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1,353 results for “single-cell transcriptomics”
Deciphering Precursor Cell Dynamics in Esophageal Preneoplasia via Genetic Barcoding and Single-Cell Transcriptomics
GEO Series GSE304762. Mus musculus. 2 samples. Type: Other.
Single-cell transcriptome and TCR repertoire sequencing of cholinergic CD4+ T cells in liver cancer
GEO Series GSE231322. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing; Other.
Single-cell transcriptomic analysis of mouse lung CD11b+ dendritic cells post allergic sensitization
GEO Series GSE156527. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Cytosplore-Transcriptomics: a scalable inter-active framework for single-cell RNA sequenc-ing data analysis
<p>Allen institute 10X mouse data (<a href="https://portal.brain-map.org/atlases-and-data/rnaseq/mouse-whole-cortex-and-hippocampus-10x">https://portal.brain-map.org/atlases-and-data/rnaseq/mouse-whole-cortex-and-hippocampus-10x</a>) converted into h5 format including metadata, to be easily uploaded in Cytosplore-Transcriptomics.</p>
Integrative analysis of spatial and single-cell transcriptome data from human pancreatic cancer reveals an intermediate cancer cell population associated with poor prognosis_Spatial H&E images
<p>High-resolution H&E images of spatial transcriptome data</p>
Cross-species imputation and comparison of single-cell transcriptomic profiles
Open the record for dataset details and reuse information.
devCellPy is a machine learning-enabled pipeline for automated annotation of complex multilayered single-cell transcriptomic data
<p>A major informatic challenge in single cell RNA-sequencing analysis is the precise annotation of datasets where cells exhibit complex multilayered identities or transitory states. Here, we present <em>devCellPy</em> a highly accurate and precise machine learning-enabled tool that enables automated prediction of cell types across complex annotation hierarchies. To demonstrate the power of <em>devCellPy</em>, we construct a murine cardiac developmental atlas from published datasets encompassing 104,199 cells from E6.5-E16.5 and train <em>devCellPy</em> to generate a cardiac prediction algorithm. Using this algorithm, we observe a high prediction accuracy (>90%) across multiple layers of annotation and across de novo murine developmental data. Furthermore, we conduct a cross-species prediction of cardiomyocyte subtypes from in vitro<em>-</em>derived human induced pluripotent stem cells and unexpectedly uncover a predominance of left ventricular (LV) identity that we confirmed by an LV-specific TBX5 lineage tracing system. Together, our results show devCellPy to be a useful tool for automated cell prediction across complex cellular hierarchies, species, and experimental systems.</p>
Integration of single-cell transcriptome and chromatin accessibility of early gonads development among goats, pigs, macaques, and humans
<p>The early gonads of mammals contain primordial germ cells (PGCs) and somatic cell precursors that are essential for sex determination and gametogenesis. Although it is extensively documented in mice, the development of early gonads in non-rodents remains to be delineated. Because molecular differences between mouse and human gonadal cells have been reported, it warrants the study of the key markers and regulatory features that are conserved or divergent between non-rodent species and human. Here, we integrate single-cell transcriptome and chromatin accessibility analysis to identify regulatory signatures of PGCs and somatic cells in the early gonads of goats, pigs, macaques, and humans. We identify the evolutionarily conserved and species-specific events, including genes expression, signaling pathways, and cell-cell interactions. We also uncover potential cis-regulatory elements and key transcription factors in PGCs and somatic cells. Our datasets provide important resources for better understanding the evolutionary programs of PGCs and gonadal somatic cell development in mammals.</p>
Joint analysis of single-cell RNA sequencing and bulk transcriptome reveals the heterogeneity of the urea cycle of astrocytes in glioblastoma
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Activation of Hedgehog Signaling Promotes Development of Mouse and Human Enteric Neural Crest Cells, Based on Single-Cell Transcriptome Analyses
<p>the key data in our paper "Activation of Hedgehog Signaling Promotes Development of Mouse and Human Enteric Neural Crest Cells, Based on Single-Cell Transcriptome Analyses"</p>
Mechanistic Studies of Chronic COPD Using Single-Cell Sequencing and Single-Cell Spatial Transcriptomics
ClinicalTrials.gov study NCT07208123. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Characteristics and Treatment Mechanism of Vascular Grafts in Elderly Patients With CAOD Through Single-cell Transcriptome Analysis
ClinicalTrials.gov study NCT07053254. IPD Sharing: NO. Countries: 1. Publications: 0.
Single-Cell Transcriptomics of the Peritoneal Microenvironment of Colorectal PC
ClinicalTrials.gov study NCT05676372. IPD Sharing: NO. Countries: 1. Publications: 0.
A Single-cell Transcriptome Study in Patients With Non-Hodgkin's Lymphoma
ClinicalTrials.gov study NCT04434833. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Integrative Analysis of Exosome-Mediated Single-Cell Transcriptomics and Proteomics in Gastric Cardia Cancer
ClinicalTrials.gov study NCT06702891. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Single-cell Transcriptome Identification of UV- and Visible-light-induced Genes in Human Melanocytes in Vivo
ClinicalTrials.gov study NCT05780606. IPD Sharing: NO. Countries: 1. Publications: 0.
Single-cell transcriptomic analysis of mouse pancreas: characteristic features of pancreatic ductal cells in chronic pancreatitis
GEO Series GSE204844. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Deciphering the Transcriptomic Landscape of Type 2 Diabetes: Insights from Bulk RNA Sequencing and Single-Cell Analysis [RNA-seq]
GEO Series GSE280402. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.
Single-cell transcriptome analysis of Terc KO bone marrow and brain
GEO Series GSE190535. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Single-cell and spatial transcriptomics uncovers the role of senescent vascular cells in pathological arterial remodeling during murine atherosclerosis
GEO Series GSE239602. Mus musculus. 82 samples. Type: Expression profiling by high throughput sequencing.
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.