Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
41
datasets available to search
ShareScore release 0.9.0
Dataset results
41 results for “MERFISH”
MERFISH data of the developing mouse visual cortex under normal- and dark-rearing
<p>MERFISH data for the manuscript "Spatial profiling of the interplay between cell type- and vision-dependent transcriptomic programs in the visual cortex"</p>
Spatial organization of the mouse retina at single cell resolution by MERFISH
<p><strong>Abstract:</strong><br> <br> The visual signal processing in the retina requires the precise organization of diverse neuronal types working in concert. While single-cell omics studies have identified more than 120 different neuronal subtypes in the mouse retina1, little is known about their spatial organization. Here, we generated the first single-cell spatial atlas of the mouse retina using multiplexed error-robust fluorescence in situ hybridization (MERFISH). We profiled over 390,000 cells and identified all major cell types and nearly all subtypes through the integration with reference single-cell RNA sequencing (scRNA-seq) data. Our spatial atlas allowed simultaneous examination of nearly all cell subtypes in the retina, revealing 8 previously unknown displaced amacrine cell subtypes and establishing the first connection between the molecular classification of many cell subtypes and their spatial arrangement. Furthermore, we identified spatially dependent differential gene expression between subtypes, suggesting the possibility of functional tuning of neuronal types based on location.<br> <br> <strong>Data description:</strong><br> 1. VZA105a_integrated_368genes.h5ad<br> This file contains the raw MERFISH count matrix for four samples with 368 gene features. The "sampleid" column represents the unique sample ID, while the "region" column corresponds to the tissue section ID. The "majorclass" and "subclass" columns indicate annotated retinal cell types. Finally, the "center_x" and "center_y" columns provide the coordinates of the cell centers.</p> <p><br> 2. VA45_integrated.h5ad<br> This file contains the raw MERFISH count matrix for six samples with 500 gene features. The "sampleid" column represents the unique sample ID, while the "region" column corresponds to the tissue section ID. The "majorclass" and "subclass" columns indicate annotated retinal cell types. Finally, the "center_x" and "center_y" columns provide the coordinates of the cell centers.<br> <br> 3. merfish_impute.h5ad<br> This file contains the imputed count matrix for ten samples. The "sampleid" column represents the unique sample ID, while the "region" column corresponds to the tissue section ID. The "majorclass" and "subclass" columns indicate annotated retinal cell types. Finally, the "center_x" and "center_y" columns provide the coordinates of the cell centers.<br> </p>
MERFISH on developing thalamus
<p><span>The thalamus plays a central coordinating role in the brain. Thalamic neurons are organized into spatially-distinct nuclei, but the molecular architecture of thalamic development is poorly understood, especially in humans. To begin to delineate the molecular trajectories of cell fate specification and organization in the developing human thalamus, we used single-cell and multiplexed spatial transcriptomics. Here we show that molecularly-defined thalamic neurons differentiate in the second trimester of human development and that these neurons organize into spatially and molecularly distinct nuclei. We identify major subtypes of glutamatergic neuron subtypes that are differentially enriched in anatomically distinct nuclei. In addition, we identify six subtypes of GABAergic neurons that are shared and distinct across thalamic nuclei.</span></p>
Vizgen MERFISH files for Single-cell analysis reveals M. tuberculosis ESX-1-mediated accumulation of anti-inflammatory macrophages in infected mouse lungs
Open the record for dataset details and reuse information.
MERFISH on developing thalamus
Open the record for dataset details and reuse information.
MERFISH and snRNAseq analysis of healthy and disease human liver
<p>Single-cell RNA sequencing (scRNA-seq) has advanced our understanding of cell types and their heterogeneity within the human liver, but the spatial organization at single-cell resolution has not yet been described. Here we apply multiplexed error robust fluorescent in situ hybridization (MERFISH) to map the zonal distribution of hepatocytes, resolve subsets of macrophage and mesenchymal populations, and investigate the relationship between hepatocyte ploidy and gene expression within the healthy human liver. We next integrated spatial information from MERFISH with the more complete transcriptome produced by single- nucleus RNA sequencing (snRNA-seq), revealing zonally enriched receptor-ligand interactions. Finally, analysis of fibrotic liver samples identified two hepatocyte populations that are not restricted to zonal distribution and expand with injury. Together these spatial maps of the healthy and fibrotic liver provide a deeper understanding of the cellular and spatial remodeling that drives disease which, in turn, could provide new avenues for intervention and further study.</p>
MERFISH Dataset of Mouse Dopamine Neurons_03Jul2024
<p>Cell_by_gene and Cell_metadata files from MERFISH runs of mouse Midbrain spatial transcriptomics. Datasets are setup to be analyzed using Seurat v5.</p>
MERFISH measurements in the mouse ileum
<p>Spatial transcriptomics protocols based on in situ sequencing or multiplexed RNA fluorescent hybridization can reveal detailed tissue organization. However, distinguishing the boundaries of individual cells in such data is challenging, and can hamper downstream analysis. Current methods generally approximate cells positions using nuclei stains. We describe a segmentation method, Baysor, which optimizes 2D or 3D cell boundaries considering joint likelihood of transcriptional composition and cell morphology. While Baysor can take into account segmentation based on co-stains, it can also perform segmentation based on the detected transcripts alone. To evaluate performance, we extend MERFISH to incorporate immuno-staining of cell boundaries. Using this and other benchmarks we show that Baysor segmentation can in some cases nearly double the number of cells, while reducing segmentation artifacts. Importantly, we demonstrate that Baysor performs well on data acquired using five different protocols, making it a useful general tool for analysis of imaging-based spatial transcriptomics.</p>
MERFISH and snRNAseq analysis of healthy and disease human liver
Open the record for dataset details and reuse information.
MERFISH measurements in the mouse ileum
Open the record for dataset details and reuse information.
MERFISH+, a large-scale, multi-omics spatial technology resolves the transcriptomic holograms of the 3D human developing heart
Open the record for dataset details and reuse information.
Bacterial-MERFISH measurements of E. coli in various media and B. thetaiotaomicron in the mouse colon
Open the record for dataset details and reuse information.
MERFISH measurements of the mouse gastrointestinal tract in the presence and absence of the microbiome
Open the record for dataset details and reuse information.
Example Multiplexed Error-Robust Fluorescence In Situ Hybridization (MERFISH) data from the mouse colon
Open the record for dataset details and reuse information.
Spatial gene expression in the mouse colon during experimental colitis measured with MERFISH
Open the record for dataset details and reuse information.
MERFISH data from the murine hypothalamus in health and under induced sickness states
Open the record for dataset details and reuse information.
Processed MERFISH datasets for brain aging (coronal, sagittal) and rejuvenation (exercise, partial reprogramming)
<p>This repository contains several AnnData ".h5ad" objects containing the processed MERFISH data and metadata for the datasets generated in our study:</p> <blockquote> <p>"aging_coronal.h5ad" - the aging coronal section dataset</p> <p>"aging_sagittal.h5ad" - the aging sagittal section dataset</p> <p>"exercise.h5ad" - exercise dataset</p> <p>"reprogramming.h5ad" - partial reprogramming dataset</p> </blockquote> <p> </p> <p>Key metadata are saved as observation annotations in each object, and include:</p> <blockquote> <p>"mouse_id" - identifier for mouse from which the cell was derived</p> <p>"slide_id" - identifier for MERSCOPE slide</p> <p>"batch" - A and B denote different experimental batches for MERFISH</p> <p>"age" - mouse age in months</p> <p>"cohort" - experimental condition / group</p> <p>"celltype" - cell type annotation</p> <p>"region" - brain region annotation</p> <p>"subregion" - brain subregion annotation (will be more variabile/noisy than region)</p> </blockquote>
Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH
<p>Please contact Rongxin Fang (r3fang@fas.harvard.edu) for any question about the dataset.</p> <p>The human cerebral cortex has tremendous cellular diversity. How different cell types are organized in the human cortex and how cellular organization varies across species remain unclear. In this study, we performed spatially resolved single-cell profiling of 4000 genes using multiplexed error-robust fluorescence in situ hybridization (MERFISH), identified more than 100 transcriptionally distinct cell populations, and generated a molecularly defined and spatially resolved cell atlas of the human middle and superior temporal gyrus. We further explored cell-cell interactions arising from soma contact or proximity in a cell type–specific manner. Comparison of the human and mouse cortices showed conservation in the laminar organization of cells and divergence in somatic interactions across species. Our data revealed human-specific cell-cell proximity patterns and a marked increase in interaction enrichment between neurons and non-neuronal cells in the human cortex.</p>
MERFISH imaging of 10,050 genes in individual U-2 OS cells.
<p>(A) A high-pass-filtered, single-z slice, single-bit image of a U-2 OS sample stained with encoding probes targeting 10,050 RNA species, imprinting a 69-bit binary barcode onto each RNA species, and with an Alexa 750-labeled readout probe that detects 1 of the 69 bits of the barcodes. (Scale bar, 10 μm.) (B) A zoomed-in image of the region marked with the red box in A. (Scale bar, 1 μm.) (C) All identified RNA molecules (colored markers) detected from all 6 imaged z slices in the region depicted in A. (Scale bar, 10 μm.) (D) A zoomed-in image of all identified RNA molecules detected from all 6 imaged z slices in the region marked with the red box in C. (Scale bar, 1 μm.) In C and D, different colored dots mark RNA molecules with distinct barcodes. (E) The copy number per cell of RNA transcripts of each gene determined by MERFISH versus the fragments per kilobase of transcript per million mapped reads determined by bulk RNA sequencing for the 10,050 measured genes. The Pearson correlation coefficient is 0.83. (F) The copy number per cell detected in the 10,050-gene measurements vs. the copy number per cell in the 130-gene measurements for the 128 genes that are commonly present in both experiments. The median value of the ratios of the 10,050-gene measurements to the 130-gene measurements for each of the 128 common genes is 0.82. (G) Normalized histograms of the FPKM-normalized copy number per cell for the 9,050 genes that were labeled using the nonoverlapping encoding-probe design (blue) and for the 1,000 genes that were labeled using the overlapping encoding-probe design (orange). The medians of the FPKM-normalized copy number per cell for the 2 groups of genes are indicated by the blue and orange dotted lines, respectively.</p>
Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH
Open the record for dataset details and reuse information.
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.