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The Cell DIVE™ platform produces single tissue sections stained with over 40 biomarkers and multiple channels merged into a single ome.tiff image using proprietary image stitching software.

The Cell DIVE multiplexed images are fully compatible with the QuPath open-source software for multi-marker visualisation and single-cell phenotyping. Cell DIVE outputs can also be analysed with commercial solutions like the HALO® platform consisting of several modular packages which can together provide a user-friendly workflow ranging from tissue classification and image segmentation to downstream quantitative analyses for generating publication-ready figures.

Beyond these available solutions, our team's current focus is on developing a custom image-analysis pipeline for Cell DIVE users. Cell DIVE's Multiplex Analysis Pipeline (DIVE-MAP) would build upon pretrained TissueNet datasets, employing the open-source Mesmer/DeepCell algorithm for nuclear and cellular segmentation of single-cell markers, followed by downstream spatial clustering and niche-based analysis of tissues.

We are presently working with the Multiplexed Imaging Users Group (MIUG) to improve current methods of membrane segmentation and our future plans include expansion of the analysis pipeline for broad applicability across different multiplexing platforms such as the MIBIscope.

The OxCODE project in collaboration with THL paved the way for biomarker analysis integration across multiplexing platforms such as the Cell DIVE and Vectra Polaris. DPOC further aims to build upon existing collaborations to provide a cross-platform image analysis pipeline that can leverage advances in multi-omic technologies for quantification of cell-cell interactions at an unprecedented resolution.

Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases.

Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes
in four chronic inflammatory diseases.