RNA-seqSingle-cell sequencing provides rich information; however, its clinical use is limited due to high costs and complex data output. Here, we present a protocol for extracting single-cell-related information from bulk RNA sequencing (RNA-seq) data using the pathway-level information extractor ...
The variation of transcriptome size across cell types significantly impacts single-cell RNA sequencing (scRNA-seq) data normalization and bulk RNA-seq cellular deconvolution, yet this intrinsic feature is often overlooked. Here we introduce ReDeconv, a c
The prime-seq protocol is based on the scRNA-seq method SCRB-seq [44] and our optimized derivative mcSCRB-seq [11]. It uses the principles of poly(A) priming, template switching, early barcoding, and UMIs to generate 3′ tagged RNA-seq libraries (Fig.1and Additional file1: Fig. S1)....
Total RNA (100 ng) was used to prepare libraries with the Illumina Stranded Total RNA Prep Ligation with Ribo-Zero Plus kit (Illumina, San Diego, California, USA), following the manufacturer's protocol. TruSeq RNA UD indexes (Integrated DNA Technology – IDT, Coralville, Iowa, USA) were ad...
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...
employed single-cell RNA-seq analysis to identify distinct subsets of chondrocytes, shedding light on the role of ferroptosis in the development of human IVDD [31]. Ling et al. illuminated the engagement of macrophages in the advancement of human intervertebral disc degeneration via single-cell RNA...
Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scR
In this study, we systematically integrated both scRNA-seq and bulk RNA-seq data to identify TIME-related lncRNAs. To further explore the clinical significance of TIME-related lncRNAs, we applied ten popular machine learning algorithms to generate an optimal TIME-related lncRNA signature (TRLS). ...
## 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 == 'healthy'] bulk.case.mtx ...
Bulk ATAC-seq assays have been used to map and profile the chromatin accessibility of regulatory elements such as enhancers, promoters, and insulators. This has provided great insight into the regulation of gene expression in many cell types in a variety