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1,353 results for “single-cell transcriptomics”
Single-cell transcriptomics identifies synergistic role of leukemic and non-leukemic immune repertoires in CD8+ T-cell Large Granular Lymphocytic Leukemia
<p>Data to reproduce findings in the manuscript "Single-cell transcriptomics identifies synergistic role of leukemic and non-leukemic immune repertoires in CD8+ T-cell Large Granular Lymphocytic Leukemia". <br> <br> The folder contains:</p> <p>1) Processed scRNA+TCRab-seq data in a Seurat-folder, including </p> <p>* Object with 11 T-LGLL samples and 6 healthy samples<br> * Object with only hyperexpanded (>= 10 TCRs) T-cells from all T-LGLL samples and 6 healthy samples<br> * Object with only T-LGLL clones from 11 T-LGLL samples<br> * Object with non-leukemic repertoires from 11 T-LGLL samples, 6 healthy samples, 4 CML samples, 4 CLL samples, 2 RCC samples, and 1 NSCLC sample</p> <p><br> 2) TCRb-seq samples from CD8+ sorted peripheral blood samples from patients with CD8+ T-LGLL </p> <p>Please see manuscript and Github for further details.</p>
Mapping the human hematopoietic stem and progenitor cell hierarchy through integrated single-cell proteomics and transcriptomics
Open the record for dataset details and reuse information.
Supplementary processed data for Chandler et al. Single-cell transcriptomics identifies aberrant glomerular angiogenic signalling in the early stages of a murine model of WT1 kidney disease
<p><strong><em>Summary datafiles for Chandler et al.</em></strong></p> <ul> <li>Processed single-cell RNA sequencing data, derived from murine glomeruli (isolated using the dynabead technique) from <em>n = 2</em> wild-type <em>Wt1<sup>+/+</sup></em> (Ctrl) and <em>n = 2</em> mutant <em>Wt1<sup>R394W/+</sup></em> (Mut) littermates of WT1 glomerulopathy, followed by 10x Genomics Chromium v3 platform.</li> <li>Please refer to associated scripts for analysis of the data: <a href="https://github.com/daniyal-jafree1995/collaborations/blob/main/Chandleretal_2022_WT1glomerulopathyscRNAseq.R">https://github.com/daniyal-jafree1995/collaborations/blob/main/Chandleretal_2022_WT1glomerulopathyscRNAseq.R</a> </li> <li>File descriptions as below: <ul> <li>barcodes.tsv.gz - barcodes file required for input to Read10X function in Seurat</li> <li>features.tsv.gz - features file required for input to Read10X function in Seurat</li> <li>matrix.mtx.gz - matrix file required for input to Read10X function in Seurat</li> <li>WT1_scRNAseq.rds - RDS file containing processed and annotated Seurat object for downstream analysis</li> </ul> </li> </ul>
Uncovering prognostic architecture of response to immunotherapy in H. pylori infection associated gastric cancer by single-cell transcriptomic analysis
<p>Most gastric cancer (GC) worldwide is ascribed to<em> Helicobacter pylori </em>(<em>H. pylori</em>) infection, which have a detrimental effect on the immunotherapy efficacy, while the key cell players and molecular mechanism associated with GC immunotherapies were rarely described. Herein, we performed comprehensive single-cell-transcriptome analysis of nine GC with current<em> H. pylori</em>-infection (HpGC), three GC with previous <em>H. pylori</em>-infection (ex-HpGC), six GC without <em>H. pylori</em>-infection (non-HpGC), and six healthy controls (HC). HpGC and ex-HpGC were enriched with VEGFA+ angiogenic-tumor-associated-macrophages (Angio-TAM) and IL11/IL24+ inflammatory CAF (iCAF), importantly, iCAFs promoted tumor angiogenesis and immune suppression by interacting with Angio-TAM through VEGFA/B-VEGFR1 and TIGIT+ suppressive T cells through NECTIN2-TIGIT pathway, which is promising target for cancer immunotherapy. Integrated analysis of scRNA and immunotherapy dataset demonstrated the iCAF abundance and angiogenic signature could predict poor GC immunotherapy outcomes. Together, our results delineated the role of <em>H. pylori</em>-infection in GC development, tumor microenvironment regulation, and immunotherapy response.</p>
Single-cell transcriptomics reveals species-dependent immune infiltration of T cells in Huntington's disease neurodegeneration
GEO Series GSE254278. Sus scrofa. 6 samples. Type: Expression profiling by high throughput sequencing.
Single-cell and spatial transcriptomic atlas of pathological scars uncovers neuro-fibroblast crosstalk mechanisms across scar types
GEO Series GSE307504. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing; Other.
Single-cell transcriptomics revealed molecular vulnerability in a human midbrain-like organoid model of Parkinson's Disease [RNA-Seq]
GEO Series GSE271115. Homo sapiens. 10 samples. Type: Expression profiling by high throughput sequencing.
Single-Cell Transcriptomic Analysis of Astrocytes 12 Hours after Ischemic Stroke.
GEO Series GSE247474. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Single-cell RNA transcriptomics of hypertensive nephropathy patients
GEO Series GSE210898. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.
Integrated transcriptome and single-cell sequencing analysis identify blood-pancreas shared lncRNA biomarkers in new-onset T2DM
GEO Series GSE298690. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.
neuroendocrine control of planarian regeneration (single-cell transcriptome)
GEO Series GSE220816. Schmidtea mediterranea. 6 samples. Type: Expression profiling by high throughput sequencing.
Single-cell transcriptome analysis of EpCAM+ cells from P3.25 mouse fetal livers
GEO Series GSE96630. Mus musculus. 52 samples. Type: Expression profiling by high throughput sequencing.
Dataset related to article "Single-cell transcriptomic reveals functional heterogeneity of myeloid cells in glioma microenvironment"
<p>This record contains raw data related to article “single-cell transcriptomic reveals functional heterogeneity of myeloid cells in glioma microenvironment."</p> <p>High grade gliomas (HGG) are highly aggressive tumors with a particularly severe prognosis and an unmet medical need. HGG are characterized by a high degree of heterogeneity due to genetic and metabolic driving forces, either within and between individual patients. Temporal and spatial HGG heterogeneity contributes to response variability to conventional and adjuvant therapies among patients. HGG are also highly infiltrated by immune cells, tumor-associated macrophages (TAM) in particular, which are key drivers of the local immunosuppression supporting HGG progression and its resistance to immunomodulating therapeutic strategies. As the impact of HGG heterogeneity on macrophage biology remain poorly understood, we perform single-cell RNA sequencing, that reveals a large and dynamic myeloid landscape in patients with primary or secondary gliomas. To define the role in local immunosuppression and tumor progression, resident microglia and monocyte-derived macrophages are characterized, exhibiting additional heterogeneity across glioma subtypes. Understanding the immunosuppressive mechanisms operating in HGG is key to guide patients’ selection and optimize success rate of immunomodulating therapies.</p>
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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.