Ayako Suzuki1 & Masahide Seki1 When biologically interpretation of the data obtained from the single-cell RNA sequencing (scRNA- seq) analysis is attempted, additional information on the location of the single cells, behavior of the surrounding cells, and the microenvironment they generate, ...
Despite its widespread use, RNA-seq is still too laborious and expensive to replace RT-qPCR as the default gene expression analysis method. We present a novel approach, BRB-seq, which uses early multiplexing to produce 3′ cDNA libraries for dozens of sa
The bulk short-read RNA-seq can be used to quantify gene expression and alternative exon usage with high accuracy in various tissues or cell types. Single-cell RNA sequencing is powerful in revealing heterogeneity in gene expression within cell types. Full-length RNA-seq protocols such as Smart-...
然后分别加载后熟悉一下: ## Bulk RNA-seq data #benchmark.eset = readRDS("https://xuranw.github.io/MuSiC/data/bulk-eset.rds") benchmark.eset = readRDS("bulk-eset.rds") benchmark.eset table(benchmark.eset$group) bulk.control.mtx = exprs(benchmark.eset)[, benchmark.eset$group == 'he...
RNA-sequencing has become a standard tool for analyzing gene activity in bulk samples and at the single-cell level. By increasing sample sizes and cell counts, this technique can uncover substantial information about cellular transcriptional states. Beyond quantification of gene expression, RNA-seq can...
TIME-related lncRNA signature DDR: DNA damage repair scRNA-seq: Single-cell RNA sequencing PCA: Principal component analysis UMAP: Uniform Manifold Approximation and Projection RMA: Robust multi-array average WGCNA: Weighted correlation network analysis TOM: Topological overlap matrix GO: Ge...
The RNA-seq data of IER3 were obtained from TCGA (https://portal.gdc.cancer.gov/) and CGGA databases and transformed into log2(TPM + 1)-normalized profiles [16]. The microarray data of IER3 in the GSE16011 set were downloaded from the Gene Expression Omnibus (GEO) database (http...
Bulk-based RNA-SeqCorrelation coefficientCount dataGene coexpression networkGene regulatory networkGene coexpression networks (GCNs) are useful tools for inferring gene functions and understanding biological processes when properly constructed. Traditional microarray analysis is being more frequently replaced by...
In summary, we have developed a prognostic signature comprising 16 novel CRCSCs-related genes through the integration of scRNA-seq and Bulk RNA-seq analysis. The validation of this signature demonstrated its effectiveness in predicting the prognosis of patients with CRC, positioning it as an independ...
RNA sequencing experiments generate large amounts of information about expression levels of genes. Although they are mainly used for quantifying expression levels, they contain much more biologically important information such as copy number variants (CN