterative imagej macro for optimization of image co localization batch analysis |
| topic | ICOBA ImageJ macro Co-localization Image analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2352711025000615 |
| work_keys_str_mv | AT tylerjrolland icobaahighlycustomizableiterativeimagejmacroforoptimizationofimagecolocalizationbatchanalysis AT emilyrhudson icobaahighlycustomizableiterativeimagejmacroforoptimizationofimagecolocalizationbatchanalysis AT lukeagraser icobaahighlycustomizableiterativeimagejmacroforoptimizationofimagecolocalizationbatchanalysis AT brianrweil icobaahighlycustomizableiterativeimagejmacroforoptimizationofimagecolocalizationbatchanalysis |