Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Nanopore-based targeted next-generation sequencing (tNGS): a versatile technology specialized in detecting low bacterial load clinical specimens

PROVIDER: PRJNA1238507 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR32793100_1.fastq.gz	Fastqsanger.gz
	SRR32793200_1.fastq.gz	Fastqsanger.gz
	SRR32793101_1.fastq.gz	Fastqsanger.gz
	SRR32793201_1.fastq.gz	Fastqsanger.gz
	SRR32793102_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 242

Similar Datasets

A solution to achieve sequencing from SARS-CoV-2 specimens with low viral loads: Concatenation of reads from independent reactions

Project description:SARS-CoV-2 sequencing of specimens with low viral load

| PRJEB60934 | ENA

Capturing SARS-cov in low abundant patient samples: a comparative analysis (arbo double ms) .

Project description:In this study, we tested the efficacy of five commercial probes panels at detecting SARS-CoV-2 genome including panels from Illumina, Twist Bioscience and Arbor Bioscience. To do so, we used 19 patient nasal swab samples broken down into 5 series of 4 samples of equivalent SARS-CoV-2 viral load (cycle threshold (CT): low CT means a high viral load – CT26, CT29, CT32, CT35 and CT36+).

2022-06-01 | E-MTAB-11232 | biostudies-arrayexpress

Capturing SARS-cov in low abundant patient samples: a comparative analysis (arbo single MS).

2022-06-01 | E-MTAB-11235 | biostudies-arrayexpress

Capturing SARS-cov in low abundant patient samples: a comparative analysis (Illumina respv NS).

2022-02-08 | E-MTAB-11233 | biostudies-arrayexpress

Capturing SARS-cov in low abundant patient samples: a comparative analysis (Twist sarscov MS).

2022-06-01 | E-MTAB-11234 | biostudies-arrayexpress

Capturing SARS-cov in low abundant patient samples: a comparative analysis (metagenomics NS).

2022-06-01 | E-MTAB-11236 | biostudies-arrayexpress

Capturing SARS-cov in low abundant patient samples: a comparative analysis (twist panviral NS).

2022-06-01 | E-MTAB-11237 | biostudies-arrayexpress

Simultaneous identification of m6A and m5C reveals coordinated RNA modification at single-molecule resolution [mouse frontal cortex]

Project description:The expanding field of epitranscriptomics might rival the epigenome in the diversity of biological processes impacted. However, the identification of multiple modification types in individual RNA molecules remains challenging. We present CHEUI, a new method that detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual transcript molecules in a single condition as well as differential methylation between two conditions, using nanopore signals. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. Moreover, CHEUI’s unique capability to identify different modifications in the same signal data reveals a non-random co-occurrence of m6A and m5C in transcripts in human cell lines and during mouse embryonic brain development. CHEUI unlocks the capability of studying links between multiple RNA modifications and phenotypes, enabling the discovery of new epitranscriptome functions. Furthermore, CHEUI's training and testing protocols are adaptable to other modifications, making it a versatile RNA technology.

2022-10-31 | GSE211760 | GEO

Simultaneous identification of m6A and m5C reveals coordinated RNA modification at single-molecule resolution [HeLa cells]

2022-10-31 | GSE211759 | GEO

Prediction of m6A and m5C at single-molecule resolution reveals a transcriptome-wide co-occurrence of RNA modifications

2024-01-16 | GSE253150 | GEO