Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Scalable Dual-omic Profiling with Single-nucleus Chromatin Accessibility and mRNA Expression Sequencing 2 (SNARE-seq2)

ABSTRACT: We perform benchmark experiments using cell lines to develop and assess the performance of a scalable method for generating matched RNA and chromatin accessibility profiles

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE157660 | GEO | 2020/09/09

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Scalable Dual-omic Profiling with Single-nucleus Chromatin Accessibility and mRNA Expression Sequencing 2 (SNARE-seq2)

Project description:Scalable Dual-omic Profiling with Single-nucleus Chromatin Accessibility and mRNA Expression Sequencing 2 (SNARE-seq2)

| PRJNA662341 | ENA

Benchmarking Single-Cell RNA Sequencing Protocols for Cell Atlas Projects (QUARTZ-Seq2)

Project description:Single-cell RNA sequencing (scRNA-seq) is the leading technique for charting the molecular properties of individual cells. The latest methods are scalable to thousands of cells, enabling in- depth characterization of sample composition without prior knowledge. However, there are important differences between scRNA-seq techniques, and it remains unclear which are the most suitable protocols for drawing cell atlases of tissues, organs and organisms. We have generated benchmark datasets to systematically evaluate techniques in terms of their power to comprehensively describe cell types and states. We performed a multi-center study comparing 13 commonly used single-cell and single-nucleus RNA-seq protocols using a highly heterogeneous reference sample resource. Comparative and integrative analysis at cell type and state level revealed marked differences in protocol performance, highlighting a series of key features for cell atlas projects. These should be considered when defining guidelines and standards for international consortia, such as the Human Cell Atlas project.

2019-12-10 | GSE133543 | GEO

Benchmarking Single-Cell RNA Sequencing Protocols for Cell Atlas Projects (CEL-Seq2)

2019-12-10 | GSE133539 | GEO

Scalable pooled CRISPR screens with single cell chromatin accessibility profiling.

Project description:A scalable, cost-effective method that combines CRISPR perturbations with a single-cell indexing assay for transposase-accessible chromatin (CRISPR-sciATAC). This method links genome-wide chromatin accessibility to genetic perturbations through simultaneous capture of ATAC-seq fragments and CRISPR guide RNAs from single cells using a 96-well plate combinatorial indexing approach.

2020-11-07 | GSE161002 | GEO

An atlas of healthy and injured cell states and niches in the human kidney [SNARE-Seq2]

Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.

2022-10-10 | GSE183273 | GEO

Performance of a highly scalable and extraction-free RNA-seq method

Project description:Performance of a highly scalable and extraction-free RNA-seq method

| PRJNA691505 | ENA

A Scalable Epitope Tagging Approach for High Throughput ChIP-seq Analysis

Project description:A Scalable Epitope Tagging Approach for High Throughput ChIP-seq Analysis ChIP-seq comparison between CRISPR editing cells using epitope antibody and non-editing cells using endogeneous TF antibody

2016-09-01 | E-GEOD-78064 | biostudies-arrayexpress

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

Miniaturization of Smart-seq2 for Single-Cell and Single-Nucleus RNA Sequencing.

Project description:This protocol presents a plate-based workflow to perform RNA sequencing analysis of single cells/nuclei using Smart-seq2. We describe (1) the dissociation procedures for cell/nucleus isolation from the mouse brain and human organoids, (2) the flow sorting of single cells/nuclei into 384-well plates, and (3) the preparation of libraries following miniaturization of the Smart-seq2 protocol using a liquid-handling robot. This pipeline allows for the reliable, high-throughput, and cost-effective preparation of mouse and human samples for full-length deep single-cell/nucleus RNA sequencing. For complete details on the use and execution of this protocol, please refer to Bowers et al. (2020).

| S-EPMC7501729 | biostudies-literature

Single-nucleus RNA-seq2 reveals functional crosstalk between liver zonation and ploidy.

Project description:Single-cell RNA-seq reveals the role of pathogenic cell populations in development and progression of chronic diseases. In order to expand our knowledge on cellular heterogeneity, we have developed a single-nucleus RNA-seq2 method tailored for the comprehensive analysis of the nuclear transcriptome from frozen tissues, allowing the dissection of all cell types present in the liver, regardless of cell size or cellular fragility. We use this approach to characterize the transcriptional profile of individual hepatocytes with different levels of ploidy, and have discovered that ploidy states are associated with different metabolic potential, and gene expression in tetraploid mononucleated hepatocytes is conditioned by their position within the hepatic lobule. Our work reveals a remarkable crosstalk between gene dosage and spatial distribution of hepatocytes.

| S-EPMC8275628 | biostudies-literature

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