Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Designing a single cell ATAC-Seq (scATAC-Seq) dataset to validate long read RNA-Seq isoforms and benchmark scATAC-Seq analysis methods II

ABSTRACT: Designing a single cell ATAC-Seq (scATAC-Seq) dataset to validate long read RNA-Seq isoforms and benchmark scATAC-Seq analysis methods II

PROVIDER: PRJNA929481 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Designing a single cell ATAC-Seq (scATAC-Seq) dataset to validate long read RNA-Seq isoforms and benchmark scATAC-Seq analysis methods

Project description:Designing a single cell ATAC-Seq (scATAC-Seq) dataset to validate long read RNA-Seq isoforms and benchmark scATAC-Seq analysis methods

| PRJNA596466 | ENA

Designing a single cell ATAC-Seq (scATAC-Seq) dataset to benchmark scATAC-Seq analysis methods

Project description:Designing a single cell ATAC-Seq (scATAC-Seq) dataset to benchmark scATAC-Seq analysis methods

| PRJNA925800 | ENA

Designing a single cell ATAC-Seq (scATAC-Seq) dataset to validate long read RNA-Seq isoforms and benchmark scATAC-Seq analysis methods

Project description:Single cell sequencing technology has been widely used for understanding the heterogeneity of complex tissue and for identifying novel cell types or cell states. Previous efforts of single cell profiling are mostly performed by measuring transcriptomes using single cell RNA sequencing (scRNA-seq). scRNA-seq is relatively well developed and around 500 analysis tools are currently available for performing different tasks. In the past five years, assays for profiling the single cell chromatin accessibility landscape have emerged and provide extra information about gene regulation at the epigenetic level. Due to its simplicity and sensitivity, single cell Assays for Transposase-Accessible Chromatin using sequencing (scATAC-seq) is widely used to obtain chromatin accessibility. This data will be used to comprehensively evaluate scATAC-seq data analysis tools and gaps in analysis workflows together with publicly available bulk ATAC-Seq and scATAC-seq data using optimised universal evaluation metrics. Furthermore, this data will be used to validate novel isoforms identified from long-read scRNA-Seq study.

2019-12-19 | GSE142285 | GEO

Designing a single cell ATAC-Seq (scATAC-Seq) dataset to validate long read RNA-Seq isoforms and benchmark scATAC-Seq analysis methods II

2023-09-14 | GSE224045 | GEO

Designing a single cell ATAC-Seq (scATAC-Seq) dataset to benchmark scATAC-Seq analysis methods

2024-01-10 | GSE223319 | GEO

Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods (Drop-Seq)

Project description:Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods (Drop-Seq)

| PRJNA486516 | ENA

Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods (RNAmix_Sort-seq)

Project description:Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods (RNAmix_Sort-seq)

| PRJNA482660 | ENA

Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods

Project description:Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods

| PRJNA486769 | ENA

Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods

Project description:Designing a single cell RNA sequencing benchmark dataset to compare protocols and analysis methods

| PRJNA596465 | ENA

scATAC-seq of mouse Plasmodium-specific CD4+ T cells

Project description:Plasmodium-specific CD4+ T cells from mice infected with Plasmodium chabaudi chabaudi AS parasites were recovered at Days 0, 4, 7, and 32 to undergo processing and to generate scATAC-seq dataset. At Day 7, CXCR5+ and CXCR6+ cells were recovered separately. At Day 32, mice were administered with either saline or artesunate (intermittent artesunate therapy - IAT). scATAC-seq dataset was analysed to investigate epigenomic landscapes of CD4+ T cells from effector to memory states.

2020-10-14 | E-MTAB-9402 | 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