RNAseqspatiallyRNA sequencing (RNAseq) can reveal gene fusions, splicing variants, mutations/indels in addition to differential gene expression, thus providing a more complete genetic picture than DNA sequencing. This most widely used technology in genomics tool box has evolved from classic bulk RNA ...
RNA sequencing (RNAseq) can reveal gene fusions, splicing variants, mutations/indels in addition to differential gene expression, thus providing a more complete genetic picture than DNA sequencing. This most widely used technology in genomics tool box has evolved from classic bulk RNA sequencing (RNA...
Fig. 10. Sc-RNA sequencing analysis reveal the PAM.score on single cell level. (A) The distribution of 9 PAM regulators in eight cell types. (B) The different of 9 PAM regulators between normal cells and LUAD cells. (C) The different of PAM.score between normal cells and LUAD cells...
Single-cell RNA-sequencinglung adenocarcinoma (LUAD)cancer-associated fibroblasts (CAFs)immune infiltrationprognostic signatureBackground: An accumulating amount of studies are highlighting the impacts of cancer-associated fibroblasts (CAFs) on the initiation, metastasis, invasion, and immune evasion of lung...
Seurat is a widely used R software package in the analysis of single-cell RNA sequencing (scRNA-seq) data. It is a highly flexible and powerful tool for processing, visualizing, and analyzing gene expression data at the single-cell level. For single-cell data processing, we used the “Seura...
Quality control of single-cell RNA sequencing data was executed with the following criteria: > 200 genes/cell, < 3000 genes/cell, > 3 cells/gene, and < 20% mitochondrion genes. The batch effect of 9 samples was eliminated using IntegrateData of Seurat packages [32]. The...
RNA-seq: Bulk RNA sequencing CRGs: Cuproptosis-related genes ECs: Endothelial cells FDX1: Ferredoxin 1 LIAS: Lipoic acid synthase LIPT1: Lipoyltransferase 1 DLD: Dihydrolipoamide dehydrogenase DLAT: Dihydrolipoamide S-acetyltransferase PDHA1:
scRNA-seq, single-cell RNA sequencing; TME, tumor immune environment; PDAC, pancreatic ductal adenocarcinoma; UMAP, uniform manifold approximation and projection; GSEA, gene set enrichment analysis; TMGs, T cell marker genes; TCGA; The Cancer Genome Atlas; TMGS, T cell marker genes score; Tcm...
Comprehensive analysis of bulk, single-cell RNA sequencing, and spatial transcriptomics revealed IER3 for predicting malignant progression and immunotherapy efficacy in gliomaQi Wang, Chunyu Zhang, Ying Pang, Meng Cheng, Rui Wang, Xu Chen, Tongjie Ji, Yuntong Yang, Jing Zhang & Chun...
Single-cell RNA sequencing (scRNA-Seq) has provided new insights into cancer biology by revealing the landscape of intercellular interactions and cell communication and improving the knowledge of tumor heterogeneity [15,16]. In HGSOC, scRNA-Seq has been used to determine the transcriptomic heterogenei...