Fig. 1: Workflow of METI.
From: METI: deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics
METI takes 10x Visium Spatial Transcriptomics (ST) data, with a spot-by-gene matrix for gene expression data, Hematoxylin and Eosin (H&E) images, and XY coordinates that map the location of each spot onto the image as input. With METI algorithm, METI offers cell type identification, nuclei segmentation and the functionality of generating 3D cell density plots in five distinct modules. Module 1 is dedicated to mapping normal and premalignant cells through the integration of gene expression (GE) data and H&E images. Module 2 focuses on identifying cancer cell domains and characterizing their heterogeneity. Module 3 is dedicated to T cell mapping and phenotyping. Module 4 involves in-depth analysis of other immune cells. Lastly, Module 5 pertains to the analysis of Cancer-Associated Fibroblasts (CAFs).
