Published in

F1000Research, F1000Research, (11), p. 1121, 2022

DOI: 10.12688/f1000research.124990.1

Links

Tools

Export citation

Search in Google Scholar

A flexible open-source processing workflow for multiplexed fluorescence imaging based on cycles

Journal article published in 2022 by Guillaume Potier ORCID, Aurélie Doméné ORCID, Perrine Paul-Gilloteaux ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Red circle
Preprint: archiving forbidden
Red circle
Postprint: archiving forbidden
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

Background Multiplexing tissue imaging is developing as a complement for single cell analysis, bringing the spatial information of cells in tissue in addition to multiple parameters measurements. More and more commercial or home-made systems are available. These techniques allow the imaging of tens of fluorescent reporters, where the spectral overlap is solved by imaging by cycles the fluorophores using microfluidics to change the reporters between each cycle. Methods For several systems, the acquisition system coupled to the microfluidic system is a wide field microscope, and the acquisition process is done by mosaicking to cover a large field of view, relying on image processing to obtain the data set to be analysed in intensity. The processed data set allows the identification of different populations, quite similarly to cytometry analysis, but with spatial information in addition. To obtain the final image for analysis from the raw acquisitions, several preprocessing steps are needed for inter-cycle registration, tissue autofluorescence correction or mosaicking. We propose a workflow for this preprocessing, implemented as an open source software (as a library, command line tool and standalone). Results We exemplify the workflow on the commercial system PhenoCycler® (formerly named CODEX®) and provide a reduced size data set for testing. Conclusions We compare our processor with the commercially provided processor and show that we solve some problems also reported by other users.