학술논문

Mosaic-PICASSO: accurate crosstalk removal for multiplex fluorescence imaging.
Document Type
Article
Source
Bioinformatics. Jan2024, Vol. 40 Issue 1, p1-8. 8p.
Subject
*FLUORESCENCE
*BIOLOGICAL specimens
*FLUOROPHORES
*BIOLOGICAL systems
Language
ISSN
1367-4803
Abstract
Motivation Ultra-multiplexed fluorescence imaging has revolutionized our understanding of biological systems, enabling the simultaneous visualization and quantification of multiple targets within biological specimens. A recent breakthrough in this field is PICASSO, a mutual-information-based technique capable of demixing up to 15 fluorophores without their spectra, thereby significantly simplifying the application of ultra-multiplexed fluorescence imaging. However, this study has identified a limitation of mutual information (MI)-based techniques. They do not differentiate between spatial colocalization and spectral mixing. Consequently, MI-based demixing may incorrectly interpret spatially co-localized targets as non-colocalized, leading to overcorrection. Results We found that selecting regions within a multiplex image with low-spatial similarity for measuring spectroscopic mixing results in more accurate demixing. This method effectively minimizes overcorrections and promises to accelerate the broader adoption of ultra-multiplex imaging. Availability and implementation The codes are available at https://github.com/xing-lab-pitt/mosaic-picasso. [ABSTRACT FROM AUTHOR]