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111,247 results for “cells”
Sequence data for the article "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol" - Protocol optimization
<p>Sequence data (Illumina MiSeq runs) for the article "Whole transcriptome analysis of thousands of FACS-sorted single cells with the single cell nanoCAGE protocol". Optimization of the protocol. Files names indicate unique run identifiers. In the manuscript, the link between unique run identifiers, cells and purpose of the experiment is found in the Supplemental Table 1. </p>
Single-cell ATAC-seq control of cross-contaminations (experiment 2)
<p>On the Fluidigm C1 platform for single-cell analysis, the cells are captured in 96 chambers arranged serially, and then washed before further processing. Thus, debris present from the loading medium or released by captured cells upstream are a possible source of contamination. We generated a control datasets using the single-cell ATAC-seq protocol available from Fluidigm's ScriptHub. We cultivated human Hep G2 and mouse Hepa 1-6 (both are liver cancer cell lines), stained them with green and red calceins (respectively), and loaded them at equal concentration in a Fluidigm medium flow cell (old design), before running the C1 single-cell ATAC-seq program. To evaluate damage and carry-over of debris from FACS-sorting, two IFCs were run in two C1 machines in parallel. In the first (flowcell ID 1772-123-155), the cells not washed and in the second, they were washed (ID 1772-123-158).</p> <p>The data deposited here is a sequencing run (Illumina MiSeq) of these ATAC-seq libraries. The metadata indicating the contents of each well is being uploaded separately and this record will be updated once the DOIs are available.</p>
Single-cell ATAC-seq control of cross-contaminations (experiment 1)
<p>On the Fluidigm C1 platform for single-cell analysis, the cells are captured in 96 chambers arranged serially, and then washed before further processing. Thus, debris present from the loading medium or released by captured cells upstream are a possible source of contamination. We generated a control datasets using the single-cell ATAC-seq protocol available from Fluidigm's ScriptHub. We cultivated human Hep G2 and mouse Hepa 1-6 (both are liver cancer cell lines), stained them with green and red calceins (respectively), and loaded them at equal concentration in a Fluidigm medium flow cell (old design), before running the C1 single-cell ATAC-seq program.</p> <p>The data deposited here is a sequencing run (Illumina MiSeq) of these ATAC-seq libraries. The metadata indicating the contents of each well is being uploaded separately and this record will be updated once the DOIs are available.</p>
Figure 2. - Nesting architecture of Xylocopanasalis; Dissected nests of Xylocopanasalis revealing the nest structure inside the bamboo culm and its residents. Measurements of the nest parameters are shown in Table 1. The diameters of the nests (excluding the nest thickness) were measured at the nest entrance, followed by the vestibulum (antechamber) length, cell length, and the inner most cell length, respectively (2a). Cells containing larvae with pollen masses and their feces were collected and weighted (2b).
Figure 2. - Nesting architecture of Xylocopanasalis; Dissected nests of Xylocopanasalis revealing the nest structure inside the bamboo culm and its residents. Measurements of the nest parameters are shown in Table 1. The diameters of the nests (excluding the nest thickness) were measured at the nest entrance, followed by the vestibulum (antechamber) length, cell length, and the inner most cell length, respectively (2a). Cells containing larvae with pollen masses and their feces were collected and weighted (2b).
Mass spectrometry analysis of MSI2 interacting partners in K562 cells
<p>Mass spectrometry analysis of MSI2 interacting partners in K562 cells for manuscript "<strong>Functional screen of MSI2 interactors identifies an essential role for SYNCRIP in myeloid leukemia stem cells"</strong> by Vu et al. 2017. </p>
Genomic variant data for the Jurkat cell line
<p>Variant calling data from whole-genome sequencing of the Jurkat cell line. The data set includes output files from four variant calling tools (jurkat_raw_variant_caller_output.tar.gz), final variant calls after filtering and merging the calls from the separate tools (jurkat_final_variant_calls.tar.gz), and files with variant effect information (jurkat_variant_effects.tar.gz).</p>
Tuning CH3NH3Pb(I1-xBrx)3 Perovskite Oxygen Stability in Thin Films and Solar Cells
<p>The rapid development of organic-inorganic lead halide perovskites has resulted in high efficiency photovoltaic devices. However the susceptibility of these devices to degradation under environmental stress has so far hindered commercial development, requiring for example expensive device encapsulation. Herein, we have investigated the stability of CH3NH3Pb(I1-xBrx)3 [x = 0..1] thin film and solar cells under controlled humidity, light, and oxygen conditions. We show that higher bromide ratios increases tolerance to moisture, with x = 1 thin films being stable to 120 hr of moisture stress. Under light and dry air, partial bromide (x < 1) subsitution does not enhance film stability significantly, with the corresponding solar cells degrading within two hours. In contrast CH3NH3PbBr3 films show excellent stability, with device stability being limited by the organic interlayer. For these x = 1 films we show charge carriers are quenched in the presence of oxygen and form superoxide; however in contrast to perovskites containing iodide, this superoxide does not degrade the crystal. Our observations show that iodide limits the oxygen and light stability of CH3NH3Pb(I1-xBrx)3 perovskites, but that CH3NH3PbBr3 provides an opportunity to develop inherently stable high voltage photovoltaic devices and 4-terminal tandem solar cells.</p>
Whole-cell Escherichia coli lactate biosensor for monitoring mammalian cell cultures during biopharmaceutical production-- dataset
<p>Raw data for Goers et al, (2017), Biotech Bioeng. doi:10.1002/bit.26254.</p> <p>Each graph including the supplementary figures is a separate tab.</p>
Supplementary dataset for journal article "De novo MYC addiction as an adaptive response of cancer cells to CDK4/6 inhibition"
<p>Supplementary material for the journal article "De novo MYC addiction as an adaptive response of cancer cells to CDK4/6 inhibition".<br> 13C Metabolic flux analyses of CDK4/6 knockdown HCT116 cells and control HCT116 cells performed using INCA v1.5 (Young, J. D., 2014, INCA: a computational platform for isotopically non-stationary metabolic flux analysis. Bioinformatics 30, 1333-1335; http://mfa.vueinnovations.com.) running with MATLAB R2012b. The two files were generated by INCA with the estimated flux map distributions, network model, and tracer simulations.</p>
Transcriptional decomposition reveals active chromatin architectures and cell specific regulatory interactions
<p><strong>Summary</strong></p> <p>Resource data across the 76 cell types from FANTOM5 analysed in our paper titled "Transcriptional decomposition reveals active chromatin architectures and cell specific regulatory interactions".</p> <p><strong>Project abstract</strong></p> <p>Gene transcription is influenced by favourable chromosome positioning and chromatin architectures bringing regulatory elements in close proximity. However, it is unclear to what extent transcription is attributable to topological organisation or to gene-specific regulatory programs. Here, we develop a strategy to transcriptionally decompose expression data into two main components reflecting the positional relationship of neighbouring transcriptional units and effects independent from their positioning. </p> <p>We demonstrate that the positionally dependent component is highly informative of topological domain activity and organisation, revealing boundaries and chromatin compartments. Furthermore, features derived from transcriptional components can accurately predict individual chromatin interactions. We systematically investigate regulatory interactions and observe different transcriptional attributes governing long- and short-range interactions. Finally, we assess differences in regulatory organisations across 76 human cell types. In all, we demonstrate a close relationship between transcription and topological chromatin architecture and provide an unprecedented resource for investigations of regulatory organisations across cell types.</p> <p><strong>Included files</strong></p> <p>PD_component_76_cell_types.tar.gz - Contains the positionally dependent (PD) components for 76 human cell types.</p> <p>PD_sd_component_76_cell_types.tar.gz - Contains the standard deviations of the positionally dependent (PD_sd) components for 76 human cell types.</p> <p>PI_component_76_cell_types.tar.gz - Contains the positionally independent (PI) components for 76 human cell types.</p> <p>PI_sd_component_76_cell_types.tar.gz - Contains the standard deviations of the positionally independent (PI_sd) components for 76 human cell types.</p> <p>predicted_EP_interactions_76_cell_types.tar.gz - Contains predicted enhancer-promoter interactions for 76 human cell types.</p> <p>predicted_boundaries_76CT.txt - Matrix with 76 columns representing human cell types and 10kb genome-wide bins as rows, coded as 0 or 1 according to whether a XAD boundary was predicted in the bin for a given cell type.</p>
pH-Responsive, Lysine-Based, Hyperbranched Polymers Mimicking Endosomolytic Cell-Penetrating Peptides for Efficient Intracellular Delivery-DATA
<p>Original data and supporting data for the paper entitled "pH-Responsive, Lysine-Based, Hyperbranched Polymers Mimicking Endosomolytic Cell-Penetrating Peptides for Efficient Intracellular Delivery".</p>
Assessment of endothelial cell function and physiological microcirculatory reserve by video microscopy using a topical acetylcholine and nitroglycerin challenge - Individual subject data
<p>This dataset contains individual subject data for microcirculatory parameters assessed in the present study. Macrocirculatory parameters are not included at this time due to the present study being part of a larger, partially unpublished project.</p>
Combined single-cell quantitation of host and SIV genes and proteins ex vivo reveals host-pathogen interactions in individual cells
<p>Single cell gene expression data for the paper "Combined single-cell quantitation of host and SIV genes and proteins ex vivo reveals host-pathogen interactions in individual cells" to appear in PLOS Pathogens.</p> <p>Package contains two single cell data sets, one consisting of single cells from PBMCs in three animals, and the other three tissues from one animal.</p> <p>The single-cells are grouped based on the SIV viral genes that they express.</p> <p> </p>
Ionic Influences on Recombination in Perovskite Solar Cells
<p>Data for our paper: "Ionic Influences on Recombination in Perovskite Solar Cells" <strong>DOI: </strong>10.1021/acsenergylett.7b00490</p>
Pre-processed B cell receptor sequences from BioProject PRJNA349143
<p>Processed sequencing data from BioProject PRJNA349143.</p> <p><strong>Study Design</strong></p> <p>Samples were collected from human volunteers as described in Laserson and Vigneault et al, 2014 (1). Briefly, blood samples were collected from three individuals both pre- and post-vaccination for seasonal influenza. Samples were collected for sequencing at time points -8 days, -2 days, -1 hour, +1 hour, +1 day, +3 days, +7 days, +14 days, +21 days and +28 days relative to injection with seasonal influenza vaccine.</p> <p><strong>Library Preparation and Sequencing</strong></p> <p>The original samples from Laserson and Vigneault et al, 2014 (1) were re-sequenced as described in Gupta et al, 2017 (2). Briefly, sequencing libraries were prepared from mRNA using 5'RACE with addition of 17-nucleotide unique molecular identifiers (UMIs). Amplification was performed using constant region primers specific to IGHA, IGHD, IGHE, IGHG, IGHM, IGKC and IGLC. Sequencing was conducted on the Illumina MiSeq platform using the 600 cycle kit with 325 cycles for read 1 and 275 cycles for read 2. A 10% PhiX spike-in was added for sequencing.</p> <p><strong>Data Processing</strong></p> <p>Sequences were processed using the pRESTO (3) and Change-O (4) toolkits as described in Gupta et al, 2017 (2).</p> <p>Note, the provided data has been filtered significantly, including the removal of sequences that fail V(D)J alignment and the exclusion of non-functional sequences.</p> <p><strong>Format</strong></p> <p>Processed sequences are provided in FASTA format annotated using the pRESTO scheme.</p> <p>Annotations included are as follows:</p> <ul> <li><strong>CONSCOUNT:</strong> Raw read count from which UMI consensus sequences were generated, summed over all UMIs for the given unique sequence.</li> <li><strong>DUPCOUNT:</strong> UMI count for the given unique sequence.</li> <li><strong>PRCONS:</strong> Constant region primer (isotype).</li> <li><strong>SUBJECT:</strong> Subject identifier.</li> <li><strong>TIME_POINT:</strong> Time point label.</li> </ul> <p><strong>Citations</strong></p> <ol> <li>Laserson U and Vigneault F, et al. High-resolution antibody dynamics of vaccine-induced immune responses. Proc Natl Acad Sci USA 111, 4928-33 (2014).</li> <li>Gupta NT, et al. Hierarchical Clustering Can Identify B Cell Clones with High Confidence in Ig Repertoire Sequencing Data. J Immunol 1601850 (2017).</li> <li>Vander Heiden JA and Yaari G, et al. pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires. Bioinformatics 30, 1930–2 (2014).</li> <li>Gupta NT and Vander Heiden JA, et al. Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data. Bioinformatics 31, 3356–8 (2015).</li> </ol>
Analysis of lac operon induction with single cell resolution using the DIMM microfluidics chip and the MoMA software
<p>In this work, we demonstrate the power of the DIMM (Dual Input Mother Machine), a new microfluidics setup allowing long term environmental control and single cell resolution, and MoMA (Mother Machine Analyzer), its companion image analysis sofware.</p> <p>We study the induction of the <em>lac</em> operon in <em>Escherichia coli</em> MG1655 when nutrients alternate between glucose and lactose, using a translational fusion of LacZ with GFP integrated at the endogeneous locus.</p> <p>The dataset is made of two archives:</p> <ul> <li>DIMM_MoMA_images.tar.gz contains the image data produced in this study in a form ready to be used in MoMA</li> <li>DIMM_MoMA_data.tar.gz contains textual data files produced by MoMA and its postprocessing, with the cell identifier, length and fluorescence intensity of each cell in each frame.</li> </ul> <p>Detailed instructions are provided in the ReadMe.md file (NB: this is a text file using markdown syntax, you can open it in your favorite text editor).</p>
Iso-Seq ToFU2 experimental RC0 dataset 1 cell
<p>1 Sequel cell of RC0 (Lexogen SIRV + ERCC UHRR) Iso-Seq data for testing ToFU2.</p> <p> </p>
ROS-Specific Huntingtin Interactions: IP Optimization in Patient-Derived Cells
<p>Optimization step in the lead up to mass spec identification of ROS-specific huntingtin protein-protein interactions.</p>
Human bone marrow assessment by single-cell RNA sequencing
<p>Seurat objects and CyTOF data for <a href="https://doi.org/10.1172/jci.insight.124928">10.1172/jci.insight.124928</a></p> <p>Please run UpdateSeuratObject() after loading. Small object contains annotated metadata with cca and tsne analyses. Large object contains additional reductions (eg umap). </p>
Supplementary data for ENACT: End-to-End Analysis and Cell Type Annotation for Visium High Definition (HD) Slides
<p>This project contains the datasets used to evaluate and reproduce the results of ENACT (End-to-End Analysis and Cell Type<br>Annotation for Visium HD Slides). The dataset consists of:</p> <ul> <li>a sample Visium HD sample of human colorectal cancer, courtesy of 10X Genomics (<a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-libraries-of-human-crc">Visium HD Spatial Gene Expression Library, Human Colorectal Cancer (FFPE) - 10x Genomics</a>). All credit goes to 10X Genomics.</li> <li>configuration files to be used to reproduce the results provided in the ENACT publication, </li> <li>evaluation plots used in the ENACT publication, and</li> <li>results obtained after running ENACT on the human colorectal cancer sample using the four bin-to-cell assignment methods (naive, weighted_by_area, weighted_by_transcript, and weighted_by_cluster) and the three cell annotation methods (Sargent, CellAssign, CellTypist)</li> </ul> <p>Additionally, results from running ENACT on the following three public VisiumHD samples are provided to showcase ENACT’s tissue-agnostic nature:</p> <div> <div> <div> <ul> <li> <p><a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-human-lung-cancer-post-xenium-expt">Human Lung FFPE</a> sample from a subject with Adenocarcinoma (age and gender unspecified),</p> </li> <li> <p><a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-human-tonsil-fresh-frozen">Human Tonsil Fresh Frozen</a> sample from a 21 year old male subject with Reactive Follicular Hyperplasia,</p> </li> <li> <p><a href="https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-human-breast-cancer-fresh-frozen">Human Breast Fresh Frozen</a> sample from a 58 year old female subject with Ductal Carcinoma in Situ (DCIS).</p> </li> </ul> </div> </div> </div> <p> </p>
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.