Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multiplexed Single Cell gene expression profile of barcoded SUM159PT cells

ABSTRACT: Multiplexed Single Cell gene expression profile of barcoded SUM159PT cells

PROVIDER: PRJEB63146 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Multiplexed Single Cell gene expression profile of barcoded SUM159PT cells

Project description:Cancer is a heterogeneous disease, where multiple, phenotypically distinct subpopulations co-exist. Tumour evolution is a result of a complex interplay of genetic and epigenetic factors. To predict the molecular drivers of distinct cancer responses, we apply single-cell lineage tracing (scRNA-Seq of barcoded cells) on a triple-negative breast cancer model. SUM159PT cells infected with a lentiviral barcode library (Perturb-seq Library) were sorted according to the presence of BFP signal, treated or not with paclitaxel (PTX), multiplexed with MULTI-Seq protocol, and then processed by scRNA-Seq.

2024-05-24 | E-MTAB-13066 | biostudies-arrayexpress

Single Cell gene expression and DNA accessibility profile of barcoded SUM159PT cells

2024-05-24 | E-MTAB-13064 | biostudies-arrayexpress

Single Cell gene expression and DNA accessibility profile of barcoded SUM159PT cells

Project description:Single Cell gene expression and DNA accessibility profile of barcoded SUM159PT cells

| PRJEB63326 | ENA

Targeted DNA sequencing of barcoded SUM159PT cells

Project description:Targeted DNA sequencing of barcoded SUM159PT cells

| PRJNA914689 | ENA

Targeted DNA sequencing of barcoded SUM159PT cells

Project description:Cancer is a heterogeneous disease, where multiple, phenotypically distinct subpopulations co-exist. Tumour evolution is a result of a complex interplay of genetic and epigenetic factors. To predict the molecular drivers of distinct cancer responses, we apply single-cell lineage tracing (scRNA-Seq of barcoded cells) on a triple-negative breast cancer model. We propose GALILEO, a framework providing lineage tracing, transcriptomic, and chromatin accessibility information simultaneously at single-cell resolution (Multiome ATAC + gene expression on barcoded cells). The combination of single-cell lineage tracing with phenotypic assays allows to link a cell state with its fate.

2024-05-31 | GSE221495 | GEO

SUM159PT

Project description:SUM159PT

| PRJNA922598 | ENA

Barcoded oligonucleotides ligated on RNA amplified for multiplexed and parallel in situ analyses

Project description:We present Barcoded Oligonucleotides Ligated On RNA Amplified for Multiplexed and parallel In Situ analyses (BOLORAMIS), a reverse transcription-free method for spatially-resolved, targeted, in situ RNA identification of single or multiple targets. BOLORAMIS was demonstrated on a range of cell types and human cerebral organoids. Singleplex experiments to detect coding and non-coding RNAs in human iPSCs showed a stem-cell signature pattern. Specificity of BOLORAMIS was found to be 92% as illustrated by a clear distinction between human and mouse housekeeping genes in a co-culture system, as well as by recapitulation of subcellular localization of lncRNA MALAT1. Sensitivity of BOLORAMIS was quantified by comparing with single molecule FISH experiments and found to be 11%, 12% and 35% for GAPDH, TFRC and POL2RA respectively. To demonstrate BOLORAMIS for multiplexed gene analysis, we targeted 96 mRNAs within a co-culture of iNGN neurons and HMC3 human microglia cells. We used fluorescence in situ sequencing to detect error-robust 8-base barcodes associated with each of these genes. We then used this data to uncover the spatial relationship among cells and transcripts by performing single-cell clustering and gene-gene proximity analyses. We anticipate the BOLORAMIS technology for in situ RNA detection to find applications in basic and translational research.

2021-02-07 | GSE166293 | GEO

Highly multiplexed and quantitative cell surface protein profiling using genetically barcoded antibodies

Project description:Next generation sequencing (NGS) allows for sensitive quantification of DNA and RNA. It would be highly desirable to have a systematic equivalent for assaying cellular protein levels on living cells. We present a highly multiplexed, quantitative, and inexpensive sequencing-based proteomic method using genetically barcoded antibodies called Phage-antibody Next Generation Sequencing (PhaNGS). We demonstrate the utility of PhaNGS by showing how a set of 144 targeted Fab-phage can reliably detect changes in 44 targeted cell surface proteins in drug sensitive and resistant B-cells, or upon induction of the Myc oncogene.

2018-02-12 | GSE102712 | GEO

High-Complexity Barcoded Rabies Virus for Scalable Circuit Mapping Using Single-Cell and Single-Nucleus Sequencing

Project description:Single cell genomics has revolutionized our understanding of the diversity of neuronal cell types. However, scalable technologies for probing single-cell connectivity are lacking, and we are just beginning to understand how molecularly defined cell types are organized into functional circuits. Here, we describe a strategy to generate high-complexity barcoded rabies virus (RV) for scalable circuit mapping that is compatible with both single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) readout. Our barcoded RV libraries contain up to 43 million unique barcodes with a relatively uniform distribution, allowing multiplexed circuit mapping from tens of thousands of individual starter cells. We demonstrate the utility of this approach by mapping the emerging circuits in the developing human cortex using organotypic slice cultures. By leveraging the power and throughput of single cell genomics for mapping synaptic connectivity, we chart a path forward for scalable circuit mapping of molecularly-defined cell types in healthy and disease states.

2026-02-17 | GSE277536 | GEO

Gene expression profile at single cell level of SUM149PT, SUM185PE, SUM229PE, SUM159PT and SUM1315MO2 cell lines

Project description:SUM149PT, SUM185PE, SUM229PE, SUM159PT and SUM1315MO2 are triple negative breast cancer cell lines. They were sequenced to test the contrastive learning-based algorithm we developed to predict Afatinib sensitivity in TNBC.

2024-03-25 | GSE228275 | 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