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23 results for “Single-cell biology”
# Single-cell network biology characterizes cell type gene regulation for drug repurposing and phenotype prediction in Alzheimer's disease
<p>Dysregulation of gene expression in Alzheimer’s disease (AD) remains elusive, especially at the cell type level. Gene regulatory network, a key molecular mechanism linking transcription factors (TFs) and regulatory elements to govern target gene expression, can change across cell types in the human brain and thus serve as a model for studying gene dysregulation in AD. However, it is still challenging to understand how cell type networks work abnormally under AD. To address this, we integrated single-cell multi-omics data and predicted the gene regulatory networks in AD and control for four major cell types, excitatory and inhibitory neurons, microglia and oligodendrocytes. Importantly, we applied network biology approaches to analyze the changes of network characteristics across these cell types, and between AD and control. For instance, many hub TFs target different genes between AD and control (rewiring). Also, these networks show strong hierarchical structures in which top TFs (master regulators) are largely common across cell types, whereas different TFs operate at the middle levels in some cell types (e.g., microglia). The regulatory logics of enriched network motifs (e.g., feed-forward loops) further uncover cell type-specific TF-TF cooperativities in gene regulation. The cell type networks are highly modular and several network modules with cell-type-specific expression changes in AD pathology are enriched with AD-risk genes and putative targets of approved and pending AD drugs, suggesting possible cell-type genomic medicine in AD. Finally, using the cell type gene regulatory networks, we developed machine learning models to classify and prioritize additional AD genes. We found that top prioritized genes predict clinical phenotypes (e.g., cognitive impairment) with reasonable accuracy. Overall, this single-cell network biology analysis provides a comprehensive map linking genes, regulatory networks, cell types and drug targets and reveals dysregulated cell type gene dysregulatory mechanisms in AD.</p>
Single-cell and single-nucleus RNA-sequencing from paired normal-adenocarcinoma lung samples provides both common and discordant biological insights
<p>The datasets generated by <em>Cellranger </em>for all 24 samples (.h5 format).<br><br></p>
Prioritization of cell types responsive to biological perturbations in single-cell data with Augur
<p>Processed and analysis-ready input data discussed in our Augur procedures.</p>
Extended data for "The need to reassess single-cell RNA sequencing datasets: the importance of biological sample processing"
<p>Extended data for "The need to reassess single-cell RNA sequencing datasets: the importance of biological sample processing"</p>
DELVE: Feature selection for preserving biological trajectories in single-cell data
<p>Contains preprocessed single-cell data and metadata for feature selection. Preprocessed adata objects can be accessed using the <em>read_h5ad</em> function in anndata. Also contains the source data files for reproducing the Figures and Supplementary Figures referenced in the manuscript.</p> <ul> <li>The RPE iterative indirect immunofluorescence imaging dataset (adata_RPE.h5ad) from Ref. (<a href="https://doi.org/10.1016/j.cels.2021.10.007">https://doi.org/10.1016/j.cels.2021.10.007</a>) was originally downloaded from the Zenodo repository (<a href="https://doi.org/10.5281/zenodo.4525425">https://doi.org/10.5281/zenodo.4525425</a>).</li> <li>The PDAC iterative indirect immunofluorescence imaging datasets (listed below) were originally downloaded from the Zenodo repository (<a href="https://doi.org/10.5281/zenodo.7860332">https://doi.org/10.5281/zenodo.7860332</a>). <ul> <li>adata_PDAC_BxPC3_control.h5ad</li> <li>adata_PDAC_CFPAC_control.h5ad</li> <li>adata_PDAC_HPAC_control.h5ad</li> <li>adata_PDAC_MiaPaCa_control.h5ad</li> <li>adata_PDAC_Pa01C_control.h5ad</li> <li>adata_PDAC_Pa02C_control.h5ad</li> <li>adata_PDAC_Pa16C_control.h5ad</li> <li>adata_PDAC_PANC1_control.h5ad</li> <li>adata_PDAC_UM53_control.h5ad</li> </ul> </li> <li>The CD8+ T cell differentiation dataset (adata_CD8.h5ad) from Ref. (<a href="https://doi.org/10.1016/j.cels.2021.10.007">https://doi.org/</a><a href="https://doi.org/10.1126/sciimmunol.aaz6894">10.1126/sciimmunol.aaz6894</a>) was originally downloaded from the Gene Expression Omnibus under the accession code GSE131847 (<a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138266">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE131847</a>).</li> <li>The definitive endoderm differentiation dataset (adata_DE.h5ad) contains multiplexed single-cell RNA sequencing data profiling the differentiation of human embryonic stem cells into the definitive endoderm. </li> </ul>
Supporting data for "Studying stochastic systems biology of the cell with single-cell genomics data"
<p>The dataset tar.gz files contain the raw unspliced and spliced count matrices generated by <em>kallisto</em>|<em>bustools</em> 0.26.0 from six datasets.</p> <p>The GVP_2023...zip file is a mirror of the related GitHub repository.</p>
Differential analysis of binarized single-cell RNA sequencing data captures biological variation
<p>Processed datasets used for binary differential analysis experiments.</p>
Integration of single-cell transcriptomes and biological function reveals distinct behavioral patterns in bone marrow endothelial cells [bulk RNA-seq]
GEO Series GSE206975. Mus musculus. 15 samples. Type: Expression profiling by high throughput sequencing.
Insights into the Biology of Hearing and Deafness Revealed by Single-Cell RNA Sequencing
GEO Series GSE114157. Mus musculus. 144 samples. Type: Expression profiling by high throughput sequencing.
EPICARDIOID SINGLE-CELL GENOMICS UNCOVER PRINCIPLES OF HUMAN EPICARDIUM BIOLOGY IN HEART DEVELOPMENT AND DISEASE [scRNA-Seq]
GEO Series GSE196513. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing.
Integration of single-cell transcriptomes and biological function reveals distinct behavioral patterns in bone marrow endothelial cells [scRNA-Seq]
GEO Series GSE206976. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Engineered cell entry links receptor biology with single-cell genomics
GEO Series GSE212998. Homo sapiens. 31 samples. Type: Expression profiling by high throughput sequencing.
Integration of single-cell transcriptomes and biological function reveals distinct behavioral patterns in bone marrow endothelial cells
GEO Series GSE206977. Mus musculus. 19 samples. Type: Expression profiling by high throughput sequencing.
Differences in cell subsets between sun-exposed and unexposed skin: preliminary single-cell sequencing and biological analysis from a single case
GEO Series GSE275491. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing.
Remarkable Lung Heterogeneity at Single-Cell Resolution and the Role of Sex as a Biological Variable in Neonatal Hyperoxic Lung Injury
GEO Series GSE211356. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models [iPSC-derived neurons]
GEO Series GSE157835. Homo sapiens. 752 samples. Type: Expression profiling by high throughput sequencing.
Liver Single-Cell Transcriptome Analysis of Cell-specific Dysregulation of Liver Cell Biology Following Intravenous Administration of AAV Vectors
GEO Series GSE124560. Mus musculus. 9 samples. Type: Expression profiling by high throughput sequencing.
Engineered cell entry links receptor biology with single-cell genomics [scRNA-Seq]
GEO Series GSE212996. Homo sapiens. 27 samples. Type: Expression profiling by high throughput sequencing.
SECANT: a biology-guided semi-supervised method for clustering, classification, and annotation of single-cell multi-omics
GEO Series GSE168264. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing; Other.
Engineered cell entry links receptor biology with single-cell genomics [bulk RNA-Seq]
GEO Series GSE212984. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
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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.