Data files and code for analysis of single-cell ccRCC data for the manuscript Tumor-Specific Cell Populations in Clear Cell Renal Carcinoma Associated with Clinical Outcome Identified Using Single-Cell Protein Activity Inference. Includes code for VIPER
a, UMAP analysis of pan-tumour VECs, coloured by inferred cell types.b, The mean proportions of each cancer type between ANT and tumour tissues across VEC subtypes. The dots represent cancer types (n = 31).c, Diffusion map indicating the trajectory of tumour angiogenesis.d, Tumour angio...
With advances in sequencing and instrument technology, bioinformatics analysis is being applied to batches of massive cells at single-cell resolution. High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells, stromal cells or infiltrated immune cells to evalua...
In addition, tumor and immune cell interactions, which characterize the tumor microenvironment, also have a great impact on cancer treatment. Such heterogeneity and complexity of individual tumors are associated with tumor progression [14] and drug resistance [15], which is challenging for precision ...
The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1070 tumor an
Leiden clustering was used to determine joint cell clusters across the entire dataset collection. To ensure the robustness of our data integration, we also analyze the data using Seurat (v4.3.0) pipeline [15]. In the Seurat pre-processing pipeline, the NormalizeData and ScaleData functions were...
Single-cell RNA sequencing (scRNA-seq) is a tool for studying gene expression at the single-cell level that has been widely used due to its unprecedented high resolution. In the present review, we outline the preparation process and sequencing platforms for the scRNA-seq analysis of solid tumor...
Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for characterizing cellular landscapes within complex tissues. Large-scale single-cell transcriptomics holds great potential for identifying rare cell types critical to the p
(B) The single-cell trajectory analysis using cell embeddings learned by different input settings. Cells are classified into two subpopulations: PDX_mRCC, representing the metastatic renal cell carcinoma (RCC), and PDX_pRCC, representing the primary RCC. Table 1. The performance of scCluster ...
and gene count quantification. Cell Ranger pipeline has been developed by 10x Genomics to automatically complete the above steps for Chromium single-cell data. After obtaining the gene count matrix, the next step is processing, which includes quality control, normalization, feature selection, and dime...