Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single cell analysis [Differentiation]

ABSTRACT: BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single cell analysis [Differentiation]

PROVIDER: PRJNA540230 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR8984140_1.fastq.gz	Fastqsanger.gz
	SRR8984140_2.fastq.gz	Fastqsanger.gz
	SRR8984131_1.fastq.gz	Fastqsanger.gz
	SRR8984131_2.fastq.gz	Fastqsanger.gz
	SRR8984141_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 24

Similar Datasets

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis

Project description:BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis

| PRJNA421186 | ENA

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single cell analysis [Genotyping]

Project description:BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single cell analysis [Genotyping]

| PRJNA540229 | ENA

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single cell analysis [Pluripotency]

Project description:BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single cell analysis [Pluripotency]

| PRJNA540231 | ENA

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis

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

2019-07-05 | GSE107723 | GEO

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis.

Project description:We describe a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts or genomic regions from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, which are all pre-selected and optimized in silico. By applying the matrices in a novel workflow named Barcode Assembly foR Targeted Sequencing (BART-Seq), we analyze developmental states of thousands of single human pluripotent stem cells, either in different maintenance media or upon Wnt/β-catenin pathway activation, which identifies the mechanisms of differentiation induction. Moreover, we apply BART-Seq to the genetic screening of breast cancer patients and identify BRCA mutations with very high precision. The processing of thousands of samples and dynamic range measurements that outperform global transcriptomics techniques makes BART-Seq first targeted sequencing technique suitable for numerous research applications.

| S-EPMC6683345 | biostudies-literature

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single cell analysis [Pluripotency]

Project description:We describe a novel workflow named Barcode Assembly foR Targeted Sequencing, which is a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts (rBART-Seq) or genomic regions (gBART-Seq) from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, for generating amplicons with dual indices. Here, we used the rBART-Seq for RNA quantification, and for the analysis of developmental states of thousands of single human pluripotent stem cells maintained in different media (mTeSR™1, KSR-bFGF, and E8).

2019-07-07 | GSE130422 | GEO

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single cell analysis [Genotyping]

Project description:We describe a novel workflow named Barcode Assembly foR Targeted Sequencing, which is a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts (rBART-Seq) or genomic regions (gBART-Seq) from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, for generating amplicons with dual indices. Here, we used the gBART-Seq for genetic screening of breast cancer patients and identified BRCA mutations with very high precision.

2019-07-07 | GSE130421 | GEO

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single cell analysis [Differentiation]

Project description:We describe a novel workflow named Barcode Assembly foR Targeted Sequencing, which is a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts (rBART-Seq) or genomic regions (gBART-Seq) from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, for generating amplicons with dual indices. Here, we used the rBART-Seq to analyze cell subpopulations that emerge during 72 hours of Wnt/β-catenin pathway activation of H9 hESCs using recombinant Wnt protein (rWnt3a), a small molecule inhibitor of GSK-3 (CHIR99021), or Dox-inducible constitutively active β-catenin (ΔN90).

2019-07-07 | GSE130420 | GEO

A generic, cost-effective and scalable cell lineage analysis platform

Project description:A generic, cost-effective and scalable cell lineage analysis platform

| PRJEB13000 | ENA

A generic, cost-effective and scalable cell lineage analysis platform

Project description:Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing based methods for cell lineage analysis depend on low resolution bulk analysis or rely on extensive single cell sequencing which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way towards large-scale human cell lineage discovery.

2016-04-18 | E-MTAB-4553 | biostudies-arrayexpress

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