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152
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ShareScore release 0.9.0
Dataset results
152 results for “Single-cell multiome”
Data for "A unified model-based framework for doublet or multiplet detection in single-cell multiomics data"
<p>This repository contains all the data necessary for replicating the COMPOSITE multiplet detection results featured in our manuscript, 'A Unified Model-Based Framework for Doublet or Multiplet Detection in Single-Cell Multiomics Data'. The data are ready to be directly used as input for the COMPOSITE cloud-based application or the Python package 'sccomposite' to replicate the results.</p>
Single-cell multiome uncovers differences in glycogen metabolism underlying species-specific speed of development [scRNAseq and scATACseq]
GEO Series GSE276058. Homo sapiens; Mus musculus; Macaca fascicularis. 6 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Spatial and Single-cell Transcriptomic Characterization of WIF1-induced Normal-tension Glaucoma [Single Cell Multiome ATAC + Gene Expression]
GEO Series GSE293381. Mus musculus. 6 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
A single-cell atlas of gene expression and chromatin accessibility changes associated with cocaine addiction in the rat amygdala (snATAC-Seq Multiome)
GEO Series GSE235317. Rattus norvegicus. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Comparative single-cell multiomic analysis reveals evolutionarily conserved and species-specific cellular mechanisms mediating natural retinal aging
GEO Series GSE307031. Mus musculus. 6 samples. Type: Other.
Single-cell multiomics study of cell-type-specific neuron activation unravels context-dependent gene regulation of brain disorders [030]
GEO Series GSE289522. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Single-cell multiomics study of cell-type-specific neuron activation unravels context-dependent gene regulation of brain disorders [024]
GEO Series GSE289515. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
A single-cell atlas of gene expression and chromatin accessibility changes associated with cocaine addiction in the rat amygdala (snRNA-Seq Multiome)
GEO Series GSE235314. Rattus norvegicus. 2 samples. Type: Expression profiling by high throughput sequencing.
Single-cell multiomics study of cell-type-specific neuron activation unravels context-dependent gene regulation of brain disorders [022]
GEO Series GSE289956. Homo sapiens. 30 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Single-cell multiomics study of cell-type-specific neuron activation unravels context-dependent gene regulation of brain disorders [029]
GEO Series GSE289518. Homo sapiens. 24 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Multiomic single-cell analysis of the stem and progenitor cell compartment in chronic myeloid leukemia
<p>This repository contains CITE-seq data generated from healthy and CML stem and progenitor cells using the BD Rhapsody Single-Cell Analysis System. <br> </p> <p><strong>File descriptions</strong></p> <p>RSEC-adjusted UMI count files generated using the BD Rhapsody Targeted Analysis Pipeline (v. 1.10.1):</p> <ul> <li>CartridgeS1_RSEC_MolsPerCell.csv</li> <li>CartridgeS2_RSEC_MolsPerCell.csv</li> <li>CartridgeS3_RSEC_MolsPerCell.csv</li> <li>CartridgeS4_RSEC_MolsPerCell.csv</li> <li>CartridgeS5_RSEC_MolsPerCell.csv</li> </ul> <p>RSEC-adjusted UMI counts for cells remaining after cell quality filtering using SeqGeq software (genes expressed vs library size):</p> <ul> <li>CartridgeS1_RSEC_MolsPerCell_postQC.csv</li> <li>CartridgeS2_RSEC_MolsPerCell_postQC.csv</li> <li>CartridgeS3_RSEC_MolsPerCell_postQC.csv</li> <li>CartridgeS4_RSEC_MolsPerCell_postQC.csv</li> <li>CartridgeS5_RSEC_MolsPerCell_postQC.csv</li> </ul> <p>Sample tag (sample of origin) calls for each putative cell, output by the BD Rhapsody Targeted Analysis Pipeline (v. 1.10.1). The files also contain information on <em>BCR-ABL1</em> positivity for each individual cell, generated using our in-house optimized <em>BCR-ABL1 </em>expression detection method.</p> <ul> <li>CartridgeS1_Sample_Tag_Calls_with_BCR-ABL1.csv</li> <li>CartridgeS2_Sample_Tag_Calls_with_BCR-ABL1.csv</li> <li>CartridgeS3_Sample_Tag_Calls_with_BCR-ABL1.csv</li> <li>CartridgeS4_Sample_Tag_Calls_with_BCR-ABL1.csv</li> <li>CartridgeS5_Sample_Tag_Calls_with_BCR-ABL1.csv</li> </ul> <p>RDS file containing mRNA (RNA assay) and protein (Abseq assay) counts for all cells included in the analysis (from the RSEC-adjusted post QC UMI count files above). The sample of origin of each cell and information on <em>BCR-ABL1</em> positivity (from the sample tag call files above) are specified in the meta data.</p> <ul> <li>CITEseq_BCRABL1_postQC.rds</li> </ul>
Dataset related to article "Single-Cell and Single-Nucleus Multiomics Reveal Cardiac Endothelial Cell Heterogeneity and Novel Pathological Processes in Pressure Overload-Induced Hypertrophy"
<p>This record contains raw data related to article “<em><span>Single-Cell and Single-Nucleus Multiomics Reveal Cardiac Endothelial Cell Heterogeneity and Novel Pathological Processes in Pressure Overload-Induced Hypertrophy</span></em>"</p> <p>Endothelial cells, the most prevalent cellular population in the heart, line the internal walls of coronary and lymphatic vessels and form the endocardium and cardiac valves. The heterogeneity of cardiac endothelium poses a challenge in fully understanding endothelial states. However, to better grasp the plasticity of endothelial cell phenotypes, it's crucial to distinguish the varied responses of endothelial populations to physiological and pathological stimuli. Endothelial dysfunction plays a significant role in the development and progression of heart failure, a condition impacting millions globally. For the heart to sustain pressure-overload-induced remodelling, endothelial cells must proliferate and generate new blood vessels. When cardiomyocyte hypertrophy and angiogenesis become uncoupled, it leads to decompensated heart failure. Despite this, the molecular mechanisms governing cardiac vascularization during pathological hypertrophy remain unclear.</p> <p>Transcriptional phenotyping methods have been widely used to capture endothelial cell plasticity and heterogeneity. However, only single-cell profiling has effectively resolved distinct phenotypes. While single-cell RNA sequencing can create detailed cellular maps and cell-to-cell communication networks, it does not fully elucidate how gene regulatory programs are established or how cell states, functions, and responses are specified. To address these gaps, multimodal omics approaches have been developed, allowing for simultaneous profiling of chromatin accessibility and gene expression within the same cell.</p> <p>In our study, we aimed to characterize the transcriptional and epigenetic profiles of cardiac endothelial cells in a mouse model of pressure-overload-induced hypertrophy using multiomics bioinformatic approaches at single-cell resolution. This innovative technology enabled us to uncover the regulatory mechanisms that drive endothelial cell sub-population specifications following banding. Our resulting atlas is intended to serve as a valuable reference and resource for future studies and the development of therapeutic strategies targeting endothelial cells in cardiovascular diseases.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.