Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

High-throughput error corrected Nanopore single cell transcriptome sequencing

ABSTRACT: High-throughput error corrected Nanopore single cell transcriptome sequencing

PROVIDER: PRJNA541014 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other
	SRR9008430_1.fastq.gz	Fastqsanger.gz
	SRR9008431_1.fastq.gz	Fastqsanger.gz
	SRR9008432_1.fastq.gz	Fastqsanger.gz
	SRR9008433_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 9

Similar Datasets

High-throughput error corrected Nanopore single cell transcriptome sequencing

Project description:E18 mouse brain single cell profiling using the 10x Genomics Chromium instrument workflow with either Illumina short read sequencing for the standard gene profiling and Nanopore PromethION long read sequencing for isoform profiling.

2020-07-10 | GSE130708 | GEO

High throughput error correction using dual nucleotide dimer blocks allows direct single-cell nanopore transcriptome sequencing

Project description:Droplet-based single-cell sequencing techniques have provided unprecedented insight into cellular heterogeneities within tissues. However, these approaches only allow for the measurement of the distal parts of a transcript following short-read sequencing. Therefore, splicing and sequence diversity information is lost for the majority of the transcript. The application of long-read Nanopore sequencing to droplet-based methods is challenging because of the low base-calling accuracy currently associated with Nanopore sequencing. Although several approaches that use additional short-read sequencing to error-correct the barcode and UMI sequences have been developed, these techniques are limited by the requirement to sequence a library using both short- and long-read sequencing. Here we introduce a novel approach termed single-cell Barcode UMI Correction sequencing (scBUC-seq) to efficiently error-correct barcode and UMI oligonucleotide sequences synthesized by using blocks of dimeric nucleotides. The method can be applied to correct both short-read and long-read sequencing, thereby allowing users to recover more reads per cell that permits direct single-cell Nanopore sequencing for the first time. We illustrate our method by using species-mixing experiments to evaluate barcode assignment accuracy and multiple myeloma cell lines to evaluate differential isoform usage and Ewing’s sarcoma cells to demonstrate Ig fusion transcript analysis.

2021-01-31 | GSE162053 | GEO

High throughput error corrected Nanopore single cell transcriptome sequencing.

Project description:Droplet-based high throughput single cell sequencing techniques tremendously advanced our insight into cell-to-cell heterogeneity. However, those approaches only allow analysis of one extremity of the transcript after short read sequencing. In consequence, information on splicing and sequence heterogeneity is lost. To overcome this limitation, several approaches that use long-read sequencing were introduced recently. Yet, those techniques are limited by low sequencing depth and/or lacking or inaccurate assignment of unique molecular identifiers (UMIs), which are critical for elimination of PCR bias and artifacts. We introduce ScNaUmi-seq, an approach that combines the high throughput of Oxford Nanopore sequencing with an accurate cell barcode and UMI assignment strategy. UMI guided error correction allows to generate high accuracy full length sequence information with the 10x Genomics single cell isolation system at high sequencing depths. We analyzed transcript isoform diversity in embryonic mouse brain and show that ScNaUmi-seq allows defining splicing and SNVs (RNA editing) at a single cell level.

| S-EPMC7423900 | biostudies-literature

High throughput error correction using dual nucleotide dimer blocks allows direct single-cell nanopore transcriptome sequencing

Project description:High throughput error correction using dual nucleotide dimer blocks allows direct single-cell nanopore transcriptome sequencing

| PRJNA680369 | ENA

Error-corrected sequencing strategies enable comprehensive detection of leukemic mutations relevant for diagnosis and minimal residual disease monitoring

Project description:Error-corrected sequencing strategies specific for leukemias

| PRJEB36035 | ENA

ESPRESSO: Robust discovery and quantification of transcript isoforms from error-prone long-read RNA-seq data

Project description:Long-read RNA sequencing (RNA-seq) holds great potential for characterizing transcriptome variation and full-length transcript isoforms, but the relatively high error rate of current long-read sequencing platforms poses a major challenge. We present ESPRESSO, a computational tool for robust discovery and quantification of transcript isoforms from error-prone long reads. ESPRESSO jointly considers alignments of all long reads aligned to a gene and uses error profiles of individual reads to improve the identification of splice junctions and the discovery of their corresponding transcript isoforms. On both a synthetic spike-in RNA sample and human RNA samples, ESPRESSO outperforms multiple contemporary tools in not only transcript isoform discovery but also transcript isoform quantification. In total, we generated and analyzed ~1.1 billion nanopore RNA-seq reads covering 30 human tissue samples and three human cell lines. ESPRESSO and its companion dataset provide a useful resource for studying the RNA repertoire of eukaryotic transcriptomes.

2022-10-14 | GSE192955 | GEO

High-throughput sequencing of MiRNA

Project description:High-throughput sequencing of MiRNA

| PRJNA554107 | ENA

High-throughput high-multiplexed screening for splicing factors

Project description:High-throughput high-multiplexed screening for splicing factors

| PRJNA854891 | ENA

Error-correction enables use of Oxford Nanopore technology for reference-free transcriptome analysis

Project description:Error-correction enables use of Oxford Nanopore technology for reference-free transcriptome analysis

| PRJEB34849 | ENA

High-throughput capture of ectopic chromosomal sequence

Project description:DNA double-strand breaks (DSBs) are a prominent source of genetic instability/variability frequently associating genome rearrangements with the capture of ectopic chromosomal sequences (ECSs) at junctions. Homologous recombination (HR) is considered in textbooks as an error-free DSB repair mechanism that protects against genome instability. Contradicting this dogma, we show that silencing the central HR players RAD51 or BRCA2 suppresses the sequence homology-independent capture of ECS at the junctions of distant DSBs, especially in 53BP1-depleted cells. We confirmed the requirement of RAD51 for ECS capture at a genome-wide level through high-throughput genome translocation sequencing.

2022-01-17 | GSE126546 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data