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Dataset results
19 results for “CyTOF”
CyTOF data of PBMC samples of patients with metastatic pancreatic ductal adenocarcinoma
<p>These two CyTOF datasets are a part of the manuscript by M. Baretti "E<span>ntinostat in combination with nivolumab in metastatic pancreatic ductal adenocarcinoma: a phase 2 clinical trial" accepted in Nature Communications. The datasets contain FCS files of PBMCs samples of patients with metastatic pancreatic ductal adenocarcinoma treated with entinostat and nivolumab. PBMC samples were run with myeloid- and lymphoid-oriented panels.<br></span></p>
Cytomulate: accurate and efficient simulation of cytof data
<p>All six datasets and analysis code for reproducing the findings of "Cytomulate: accurate and efficient simulation of cytof data". The analysis code is also available at <a href="https://github.com/kevin931/cytomulate/releases/tag/benchmark.rev.1">https://github.com/kevin931/cytomulate/releases/tag/benchmark.rev.1</a>. The Cytomulate Python software can be found at <a href="https://github.com/kevin931/cytomulate">https://github.com/kevin931/cytomulate</a>. </p>
CyTOF and Flow Cytometry dataset assocaited with "Early-to-mid stage idiopathic Parkinson's disease shows enhanced cytotoxicity and differentiation in CD8 T-cells in females"
<p>This dataset contains all the raw mass cytometry (CyTOF) and flow cytometry fcs files associated with Capelle <i>et al</i>. '<i>Early-to-mid stage idiopathic Parkinson's disease shows enhanced cytotoxicity and differentiation in CD8 T-cells in females',</i> <i><strong>Nature Communications</strong>, <strong>2023</strong>,</i> In Press.</p><p>The dataset contains the following information:</p><p>1, The folder " CoPImmunoPD Flow Zenodo V2.zip " contains all the raw fcs files of flow cytometry analysis and the excel table with marker information of five staining panels in the initial discovery analysis using fresh blood samples. The folder also includes the fcs files of analyzing cytotoxicity potential within CD8 T cells and of validation analyses using cryopreserved samples. Single-color/fluorochrome staining files have also been provided for the relevant experiments in the given subfolders for compensation.</p><p>2, The folder "<a href="https://zenodo.org/api/files/75c910aa-3615-4eff-a201-9d2d46e33ea0/CoPImmunoPD_CyTOF_Zenodo.zip">CoPImmunoPD_CyTOF_Zenodo.zip</a>" contains all the raw fcs files generated from the CyTOF measurements in the initial discovery analysis.</p><p><strong>To reproduce our published Figures, please be assure to first read all the accompanied readme/excel information annotation files deposited in the corresponding folders within the zip files, all the Source Data files of different main and supplementary Figure subpanels, Methods and/or any other relevant sections in our manuscript.</strong></p>
Raw CyTOF images associated with Moldoveanu et al. 2022, Science Immunology
<p>This dataset contains the raw CyTOF images associated with the paper "An In-depth Map of the Melanoma Immune Microenvironment and Correlates of Immunotherapy Response by Imaging Mass Cytometry" (Moldoveanu et al. 2022). The MCD files output by CyTOF IMC were exported to one TIFF per channel per sample. This dataset contains one directory per sample (see Supplementary Table S1 for additional information). Each directory contains 46 TIFF images, which includes the 35 channels used in our study, 1 TIFF of the cell segmentation mask, and 10 TIFFs associated with background or unused channels.</p>
Mass Cytometry (CyTOF) FCS files from Priest et al. 2024. Human PBMC from longitudinal analysis of COVID-19, Bacterial Sepsis, mRNA vaccination cohorts.
<p>Mass Cytometry (CyTOF) FCS files from Priest et al. "Non-classical CD45RB<sup>lo</sup> memory B-cells are the majority of circulating antigen-specific B-cells following mRNA vaccination and COVID-19 infection." Research Square 2024. </p> <p>Files are already normalised, debarcoded, gated, batch corrected and compensated as described in Priest et al. </p> <p>Data is from Human PBMCs of londitudanal cohorts of Severe COVID-19, Sepsis and mRNA vaccine recipients. </p> <p>Samples were barcoded, mixed and then split magnetically before staining with seperate antibody panels for CD3+ (CD4, Treg, Tfh, CD8, gdT) or CD3- (B cells, DC, NK, Monocytes) to give approximatly 1280 FCS files from 218 individuals. </p> <p>A follow up experiment with a B-cell specific panel and Tetramers is included. </p> <p>Patient level metadata and antibody panel details are included. </p> <p> </p>
CyTOF test data for BinaryClust2
<p>PBMC samples from 11 Myeloproliferative neoplasms(MPN) patients were subject to a 36-marker panel and aquired by mass cytometry for immune surveillance, which represent a test dataset for BinaryClust2 pipeline(https://github.com/JingAnyaSun/BinaryClust2). </p> <p>Enclosed are raw data including fcs files after clean-up, sample metadata('metadata2.xlsx') and panel metadata('panel_metadata2'), and the defined R objects which comprises panel.RData, md.RData and MPN_sce.RData. </p>
Test dataset(CyTOF) for BinaryClust2
<p>Raw dataset are from Trussart et al. (Marie Trussart, Charis E Teh, Tania Tan, Lawrence Leong, Daniel HD Gray, Terence P Speed (2020) Removing unwanted variation with CytofRUV to integrate multiple CyTOF datasets eLife 9:e59630 https://doi.org/10.7554/eLife.59630), which was adopt here for testing the batch normalisation function of BinaryClust2. </p>
Healthy and B-cell precursor Acute Lymphoblastic Leukemia (ALL) cells analyzed via CyTOF
Open the record for dataset details and reuse information.
Data from: Subsets of tissue CD4 T cells display different susceptibilities to HIV infection and death: Analysis by CyTOF and single cell RNA-seq
Open the record for dataset details and reuse information.
CyTOF Dataset for Plerixafor and Cemiplimab in Metastatic PDAC
<p>This repository includes all relevant suspension mass cytometry files - all raw FCS files and two fully annotated datasets (<em>backup_output.rds</em> for myeloid cells and <em>backup_output.rds</em> for T cells) for single-cell analysis in "A phase 2 trial of CXCR4 antagonism and PD1 inhibition in metastatic pancreatic adenocarcinoma reveals recruitment of T cells but also immunosuppressive macrophages".</p> <p> </p> <p>R scripts and relevant configuration files used for the analysis of this dataset are available on <a href="github.com/wjhlab/J19113CyTOF">github.com/wjhlab/J19113CyTOF</a>.</p>
CyTOF datasets for tadalafil PDAC study (updated)
<p><strong>CyTOF datasets accompanying the tadalafil study in PDAC mouse models (Gross NE and Zhang Z et al.)</strong></p> <p> </p> <p><strong>Original version: </strong><br>CyTOF datasets accompanying Figures 2, 3, and Supplementary Figure 1<br>Each zip file contains an "output.rds" which contains all of the fcs files along with the associated R script</p> <p> </p> <p>The <strong>readme</strong> file describes the contents of the output RDS object in detail </p>
CyTOF
<p>Mass cytometry (CyTOF) was adopted for systematic and deep phenotyping of the lamina propria cells from the mice in the groups of SD (N=5), SD-OVA (N=5), and HAGE-OVA (N=5). </p>
CyTOF
<div> <p>Mass cytometry (CyTOF) was adopted for systematic and deep phenotyping of the mesenteric lymph nodes (MLN) cells from the mice in the groups of SD (N=4), SD-OVA (N=4), HAGE (N=4), and HAGE-OVA (N=3).</p> </div>
Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia: scRNA-seq and CyTOF processed datasets
<p><strong>This data was generated as part of the Tumor Profiler study. If you use it in your research, please cite:</strong></p> <p>Wegmann, R., Bonilla, X., Casanova, R. <em>et al.</em> Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia. <em>Nat Commun</em> 15, 9402 (2024). https://doi.org/10.1038/s41467-024-53535-4</p> <p><strong>Derived data - scRNA-seq</strong></p> <p>This is an R data set (.RDS) containing a SingleCellExperiment object with the following slots:</p> <div> <ul> <li>Assays: <ul> <li>counts: raw counts</li> </ul> </li> </ul> </div> <div> <ul> <li>colData: Cell-level metadata <ul> <li> barcodes: The cell barcode</li> <li> fractionMT: Fraction mitochondrial genes per cell</li> <li> n_umi: Total number of UMIs per cell</li> <li> n_gene: Total number of genes per cell</li> <li> log_umi: log10 total number of UMIs per cell</li> <li> g2m_score: Cell cycle phase score for G2M</li> <li>s_score: Cell cycle phase score for S</li> <li>cycle_phase: predicted cell cycle phase</li> <li>celltype_major_full_ct_name: Major cell type full name</li> <li>celltype_major: Major cell type short name</li> <li>celltype_final_full_ct_name: Cell subtype full name</li> <li>celltype_final: Cell subtype short name </li> <li>sample_id </li> </ul> </li> </ul> </div> <div> <ul> <li>rowData: Gene-level metadata <ul> <li>gene_ids</li> <li>gene_names</li> </ul> </li> </ul> </div> <p><strong>Derived data - CyTOF</strong></p> <p>This is an R data set (.RDS) containing a SingleCellExperiment object with the following slots:</p> <ul> <li>Assays:<br> <ul> <li>counts_raw: signal intensity based on CyTOF dual counts</li> <li>exprs_raw: arcsinh transformed raw counts (cofactor 5)</li> <li>counts: batch corrected raw counts (linear scaling based on a quantile)</li> <li>exprs: arcsin transformed counts (cofactor 5)</li> <li>scaled: 0-1 normalized exprs (clipped to the 99.95th percentile)</li> </ul> </li> <li>colData (cell metadata) <ul> <li>bc_id: barcode of the sample during staining </li> <li>run: CyTOF experiment batch, named after the first sample of the batch</li> <li>type: Sample type (blood or bone marrow)</li> <li>sample_id: TuPro sample ID</li> <li>pred_id: Predicted cell type [char]</li> <li>pred_n: Predicted cell type [integer]</li> </ul> </li> <li>rowData (marker metadata) <ul> <li>channel_name: Name and isotopic mass of the metal ion corresponding to this marker</li> <li>marker_name: Protein name</li> <li>channel_group, channel_group_integer: Biological processes the channel identifies, e.g. specific cell type, signalling, cell death</li> <li>tsne_channel: Logical - use this channel for dimensionality reduction?</li> <li>channel_order: Define the order of channels for plotting</li> <li>cluster_channel: Logical - use this channel for clustering?</li> </ul> </li> </ul>
Single-cell glycomics analysis by CyTOF-Lec reveals glycan features defining cells differentially susceptible to HIV
Open the record for dataset details and reuse information.
Optimization of Time-of-Flight Mass Cytometry (CyTOF) Analysis for Evaluation of Immune Changes Following Surgery
ClinicalTrials.gov study NCT01882569. IPD Sharing: Not stated. Countries: 1. Publications: 0.
CyTOF and flow cytometry fcs files from BMMCs of patients with myeloid neoplasms (AML, MDS, CMML)
<p>This dataset contains all the flow cytometry and mass cytometry (CyTOF - CD45+ immune cells) fcs files , associated with Tasis <em>et al</em>. Preprint doi: https://doi.org/10.1101/2023.12.30.23300608</p> <p> </p>
CyTOF datasets for tadalafil PDAC study
<p><strong>CyTOF datasets accompanying the tadalafil study in PDAC mouse models (Gross NE and Zhang Z et al.)</strong></p> <p> </p> <p><strong>Original version: </strong><br>CyTOF datasets accompanying Figures 2, 3, and Supplementary Figure 1<br>Each zip file contains an "output.rds" which contains all of the fcs files along with the associated R script</p> <p> </p> <p>The <strong>readme</strong> file describes the contents of the output RDS object in detail </p>
SYSTACT CyTOF dataset associated with Multiomics approaches disclose very-early molecular and cellular switches during insect-venom allergen-specific immunotherapy: an observational study
<p>This dataset contains all the raw mass cytometry (CyTOF) fcs files associated with Pogorelov et al. 'Multiomics approaches disclose very-early molecular and cellular switches during insect-venom allergen-specific immunotherapy: an observational study', <em>Nature Communications</em>, 2024, in Press. The dataset contains all the raw fcs files generated by CyTOF analysis of 199 time-series samples including ~200 million of deeply characterized immune cells, either from patients with insect-venom allergy or patients with pollen allergy following allergen-specific immunotherapy (AIT) or from healthy controls (HC), who did not receive any AIT or other immunotherapy. As specified in the manuscript, we sampled different individuals up to seven times (0h, 8h, 24h, Day 7, Week 2, Week 6 and Week 12) over a three-month period. All the samples from insect-venom allergy patients are stored in the zipper folder called "Venom" and all the samples from pollen allergy patients are in the zipper folder called "Pollen" while all the samples from HC are placed in the zipper folder called "Control". We also provide the following annotation files (metadata) to help the readers to better understand, validate and re-analyze our immunological dataset.</p> <p>1, In addition to the Supplementary Tables in our manuscript, we also attached one Word table file mapping the 36 specific metal isotypes and the specific Ab target markers.</p> <p>2, The Excel file with the list of 199 samples, showing the correct group and time point information (of note, the manually input sample information in the file name might be wrong for some samples). The correct time point information is in the column "Timepoint Detail" and "Timepoint Final".</p> <p>Associated with these raw fcs files, our processed results of all the CyTOF data are deposited in another webpage. Our large-scale interactive interlinked immunological Data resource (i3Dare) allows investigators to more effectively explore or reuse our immunological datasets of each immune subset from each participant at each time point (please refer to <a href="https://public.tableau.com/app/profile/lihpublicdata/viz/i3Dare_SYSTACT_Database/SYSTACTHome">https://public.tableau.com/app/profile/lihpublicdata/viz/i3Dare_SYSTACT_Database/SYSTACTHome</a>). OF note, to further protect privacy, the pseudoIDs within groups in i3Dare were re-labelled again. </p> <p><strong>Please read the accompanying information/metadata files, our main manuscript and Supplementary Information, our processed data on the i3Dare webpage and the published Source Data together with the raw fcs files in order to reproduce our published results.</strong></p>
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.