Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Effect of 4sU labeling durations on quantification bias in nucleotide conversion RNA-seq data

ABSTRACT: Effect of 4sU labeling durations on quantification bias in nucleotide conversion RNA-seq data

PROVIDER: PRJNA954792 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR24144023_1.fastq.gz	Fastqsanger.gz
	SRR24144023_2.fastq.gz	Fastqsanger.gz
	SRR24144024_1.fastq.gz	Fastqsanger.gz
	SRR24144024_2.fastq.gz	Fastqsanger.gz
	SRR24144025_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 24

Similar Datasets

Effect of 4sU labeling durations on quantification bias in nucleotide conversion RNA-seq data

Project description:To investigate the effect of labeling durations on quantification bias in nucleotide conversion RNA-seq, we labeled NIH cells with 4sU. We then measured 4sU dropout in 4sU samples compared to 4sU naive samples.

2024-02-06 | GSE229506 | GEO

Effect of 4sU labeling concentrations on quantification bias in nucleotide conversion RNA-seq data

Project description:To investigate the effect of increasing 4sU labeling concentrations on quantification bias in nucleotide conversion RNA-seq, we labeled 3 different cell lines with increasing concentrations of 4sU. We then measured 4sU dropout in 4sU samples compared to 4sU naive samples.

2024-02-06 | GSE229504 | GEO

Effect of 4sU labeling on quantification bias in nucleotide conversion RNA-seq data

Project description:Effect of 4sU labeling on quantification bias in nucleotide conversion RNA-seq data

| PRJNA954780 | ENA

Effect of 4sU labeling concentrations on quantification bias in nucleotide conversion RNA-seq data

Project description:Effect of 4sU labeling concentrations on quantification bias in nucleotide conversion RNA-seq data

| PRJNA954793 | ENA

Effect of TUC-seq protocol versus SLAM-seq on quantification bias in nucleotide conversion RNA-seq data

Project description:To investigate the effect of TUC-seq versus SLAM-seq on quantification bias in nucleotide conversion RNA-seq, we performed SLAM-seq and TUC-seq on NIH cells. We then measured 4sU dropout in 4sU samples compared to 4sU naive samples.

2024-02-06 | GSE253169 | GEO

Effect of 4sU labeling on quantification bias in nucleotide conversion RNA-seq data

Project description:This SuperSeries is composed of the SubSeries listed below.

2024-02-06 | GSE229507 | GEO

Effect of performing SLAM-seq chemistry in methanol fixed cells versus standard tube processing on quantification bias in nucleotide conversion RNA-seq data

Project description:To investigate the occuring 4sU dropout during library preparation we performed SLAM conversion either in intact, methanol fixed cells or in tubes

2024-02-06 | GSE253370 | GEO

Bias-minimized quantification of microRNA reveals widespread alternative processing and 3′ end modification

Project description:MicroRNAs (miRNAs) modulate diverse biological and pathological processes via post-transcriptional gene silencing. High-throughput small RNA sequencing (sRNA-seq) has been widely adopted to investigate the functions and regulatory mechanisms of miRNAs. However, accurate quantification of miRNAs has been limited owing to the severe ligation bias in conventional sRNA-seq methods. Here we quantify miRNAs and their variants (known as isomiRs) by an improved sRNA-seq protocol, termed AQ-seq (accurate quantification by sequencing), that utilizes adapters with terminal degenerate sequences and a high concentration of polyethylene glycol (PEG), which minimize the ligation bias during library preparation. Measurement using AQ-seq allows us to correct the previously misannotated 5′ end usage and strand preference in public databases. Importantly, the analysis of 5′ terminal heterogeneity reveals widespread alternative processing events which have been underestimated. We also identify highly uridylated miRNAs originating from the 3p strands, indicating regulations mediated by terminal uridylyl transferases at the pre-miRNA stage. Taken together, our study reveals the complexity of the miRNA isoform landscape, allowing us to refine miRNA annotation and to advance our understanding of miRNA regulation. Furthermore, AQ-seq can be adopted to improve other ligation-based sequencing methods including crosslinking-immunoprecipitation-sequencing (CLIP-seq) and ribosome profiling (Ribo-seq).

2018-12-12 | GSE123627 | GEO

Effect of TUC-seq protocol versus SLAM-seq on quantification bias in nucleotide conversion RNA-seq data

Project description:Effect of TUC-seq protocol versus SLAM-seq on quantification bias in nucleotide conversion RNA-seq data

| PRJNA1064143 | ENA

Quantification, dynamic visualization, and validation of bias in ATAC-seq data with ataqv

Project description:Quantification, dynamic visualization, and validation of bias in ATAC-seq data with ataqv

| PRJNA540283 | ENA