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208
datasets available to search
ShareScore release 0.9.0
Dataset results
208 results for “spatial association”
Single-cell resolution spatial analysis of antigen-presenting cancer-associated fibroblast niches [scRNA-seq]
GEO Series GSE274609. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Molecular signatures and spatial distribution of disease-associated cellular populations in early-onset Alzheimer's disease mouse brain
GEO Series GSE253570. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing; Other.
Multiomic analysis reveals conservation of cancer associated fibroblast phenotypes across species and tissue of origin [spatial trascriptomics]
GEO Series GSE212706. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Other.
Spatial genome organization is associated with nematode programmed DNA elimination
GEO Series GSE314626. Ascaris suum. 7 samples. Type: Other.
Single-cell resolution spatial analysis of antigen-presenting cancer-associated fibroblast niches [Xenium PM]
GEO Series GSE274623. Homo sapiens. 8 samples. Type: Other.
Data associated with Spatial predictors of immunotherapy response in triple negative breast cancer
<p>This dataset contains all the IMC data associated with Wang <em>et al</em>. <em>Spatial predictors of immunotherapy response in triple negative breast cancer,</em> 2023. </p> <p>The zip file NTPublic contains:</p> <ul> <li>Raw multiplexed image data, image masks (cell, nuclear, epithelial, vessel), spillover matrix for signal compensation, antibody panel information, clinical data</li> <li>Processed single-cell data</li> <li>Code for analysis and creating plots</li> </ul> <p><strong>Please read the accompanying DataGuide.pdf for folder structure guide and information on both the raw and processed data.</strong></p> <p>Please read the accompanying CodeGuide.pdf to reproduce published figures. </p>
Spatial Transcriptomics Reveals Spatially Diverse Cancer-Associated Fibroblast in Lung Squamous Cell Carcinoma Linked to Tumor Progression
<p><span><span>While cancer-associated fibroblasts (CAFs) are crucial in influencing tumor growth and immune responses in lung cancer, we still lack a comprehensive understanding of their spatial organization associated with tumor progression and clinical outcomes. This gap highlights the need to elucidate how the intricate spatial arrangement of CAFs affects their interactions within the tumor microenvironment, ultimately shaping cancer progression and patient prognosis. Here, we unveil the spatial diversity of CAFs in lung squamous cell carcinoma (LUSC), a prevalent and aggressive lung cancer type, elucidating their impact on tumor progression and patient outcomes using spatial transcriptomics (ST). Image-based ST data from 33 LUSC patients demonstrated a significant association of spatial interactions of tumor epithelium and CAFs with tumor size and metabolic activity measured by [<sup>18</sup>F]fluorodeoxyglucose PET. Furthermore, the proximity of fibroblasts to tumor epithelial cells was linked to recurrence-free survival in LUSC patients. By characterizing CAFs based on their spatial relationship, we identified distinct molecular signatures related to spatially distinct fibroblast subpopulations. In addition, barcode-based ST data from 8 LUSC patients revealed spatially overlapping fibroblast regions characterized by upregulated glycolysis pathways. </span></span><span><span><span><span>Our study underscores the importance of the complex spatial dynamics of the tumor microenvironment revealed by ST and its implications for patient outcomes in LUSC.</span></span></span></span></p>
Data from: Specialization patterns in symbiotic associations: a community perspective over spatial scales.
<p><strong>Nostoc_rbcLX_alignment: </strong>Alignment of Nostoc rbcLX sequences in FASTA format. </p> <p><strong>Name_equivalences: </strong>Excel cointaining mycociont species names, abbreviations, alignment code for each sample used in the aligment, forest and Nostoc phylogroup.</p> <p><strong>Abstract:</strong> </p> <ol> <li>Specialization, contextualized in a resource axis of an organism niche, is a core concept in ecology. In biotic interactions, specialization can be determined by the range of interacting partners. Evolutionary and ecological factors, in combination with the surveyed scale (spatial, temporal, biological and/or taxonomic) influence the conception of specialization.</li> <li>This study aimed to assess the specialization patterns and drivers in the lichen symbiosis, considering the interaction between the principal fungus (mycobiont) and the associated <em>Nostoc</em> (cyanobiont), from a community perspective considering different spatial scales. Thus, we determined <em>Nostoc</em> phylogroup richness and composition of lichen communities in eleven <em>Nothofagus pumilio</em> forests across a wide latitudinal gradient in Chile. To measure specialization, cyanobiont richness, Simpson’s, and d’ indices were estimated for 37 mycobiont species in these communities. Potential drivers that might shape <em>Nostoc</em> composition and specialization measures along the environmental gradient were analysed. Limitations in lichen distributional ranges due to the availability of their cyanobionts were studied. Turnover patterns of cyanobionts were identified at multiple spatial scales.</li> <li>The results showed that environmental factors shaped the <em>Nostoc</em> composition of these communities, thus limiting cyanobiont availability to establish the symbiotic association. Besides, specialization changed with the spatial scale and with the metric considered. Cyanolichens were more specialized than cephalolichens when considering partner richness and Simpson’s index, whereas the d’ index was mostly explained by mycobiont identity. Little evidence of lichen distributional ranges due to the distribution of their cyanobionts was found. Thus, lichens with broad distributional ranges either associated with several cyanobionts or with widely distributed cyanobionts. Comparisons between local vs. regional scales showed a decreasing degree of specialization at larger scales due to an increase in cyanobiont richness.</li> <li><em>Synthesis</em>. The results support the context dependency of specialization and how its consideration changes with the metric and the spatial scale considered. Subsequently, we suggest considering the entire community, and widening the spatial scale studied as it is crucial to understand factors determining specialization.</li> </ol>
ScienceDex guides
Understand access before you commit
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.