Fig. 1: Characterization of scRNA-seq data in the pan-cancer TME.
a, Schematic depicting the TabulaTIME framework and its application. TabulaTIME was applied within a multiphase workflow, encompassing tumor-related scRNA-seq data collection, data preprocessing and MetaCell identification, integration of all lineages, lineage-specific integration and characterization of cell subtypes; Imm-reg, immune-regulatory; AP, antigen-presenting; TCA, tricarboxylic acid; NSCLC, non-small cell lung cancer; HNSC, head and neck squamous cell carcinoma; KIPAN, pan-kidney cohort; OV, ovarian serous cystadenocarcinoma; ESCA, esophageal cancer; CRC, colorectal cancer; SKCM, skin cutaneous melanoma; PRAD, prostate adenocarcinoma; LIHC, liver hepatocellular carcinoma; UVM, uveal melanoma. b, Data collection statistics. The numbers of cells (top) and donors (bottom) collected for each tissue are presented; k indicates ×1,000. c, Uniform manifold approximation and projection (UMAP) visualization of all MetaCells, colored by the cell type (top) and source (bottom), respectively. d, Expression of cell-type-specific markers. Dot size and color represent the percentage of cells with the gene expressed and the average expression value, respectively; Mono, monocytes; Macro, macrophages; DC, dendritic cells; Treg, regulatory T cells; CD4+ Tconv, conventional CD4+ T cells; Tprolif, proliferating T cells.
