Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ArchR: An integrative and scalable software package for single-cell chromatin accessibility analysis

ABSTRACT: The advent of large-scale single-cell chromatin accessibility profiling has accelerated our ability to map gene regulatory landscapes, but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; www.ArchRProject.com) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element to gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility, and multi-omic integration with scRNA-seq. Enabling the analysis of over 1.2 million single cells within 8 hours on a standard Unix laptop, ArchR is a comprehensive analytical suite for end-to-end analysis of single-cell chromatin accessibility data that will accelerate the understanding of gene regulation at the resolution of individual cells.

ORGANISM(S): Homo sapiens

PROVIDER: GSE162690 | GEO | 2020/12/05

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

ArchR: An integrative and scalable software package for single-cell chromatin accessibility analysis

Project description:ArchR: An integrative and scalable software package for single-cell chromatin accessibility analysis

| PRJNA682619 | ENA

PING 2.0: An R/Bioconductor package for nucleosome positioning using next-generation sequencing data

2013-07-11 | GSE47073 | GEO

PING 2.0: An R/Bioconductor package for nucleosome positioning using next-generation sequencing data

Project description:MNase-Seq and ChIP-Seq have evolved as popular techniques to study chromatin and histone modification. Although many tools have been developed to identify enriched regions, software tools for nucleosome positioning are still limited. We introduce a flexible and powerful open-source R package, PING 2.0, for nucleosome positioning using MNase-Seq data or MNase- or sonicated- ChIP-Seq data combined with either single-end or paired-end sequencing. PING uses a model-based approach, which enables nucleosome predictions even in the presence of low read counts. We illustrate PING using two paired-end datasets from Saccharomyces cerevisiae and compare its performance to nucleR and ChIPseqR. Identification of nucleosomes from two different mononucleosomes data. A yeast strain (W303 background) with the HTZ1 gene expressed a fusion with a myc epitope was used to map total and Htz1-containign nucleosome by MNase-ChIP-Seq. Cells were grown to mid-log phase and monomucleosomes were generated using MNase treatment of isolated nuclei. Especially for the sample of SC0017_61YDGAAXX_8_TCATTC, the Htz1-containing nucleosomes were enriched by immunoprecipitation using an anti-Myc antibody (3E10). DNA from both total nucleosomes and Htz1-enriched nucleosomes were purified and sequenced on an Illumina GA IIx using the by paired-end protocol.

2013-07-11 | E-GEOD-47073 | biostudies-arrayexpress

Nanowell-based single-cell combinatorial indexed ATAC-seq

Project description:Here we present advancements in single-cell combinatorial indexed ATAC-seq (sciATAC) to measure chromatin accessibility that leverage nanowell chips to achieve atlas-scale cell throughput (>105) at low cost. Our optimized techniques also achieve a high fraction of reads that fall within called peaks (>80%) and low cell doublet rates. We also demonstrate an alternative workflow that achieves high cell coverage while retaining exceptional enrichment for open chromatin regions, enabling the assessment of >70,000 unique accessible loci per cell.

2023-02-08 | GSE218881 | GEO

Transcription Factor Activity Regulating Macrophage Heterogeneity during Skin Wound Healing

Project description:We aimed to study chromatin accessibility for TF binding sites for inferring TF activity in monocytes and macrophages during skin wound healing. Monocytes and macrophages isolated from skin wounds on male C57BL6/J mice on day 3 and 6 post-injury, subjected to enzymatic digestion to obtain single cells and pooled from two mice per time point. Nuclei were processed using the 10x Chromium platform. Libraries sequenced on NovaSeq 6000 with paired-end reads. Fastq files were generated and demultiplexed into single cells using Cell Ranger software.

2024-08-14 | GSE250317 | GEO

Spatially mapped single-cell chromatin accessibility

Project description:Spatially mapped single-cell chromatin accessibility

| PRJNA692203 | ENA

AMAR-seq: automated multimodal sequencing of DNA methylation, chromatin accessibility, and RNA expression with single-cell resolution

Project description:Parallel single-cell multimodal sequencing is the most intuitive and precise tool for cellular status research. In this study, we propose AMAR-seq to automate methylation, chromatin accessibility and RNA sequencing on a chip with single-cell precision. We validated the accuracy and robustness of AMAR-seq in comparison with standard single-omics methods. The high gene detection rate and genome coverage of AMAR-seq enabled us to establish a genome-wide gene expression regulatory atlas, implement single-cell copy number variation analysis, and construct a single-gene, single-base resolution gene expression, DNA methylation, and chromatin accessibility landscape. Applying AMAR-seq to investigate the process of mouse embryonic stem cell differentiation, we revealed the dynamic coupling of the epigenome and transcriptome which may contribute to the unravelling of the molecular mechanisms of early embryonic development. Collectively, these results illustrate that the employment of AMAR-seq can deeply and accurately establish single-cell multi-omics regulatory networks in a single-cell context in a cost-efficient and automated manner, which paves the way for incisive dissection of complex life procedures.

2024-03-21 | GSE261788 | GEO

Multiplex Single Cell Profiling of Chromatin Accessibility by Combinatorial Cellular Indexing [RNA-seq]

Project description:Technical advances have enabled the collection of genome and transcriptome data sets with single-cell resolution. However, single-cell characterization of the epigenome has remained challenging. Furthermore, because cells must be physically separated prior to biochemical processing, conventional single-cell preparatory methods scale linearly. We applied combinatorial cellular indexing to measure chromatin accessibility in thousands of single cells per assay, circumventing the need for compartmentalization of individual cells. We report chromatin accessibility profiles from over 15,000 single cells and use these data to cluster cells on the basis of chromatin accessibility landscapes. We identify modules of coordinately regulated chromatin accessibility at the level of single cells both between and within cell types, with a scalable method that may accelerate progress toward a human cell atlas. 3 replicates from GM12878 and HL-60 cell lines collected for differential gene expression analysis.

2015-05-07 | E-GEOD-68102 | biostudies-arrayexpress

cinaR: A comprehensive R package for the differential analyses and interpretation of ATAC-seq data

Project description:ATAC-seq is a frequently used assay to study chromatin accessibility levels. Differential chromatin accessibility level analyses between biological groups and functional interpretation of these differential regions are essential in ATAC-seq data analyses. Although distinct methods and analyses pipelines are developed for this purpose, we are missing a stand-along R package that combines state-of-the art differential analyses and functional enrichment analyses. To fill this gap, we developed cinaR, which is a single wrapper function and provides users with various configurable plots. To show-case this pipeline we provide these bulk ATAC-seq samples from bone-marrow of 3 & 18 months old New Zelland Obese (NZO) mice and show the activation of pro-inflammatory pathways.

2021-01-20 | GSE165120 | GEO

Single-cell chromatin accessibility data using scATAC-seq

Project description:Single-cell chromatin accessibility data using scATAC-seq

| PRJNA274006 | ENA