WebApr 10, 2024 · Spatiotemporal regulation of the cellular transcriptome is crucial for proper protein expression and cellular function. However, the intricate subcellular dynamics of RNA remain obscured due to ... WebMar 8, 2024 · The gene regulatory network analysis software ANANSE and the motif enrichment software GimmeMotifs were both developed to analyse bulk datasets. Radboud University researchers have developed scANANSE, a software pipeline for gene regulatory network analysis and motif enrichment using single-cell RNA and ATAC datasets.
Gene Expression & Transcriptome Analysis Profiling methods
WebSequencing metrics were shown to be consistent between technical replicates, as well across the entire range of RNA input amounts. The average number of transcripts ≥0.1 TPM (transcripts per kilobase million) was reported as 43,778 ± 1,352 (mean ± s.d., standard deviation), CV=3.1%. WebTranscriptome analysis experiments enable researchers to characterize transcriptional activity (coding and non-coding), focus on a subset of relevant target genes and transcripts, or profile thousands of genes at once to create a global picture of cell function. northeastern css profile due date
Differential transcript usage analysis of bulk and single-cell RNA …
WebSep 1, 2024 · It has been successfully applied to bulk and single-cell RNA-seq data of human and mouse, confirming and extending key results. In addition, we present novel potential DTU applications like the identification of cell-type specific transcript isoforms as biomarkers. Availability and implementation WebApr 14, 2024 · Although previous RNA-seq studies have shown transcriptome changes in the cartilage of piglet tibia , studies on cartilage tissues are still lacking. Therefore, we conducted this RNA-seq study to analyze the non-coding RNAs and mRNA expression profiles in the TIC of the pig. A large number of DEGs that play essential roles in the … WebJul 28, 2024 · The correlations between bulk RNA-seq and pseudo-bulk single-cell transcriptomics profiles were high for all tissues, ranging from 0.76 to 0.88 (fig. S2). All clusters were manually annotated on the basis of known tissue- and cell type–specific markers and their expected expression in the corresponding clusters (data S2 and fig. S3). how to restore line in photoshop