Statistical validation of triple colocalization analysis

Background: in the last decades, colocalization analysis of fluorescently tagged biomolecules has proven to be a powerful approach to studying functional relationships between these biomolecules. However, in many cases, to give this analysis a biological meaning, colocalization coefficients must be...

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Autores principales: Buonfigli, Julio, Quintero, Cristian, Sánchez, Diego, Leiva, Natalia, Damiani, Maria Teresa
Formato: Artículo Científico
Lenguaje:Inglés
Publicado: 2025
Materias:
Scrambling
Overlapping
Significance
Correlation
Triple
Acceso en línea:https://repositorio.umaza.edu.ar/handle/00261/3593
Aporte de:
UMAZA Digital (Universidad MAZA - Mendoza) de Universidad Juan Agustín MAZA
id I56-R162-00261-3593
record_format dspace
spelling I56-R162-00261-35932025-09-17T14:35:03Z Statistical validation of triple colocalization analysis Buonfigli, Julio Quintero, Cristian Sánchez, Diego Leiva, Natalia Damiani, Maria Teresa Scrambling Overlapping Significance Correlation Triple Background: in the last decades, colocalization analysis of fluorescently tagged biomolecules has proven to be a powerful approach to studying functional relationships between these biomolecules. However, in many cases, to give this analysis a biological meaning, colocalization coefficients must be tested statistically, comparing them with the colocalization expected by chance. Aim: It addressed the statistical significance of triple colocalization to distinguish real triple colocalization and classify different triple signal scenarios. Methods: we use biological and generated images of triple signal scenarios to contrast seven independent statistical facts with independent statistical tests. Three of these tests correspond to pairwise relationships (double scrambling tests), and the others correspond to triple relationships: single scrambling tests (red, green, and blue scrambling) and the triple scrambling test. The analysis and methodology proposed can be reproduced using the application developed in our laboratory. Results: In the study approach, we found true triple relationships ignored by using traditional methods of computing the statistical significance, while we could reinterpret cases of not significant triple colocalization wrongly considered as significant by traditional methods. Discussion: single scrambling tests can reveal significant triple colocalization for low levels of triple co-occurrence, even when all pairwise relationships were exclusion relationships. Moreover, on the other hand, single scrambling tests can reveal the absence of a significant triple colocalization for high levels of triple co-occurrence, even when all pairwise relationships were significant colocalization. Conclusion: all scrambling tests are useful to classify a specific scenario of a triple relationship. Dynamics like mitosis can be distinguished into their phases by triple signal relationships using these 7 independent statistical tests. 2025-09-15T12:53:15Z 2025-09-15T12:53:15Z 2023 Artículo Científico Buonfigli, J., Quintero, C., Sánchez, D., Leiva, N., & Damiani, M. T. (2023). Statistical validation of triple colocalization analysis. Southern Brazilian Journal of Chemistry, 31(36), 45–62. https://doi.org/10.48141/SBJCHEM.v31.n36.2023_BUONFIGLI_pgs_45_62 https://repositorio.umaza.edu.ar/handle/00261/3593 eng info:eu-repo/semantics/altIdentifier/url/10.48141/SBJCHEM.v31.n application/pdf
institution Universidad Juan Agustín MAZA
institution_str I-56
repository_str R-162
collection UMAZA Digital (Universidad MAZA - Mendoza)
language Inglés
orig_language_str_mv eng
topic Scrambling
Overlapping
Significance
Correlation
Triple
spellingShingle Scrambling
Overlapping
Significance
Correlation
Triple
Buonfigli, Julio
Quintero, Cristian
Sánchez, Diego
Leiva, Natalia
Damiani, Maria Teresa
Statistical validation of triple colocalization analysis
topic_facet Scrambling
Overlapping
Significance
Correlation
Triple
description Background: in the last decades, colocalization analysis of fluorescently tagged biomolecules has proven to be a powerful approach to studying functional relationships between these biomolecules. However, in many cases, to give this analysis a biological meaning, colocalization coefficients must be tested statistically, comparing them with the colocalization expected by chance. Aim: It addressed the statistical significance of triple colocalization to distinguish real triple colocalization and classify different triple signal scenarios. Methods: we use biological and generated images of triple signal scenarios to contrast seven independent statistical facts with independent statistical tests. Three of these tests correspond to pairwise relationships (double scrambling tests), and the others correspond to triple relationships: single scrambling tests (red, green, and blue scrambling) and the triple scrambling test. The analysis and methodology proposed can be reproduced using the application developed in our laboratory. Results: In the study approach, we found true triple relationships ignored by using traditional methods of computing the statistical significance, while we could reinterpret cases of not significant triple colocalization wrongly considered as significant by traditional methods. Discussion: single scrambling tests can reveal significant triple colocalization for low levels of triple co-occurrence, even when all pairwise relationships were exclusion relationships. Moreover, on the other hand, single scrambling tests can reveal the absence of a significant triple colocalization for high levels of triple co-occurrence, even when all pairwise relationships were significant colocalization. Conclusion: all scrambling tests are useful to classify a specific scenario of a triple relationship. Dynamics like mitosis can be distinguished into their phases by triple signal relationships using these 7 independent statistical tests.
format Artículo Científico
author Buonfigli, Julio
Quintero, Cristian
Sánchez, Diego
Leiva, Natalia
Damiani, Maria Teresa
author_facet Buonfigli, Julio
Quintero, Cristian
Sánchez, Diego
Leiva, Natalia
Damiani, Maria Teresa
author_sort Buonfigli, Julio
title Statistical validation of triple colocalization analysis
title_short Statistical validation of triple colocalization analysis
title_full Statistical validation of triple colocalization analysis
title_fullStr Statistical validation of triple colocalization analysis
title_full_unstemmed Statistical validation of triple colocalization analysis
title_sort statistical validation of triple colocalization analysis
publishDate 2025
url https://repositorio.umaza.edu.ar/handle/00261/3593
work_keys_str_mv AT buonfiglijulio statisticalvalidationoftriplecolocalizationanalysis
AT quinterocristian statisticalvalidationoftriplecolocalizationanalysis
AT sanchezdiego statisticalvalidationoftriplecolocalizationanalysis
AT leivanatalia statisticalvalidationoftriplecolocalizationanalysis
AT damianimariateresa statisticalvalidationoftriplecolocalizationanalysis
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