Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

ABSTRACT: Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

PROVIDER: PRJNA832249 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR18923500.fastq.gz	Fastqsanger.gz
	SRR18923501.fastq.gz	Fastqsanger.gz
	SRR18923502.fastq.gz	Fastqsanger.gz
	SRR18923503.fastq.gz	Fastqsanger.gz
	SRR18923504.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 116

Similar Datasets

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

| PRJNA1039282 | ENA

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

| PRJNA906702 | ENA

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:We report the development of a method (nanoSPLITS) capable of performing global proteome and transcriptome measurements from the same single-cell.

2022-05-18 | GSE201575 | GEO

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:We report the development of a method (nanoSPLITS) capable of performing global proteome and transcriptome measurements from the same single-cell.

2022-12-05 | GSE219047 | GEO

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:We report the development of a method (nanoSPLITS) capable of performing global proteome and transcriptome measurements from the same single-cell.

2024-05-06 | GSE247519 | GEO

Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS

Project description:Single-cell and pooled cell proteomic data from alveolar type II epithelial cell line (C10) and axillary lymph node cell line (SVEC). Cells were sorted using cellenONE onto several nanoSPLITS chips. Cell lysates were then split for parallel RNAseq and proteomic analysis. For the proteomic sample prep all steps utilized the nanoPOTS sample handling robot. Lysates were reduced, treated with IAA, digested overnight with trypsin/Lys-C at 37C, and vacuum dried / stored at -20C. LC-MS/MS data was acquired using TIFF DDA methodology on a Thermo Tribrid mass spectrometer. Data was searched using FragPipe version 17.1 before downstream analysis in R.

2022-04-19 | MSV000089280 | MassIVE

Integrated analysis of multimodal single-cell data

Project description:The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single-cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce ‘weighted-nearest neighbor’ analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity.

2021-01-15 | GSE164378 | GEO

Simultaneous trimodal single cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq

Project description:Single-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to signals, and human disease. Recent advances have allowed paired capture of protein abundance and transcriptomic state, but a lack of epigenetic information in these assays has left a missing link to gene regulation. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases signal-to-noise and allows paired measurement of cell surface markers and chromatin accessibility: Integrated Cellular Indexing of Chromatin Landscape and Epitopes (ICICLE-seq). We extended this approach using a droplet-based multiomics platform to develop a trimodal assay that simultaneously measures Transcriptomics (scRNA-seq), Epitopes, and chromatin Accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.

2021-04-02 | GSE158013 | GEO

Measurement of variant surface glycoprotein mRNA using RNAseq

Project description:Measurement of variant surface glycoprotein mRNA using RNAseq

| PRJEB38469 | ENA

Multimodal measurement of the transcriptome and proteome in G2/M arrested single cells using nanoSPLITS

Project description:Single-cell proteomic data from RO-3306 treated alveolar type II epithelial cells (C10) and untreated C10 cells. Cells were sorted using cellenONE onto several nanoSPLITS chips. Cell lysates were then split for parallel RNAseq and proteomic analysis. For proteomics recovery experiment where both chips were analyzed by proteomics, 10 C10 cells were pooled onto a single cell before splitting. For the proteomic sample prep all steps utilized the nanoPOTS sample handling robot. Lysates were reduced, treated with IAA, digested overnight with trypsin/Lys-C at 37C, and vacuum dried / stored at -20C. LC-MS/MS data was acquired using TIFF DDA methodology on a Thermo Tribrid mass spectrometer. Data was searched using FragPipe version 18.0 before downstream analysis in R.

2022-12-02 | MSV000090828 | MassIVE

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