Mistic: An open-source multiplexed image t-SNE viewer

ABSTRACT: Summary Understanding the complex ecology of a tumor tissue and the spatiotemporal relationships between its cellular and microenvironment components is becoming a key component of translational research, especially in immuno-oncology. The generation and analysis of multiplexed images from patient samples is of paramount importance to facilitate this understanding. Here, we present Mistic, an open-source multiplexed image t-SNE viewer that enables the simultaneous viewing of multiple 2D images rendered using multiple layout options to provide an overall visual preview of the entire dataset. In particular, the positions of the images can be t-SNE or UMAP coordinates. This grouped view of all images allows an exploratory understanding of the specific expression pattern of a given biomarker or collection of biomarkers across all images, helps to identify images expressing a particular phenotype, and can help select images for subsequent downstream analysis. Currently, there is no freely available tool to generate such image t-SNEs. Highlights • Mistic is a multiplexed image t-SNE viewer• Mistic enables the simultaneous viewing of multiple 2D images• This grouped overview allows visualization of existing patterns in the data• Mistic supports images from Vectra, CyCIF, t-CyCIF, and CODEX The bigger picture A crucial component of translational research is in exploiting tumor tissue for diagnostic or prognostic purposes. We believe this can best be achieved through a deeper understanding of the complex ecology of a tumor tissue and the spatiotemporal relationships between its cellular and microenvironment components. Multiplexed images from patient samples facilitate this understanding. We present Mistic, an open-source multiplexed image t-SNE viewer that enables the simultaneous viewing of multiple 2D multiplexed images to provide an overall visual preview of the entire dataset. This allows an exploratory understanding of underlying patterns in the data such as the specific expression pattern of a given biomarker across all images. Currently, there is no free tool to generate such image t-SNEs. Mistic aims to fill this gap by providing an easy to implement tool with simple functionality to view multiple images at once. Mistic supports images from Vectra, CyCIF, t-CyCIF, and CODEX. Multiplex imaging of tissues allows the simultaneous imaging of multiple biomarkers on a tissue specimen of interest and is a critical tool for clinical cancer diagnosis and prognosis. A common way to visualize and better understand such multiplexed images is to utilize dimensionality reduction (DR) methods, where each image is abstracted as a point in the reduced space. We developed Mistic to enable the simultaneous viewing of multiple 2D multiplexed images by combining DR, image processing, and GUI programming.

SUBMITTER: Prabhakaran S 

PROVIDER: S-EPMC9278502 | biostudies-literature |

REPOSITORIES: biostudies-literature