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31
datasets available to search
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Dataset results
31 results for “cell-cell communication”
Inferring causal cell-cell communication from single-cell transcriptomics
<p>Data used to produce the analysis in "Inferring causal cell-cell communication from single-cell transcriptomics" by Almet and Nie (2022)</p>
Data for Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points
<p>processed_data.tar.gz contains all files from the data directory associated with the 230418_TS_AgingCCC GitHub project and includes the following:</p> <ul> <li> <p>CellRangerCounts/</p> </li> <ul> <li> <p>post_soupX/ : contains 12 directories for 12 samples, which each contain 3 files obtained from ambient RNA removal with soupX. Below is a representative example, but the post_soupX directory contains one directory for each of the 12 samples:</p> </li> <ul> <li> <p>S01_6m_AD/</p> </li> <ul> <li> <p>barcodes.tsv</p> </li> <li> <p>genes.tsv</p> </li> <li> <p>matrix.mtx</p> </li> </ul> </ul> <li> <p>pre_soupX/ : contains 12 directories for 12 samples, which each contain 2 files obtained from Cell Ranger after aligning fastq files to the reference genome. Below is a representative example, but this directory contains 1 directory for each individual sample:</p> </li> <ul> <li> <p>S01_6m_AD/outs/</p> </li> <ul> <li> <p>filtered_feature_ bc_matrix.h5</p> </li> <li> <p>raw_feature_bc_matrix.h5 </p> </li> </ul> </ul> </ul> <li> <p>PANDA_inputs/</p> </li> <ul> <li> <p>PANDA_exp_files_array.txt: Text files with files paths to expression inputs for PANDA gene regulatory networks.</p> </li> <li> <p>mm10_TFmotifs.txt: Mouse TF motif input for PANDA gene regulatory networks. Previously published in Whitlock et al. 2023 </p> </li> <li> <p>mm10_ppi.txt: Mouse protein-protein interaction information from SringDB input for PANDA gene regulatory networks. Previously published in Whitlock et al. 2023 </p> </li> </ul> <li> <p>ccc/</p> </li> <ul> <li> <p>nichenet_v2_prior/</p> </li> <ul> <li> <p>gr_network_mouse_21122021.rds : accessed in December 2023, gene regulation network – gene regulatory information from MultiNicheNet</p> </li> <li> <p>ligand_target_matrix_nsga2r_final_mouse.rds: accessed in December 2023, ligand target matrix for mouse from MultiNicheNet.</p> </li> <li> <p>ligand_tf_matrix_nsga2r_final_mouse.rds: accessed in December 2023, mouse ligand tf matrix for signaling path determination from MultiNicheNet</p> </li> <li> <p>lr_network_mouse_21122021.rds : accessed in December 2023, ligand-receptor matrix from MultiNicheNet</p> </li> <li> <p>signaling_network_mouse_21122021.rds : accessed in December 2023, signaling network – protein-protein interaction information from MultiNicheNet for mouse</p> </li> <li> <p>weighted_networks_nsga2r_final_mouse.rds : accessed in October 2023, networks weighted by literature evidence from MultiNicheNet for mouse</p> </li> </ul> <li> <p>multinichenet_output.rds : MultiNicheNet output for 3xTg-AD snRNA-seq data</p> </li> <li> <p>12m_signaling_igraph_objects.rds : list of igraph objects for 93 LRTs and their signaling mediators at 12 months</p> </li> <li> <p>6m_signaling_igraph_objects.rds :list of igraph objects for 2 LRTs and their signaling mediators at 6 months</p> </li> </ul> <li> <p>elisa/: CSV files of measured OD values for every ELISA.</p> </li> <ul> <li> <p>240319_ELISA_Ab40.csv: OD measurements for Ab40</p> </li> <li> <p>240319_ELISA_Ab42.csv: OD measurements for Ab42</p> </li> <li> <p>240319_ELISA_total_tau.csv: OD measurements for Total Tau</p> </li> </ul> <li> <p>panda/: PANDA gene regulatory networks for each time point and condition in excitatory and inhibitory neurons. Used for differential gene targeting.</p> </li> <ul> <li> <p>excitatory_neurons_AD12.Rdata</p> </li> <li> <p>excitatory_neurons_AD6.Rdata</p> </li> <li> <p>excitatory_neurons_WT12.Rdata</p> </li> <li> <p>excitatory_neurons_WT6.Rdata</p> </li> <li> <p>inhibitory_neurons_AD12.Rdata</p> </li> <li> <p>inhibitory_neurons_AD6.Rdata</p> </li> <li> <p>inhibitory_neurons_WT12.Rdata</p> </li> <li> <p>inhibitory_neurons_WT6.Rdata</p> </li> </ul> <li> <p>pseudobulk/: includes pseudo bulk matrices for every cell type which were used for downstream analyses. Each matrix also includes metadata information on condition and time point.</p> </li> <ul> <li> <p>all_counts_ls.rds: List of all the pseudo bulk matrices (below).</p> </li> <li> <p>astrocytes.rds: pseudobulk matrix for astrocytes. Include time point and condition information for downstream analyses.</p> </li> <li> <p>endothelial_cells.rds: pseudobulk matrix for endothelial cells. Include time point and condition information for downstream analyses.</p> </li> <li> <p>ependymal_cells.rds: pseudobulk matrix for ependymal cells. Include time point and condition information for downstream analyses.</p> </li> <li> <p>excitatory_neurons.rds: pseudobulk matrix for excitatory neurons. Include time point and condition information for downstream analyses.</p> </li> <li> <p>fibroblasts.rds: pseudobulk matrix for fibroblasts. Include time point and condition information for downstream analyses.</p> </li> <li> <p>inhibitory_neurons.rds: pseudobulk matrix for inhibitory neurons. Include time point and condition information for downstream analyses.</p> </li> <li> <p>meningeal_cells.rds: pseudobulk matrix for meningeal cells. Include time point and condition information for downstream analyses.</p> </li> <li> <p>microglia.rds: pseudobulk matrix for microglia. Include time point and condition information for downstream analyses.</p> </li> <li> <p>oligodendrocytes.rds: pseudobulk matrix for oligodendrocytes. Include time point and condition information for downstream analyses.</p> </li> <li> <p>opcs.rds: pseudobulk matrix for oligodendrocyte progenitor cells. Include time point and condition information for downstream analyses.</p> </li> <li> <p>percicytes.rds: pseudobulk matrix for pericytes. Include time point and condition information for downstream analyses.</p> </li> <li> <p>rgcs.rds: pseudobulk matrix for retinal ganglion cells. Include time point and condition information for downstream analyses.</p> </li> </ul> <li> <p>pseudobulk_split/: Includes pseudo bulk count matrices split by time point and condition. Used for input to PANDA for gene regulatory network construction.</p> </li> <ul> <li> <p>excitatory_neurons_AD12.Rdata</p> </li> <li> <p>excitatory_neurons_AD6.Rdata</p> </li> <li> <p>excitatory_neurons_WT12.Rdata</p> </li> <li> <p>excitatory_neurons_WT6.Rdata</p> </li> <li> <p>inhibitory_neurons_AD12.Rdata</p> </li> <li> <p>inhibitory_neurons_AD6.Rdata</p> </li> <li> <p>inhibitory_neurons_WT12.Rdata</p> </li> <li> <p>inhibitory_neurons_WT6.Rdata</p> </li> </ul> <li> <p>seurat_preprocessing/</p> </li> <ul> <li> <p>filtered_seurat.rds : merged and filtered seurat object</p> </li> <li> <p>integrated_seurat.rds : seurat object integrated using harmony</p> </li> <li> <p>clustered_seurat.rds : clustered seurat object</p> </li> <li> <p>processed_seurat.rds : processed seurat object with final cell type assignments at specified resolution</p> </li> </ul> </ul> <p> </p> <p>Raw data publicly available on GEO under series accession: GSE261596</p>
Impaired cell-cell communication in multicellular cyanobacteria affects carbon uptake, photosynthesis and the cell wall
GEO Series GSE161085. Nostoc sp. PCC 7120 = FACHB-418. 24 samples. Type: Expression profiling by high throughput sequencing.
Molecular gatekeepers: how peptide maturation molecules coordinate cell-cell communication in Streptococcus pneumoniae
GEO Series GSE268602. Streptococcus pneumoniae. 8 samples. Type: Expression profiling by high throughput sequencing.
Cell type and stage specific transcriptional, chromatin and cell-cell communication landscapes in the mammary gland (ATAC-Seq).
GEO Series GSE222483. Mus musculus. 9 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Wound healing in aged skin exhibits systems-level alterations in cellular composition and cell-cell communication
GEO Series GSE188432. Mus musculus. 11 samples. Type: Expression profiling by high throughput sequencing.
Human stem cells with in vivo high plasticity generated by cell-cell communication
GEO Series GSE242346. Homo sapiens. 22 samples. Type: Expression profiling by high throughput sequencing.
Spatial transcriptomics Reveals Impact of APOE4 Allele on α-Synuclein Aggregation and Cell-Cell Communication in Lewy Body Dementia
GEO Series GSE293896. Homo sapiens. 10 samples. Type: Other.
Evaluation of altered cell-cell communication between glia and neurons in the hippocampus of 3xTg-AD mice at two time points
GEO Series GSE261596. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Comprehensive Profiling of Peripheral Blood Mononuclear Cells Reveals Monocyte-CD8+ T cell-B cell Communication as Central Cell-cell Interaction and pathogenesis in IgA Vasculitis
GEO Series GSE243002. Homo sapiens. 21 samples. Type: Expression profiling by high throughput sequencing; Other.
Pathogenic TSC2 variants alter developmental trajectories of human cortical organoids and perturb cell-cell communication networks [scRNA-seq]
GEO Series GSE247368. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
A single-cell RNA sequencing atlas of the COPD distal lung to predict cell-cell communication
GEO Series GSE269390. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Systematic identification of cell-cell communication networks in the developing brain
GEO Series GSE133079. Mus musculus. 35 samples. Type: Expression profiling by high throughput sequencing.
Single-cell RNA sequencing uncovers dynamic roadmap and cell-cell communication during buffalo spermatogenesis
GEO Series GSE190477. Bubalus bubalis. 2 samples. Type: Expression profiling by high throughput sequencing.
Single-Cell Profiling and Cell-Cell Communication Analysis of Splenic CD11c⁺ Cells in Wild-Type Mice
GEO Series GSE315452. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Pathogenic TSC2 variants alter developmental trajectories of human cortical organoids and perturb cell-cell communication networks
GEO Series GSE247369. Homo sapiens. 92 samples. Type: Expression profiling by high throughput sequencing.
Transcriptional analysis for cell-cell communication during graft union development in Arabidopsis
GEO Series GSE36447. Arabidopsis thaliana. 10 samples. Type: Expression profiling by array.
Cell type and stage specific transcriptional, chromatin and cell-cell communication landscapes in the mammary gland (RNA-Seq).
GEO Series GSE222484. Mus musculus. 18 samples. Type: Expression profiling by high throughput sequencing.
Androgen signaling in cell fate and cell-cell communication during early prostate development at single-cell resolution
GEO Series GSE153701. Mus musculus. 1 samples. Type: Expression profiling by high throughput sequencing.
Large-scale analysis of cell-cell communication reveals angiogenin-dependent tumor progression in clear cell renal cell carcinoma
GEO Series GSE222703. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
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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.