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11,105
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11,105 results for “single cells”
Exploring the cellular landscape of circular RNAs using full-length single-cell RNA sequencing
<p>Source data for our circSC manuscript.</p>
Single-Cell ALRA-imputed Rat Lung Data
<p>ALRA-imputed Rat Lung Data from Raredon 2019 (10.1126/sciadv.aaw3851) </p>
scPerturb Single-Cell Perturbation Data: ATAC files
<p>Secondary upload of datasets on scPerturb.org</p> <p>.zip files for ATAC-seq datasets</p>
Empirical single-cell tracking and cell-fate simulation reveal dual roles of p53 in tumor suppression
<p>The tumor suppressor p53 regulates various stress responses via increasing its cellular levels. The lowest p53 levels occur in unstressed cells; however, the impact of these low levels on cell integrity remains unclear. To address the impact, we used empirical single-cell tracking of p53-expressing and silenced cells, and developed a fate-simulation algorithm. Here we show that p53-silenced cells underwent more frequent cell death and cell fusion, which further induced multipolar cell division to generate aneuploid progeny. Those results suggest that the low levels of p53 in unstressed cells indeed have a role to maintain the integrity of a cell population. Results of a cell-fate simulation that provides a flexible and dynamic virtual culture space confirmed that these aneuploid progeny could propagate. However, p53-silenced cells were unable to propagate in a virtual cell population that was mainly comprised of p53-expressing cells, supporting the notion that p53 acts as a tumor suppressor. In contrast, when DNA damage responses were repeatedly induced in 53-expressed cells, p53-silenced cells became the major cell population, as the growth of p53-expressed cells was more tightly suppressed by the response than that of p53-silenced cells. In this context, the p53-mediated damage response that is supposed to suppress tumor formation has a pro-malignant function. The cellular microenvironment could thus be a major factor to determine the fate of cancer cells and the fate-simulation algorithm can be used to reveal the fate. </p>
Single-cell multiomics analysis reveals regulatory programs in clear cell renal cell carcinoma
<p>Here, we performed an integrative analysis of scRNA-seq and scATAC-seq data from four ccRCC patients and aimed to identify the key regulatory molecules that mediate tumor development and manipulate the function of immune cells.</p>
Single-cell resolution of the plant response to Pseudomonas syringae infection
<p>Original images for figures and quantifications. </p>
Reanalysis of Single-Cell Sequencing Data from Healthy and Periodontitis Patients: Characterization of Oral Epithelial Cells
Open the record for dataset details and reuse information.
CrossMP: Enabling Cross-Modality Translation between Single-Cell RNA-Seq and Single-Cell ATAC-Seq through Web-Based Portal - Appendix
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Datasets for the paper "Regulation of endocrine cell alternative splicing revealed by single-cell RNA sequencing in type 2 diabetes pathogenesis."
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Multimodal single-cell analyses reveal distinct fusion-regulated transcriptional programs in Ewing sarcoma.
<p>All processed data for analysis at <a href="https://github.com/furlan-lab/EwS_multiome">https://github.com/furlan-lab/EwS_multiome</a></p>
RNA velocity analysis of the integrated single cell atlas of neural crest lineages along the posterior developing zebrafish
<p>H5AD files of an RNA velocity analysis of the integrated single cell atlas of neural crest lineages along the posterior developing zebrafish . For this, we have used Velocyto and scVelo. The notebooks to reproduce the scVelo part are here https://github.com/brunicardoso/e-signal-lab/blob/main/scvelo_sox10_integration48_68h__Uribe_using_original_seurat_metadata.ipynb .</p> <p>This analysis was based on data published here https://elifesciences.org/articles/60005</p>
Imada Fasting Cancer - single cell RNA-Seq Processed Data R object
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Inferring clonal somatic mutations directed by X chromosome inactivation status in single cells
<p>This repository contains large files for the reproduction of results described in the manuscript <strong>Inferring clonal somatic mutations directed by X chromosome inactivation status in single cells</strong>.</p>
Label-Free Differentiation of Living versus Dead Single Yeast Cells using Broadband Electrical Impedance Spectroscopy
<p>Data to support manuscript.</p>
Single-cell molecular and spatial characterization of plasmablast-like tumors in primary central nervous system lymphoma
<p><span>We delineate intratumor heterogeneity and immune contexture of lymphoma microenvironment in PCNSL through the integration of single cell sequencing and spatial transcriptomics. These dataset contains droplet-based single cell data and GeoMx Digital Spatial Profiler data. This repository also contains the analysis R scripts.</span></p>
Single Cell Analysis of the Pathogenesis of Pediatric Nephrotic Syndrome
<p>This is ScRNAseq datasets used to analyses the pathogenesis of nephrotic syndrome. </p>
AnnData set for single cell analysis tutorial
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scCDC: a computational method for gene-specific contamination detection and correction in single-cell and single-nucleus RNA-seq data
<p><span>In droplet-based single-cell and single-nucleus RNA-seq assays, systematic contamination of ambient RNA molecules biases the quantification of gene expression levels. Existing methods correct the contamination for all genes globally. However, specific evaluation for different contamination levels is lacking. Here, we show that DecontX and CellBender under-correct highly-contaminating genes, while SoupX and scAR over-correct lowly-/non-contaminating genes. Here, we develop scCDC as the first method to detect the contamination-causing genes and only correct expression levels of these genes, some of which are cell-type markers. Compared with existing decontamination methods, scCDC excels in decontaminating highly-contaminating genes while avoiding over-correction of other genes.</span></p>
Aligned Cross-modal Integration and Regulatory Heterogeneity Characterization of Single-Cell Multiomic Data with Deep Contrastive Learning
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Genomic and single-cell characterization of patient-derived tumor organoid models of head and neck squamous cell carcinoma
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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.