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.
2,750
datasets available to search
ShareScore release 0.9.0
Dataset results
2,750 results for “scRNA seq”
Data Repository: Single-cell mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially expressed genes
<p>Data repository for the scMappR manuscript:</p> <p>Abstract from biorXiv (https://www.biorxiv.org/content/10.1101/2020.08.24.265298v1.full).</p> <p>RNA sequencing (RNA-seq) is widely used to identify differentially expressed genes (DEGs) and reveal biological mechanisms underlying complex biological processes. RNA-seq is often performed on heterogeneous samples and the resulting DEGs do not necessarily indicate the cell types where the differential expression occurred. While single-cell RNA-seq (scRNA-seq) methods solve this problem, technical and cost constraints currently limit its widespread use. Here we present single cell Mapper (scMappR), a method that assigns cell-type specificity scores to DEGs obtained from bulk RNA-seq by integrating cell-type expression data generated by scRNA-seq and existing deconvolution methods. After benchmarking scMappR using RNA-seq data obtained from sorted blood cells, we asked if scMappR could reveal known cell-type specific changes that occur during kidney regeneration. We found that scMappR appropriately assigned DEGs to cell-types involved in kidney regeneration, including a relatively small proportion of immune cells. While scMappR can work with any user supplied scRNA-seq data, we curated scRNA-seq expression matrices for ∼100 human and mouse tissues to facilitate its use with bulk RNA-seq data alone. Overall, scMappR is a user-friendly R package that complements traditional differential expression analysis available at CRAN.</p>
Supplementary information to "ScRNA-IMM: Single-cell RNA-Seq Imputation method using Mean/Median Imputation"
Open the record for dataset details and reuse information.
Sp 3dpf scRNA-Seq
<p>Identifying the molecular fingerprint of organismal cell types is key for understanding their function and evolution. Here, we use single cell RNA sequencing (scRNA-seq) to survey the cell types of the sea urchin early pluteus larva, representing an important developmental transition from non-feeding to feeding larva. We identify 21 distinct cell clusters, representing cells of the digestive, skeletal, immune, and nervous systems. Further subclustering of these reveal a highly detailed portrait of cell diversity across the larva, including the identification of neuronal cell types. We then validate important gene regulatory networks driving sea urchin development and reveal new domains of activity within the larval body. Focusing on neurons that co-express Pdx-1 and Brn1/2/4, we identify an unprecedented number of transcription factors shared by this population of neurons in sea urchin and vertebrate pancreatic cells. Using differential expression results from Pdx-1 knockdown experiments, we reconstruct the Pdx-1-driven gene regulatory network in these cells. We hypothesize that a similar network was active in an ancestral deuterostome cell type and then inherited by neuronal and pancreatic developmental lineages in sea urchins and vertebrates.</p>
Benchmark Gene Counts for scRNA-seq Analysis
<p>A gene counts file, containing a large list of R matrices with gene counts and cells saved in RDS format with genes as rows and cells as columns. Contains 48 datasets stored across various matrices types. This data set is adapted from the data used in</p> <p>Chen, X., Yang, Z., Chen, W. <em>et al.</em> A multi-center cross-platform single-cell RNA sequencing reference dataset. <em>Sci Data</em> <strong>8, </strong>39 (2021). https://doi.org/10.1038/s41597-021-00809-x</p> <p>The "mixed" cell datasets have been removed form this collection, leaving 48 of the original 72 datasets.</p>
scRNA-seq data for "Bacteroides fragilis toxin suppresses METTL3-Mediated m6A modification in macrophage to promote inflammatory bowel disease"
Open the record for dataset details and reuse information.
Supplement notebooks for "scBoolSeq: Linking scRNA-Seq Statistics and Boolean Dynamics"
<p>See https://github.com/bnediction/scBoolSeq-supplementary</p>
scRNA-seq dataset prefiltered from Paul et al. (2015), Cell
<p>Preprocessed dataset from Paul et al. (2015), Cell, to use for tradeSeq vignette.</p>
scPanel: A tool for automatic identification of sparse gene panels for generalizable patient classification using scRNA-seq datasets
<p>Dataset used to reproduce severe COVID-19 prediction results in scPanel manuscript.</p>
Joint profiling of cell morphology and gene expression during in vitro neurodevelopment (scRNA-seq data)
<p>Single cell RNA sequencing data: raw counts matrix and associated metadata including cell type annotations, and monocle3 cds object. </p>
Detection of HBV mRNA in a liver scRNA-seq data set
Open the record for dataset details and reuse information.
scRNA seq-raw data
Open the record for dataset details and reuse information.
Sp 3dpf scRNA-Seq
Open the record for dataset details and reuse information.
10x Lacrimal Gland scRNA seq data matrix
Open the record for dataset details and reuse information.
Flt3-ITD drives cooperating mutation-specific changes in cell identity and variable interferon dependence [scRNA-seq]
GEO Series GSE200556. Mus musculus. 16 samples. Type: Expression profiling by high throughput sequencing.
mouse RNA-seq, human RNA-seq, ATAC-seq, and scRNA-seq analyses data
GEO Series GSE224702. Homo sapiens; Mus musculus. 45 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Resolvin D1–mediated cellular crosstalk protects against MASH [scRNA-seq]
GEO Series GSE263770. Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.
Generation of transcriptional regulatory network of Lgr5+ small and large intestinal stem cells from mouse [scRNA-seq]
GEO Series GSE196915. Mus musculus. 1 samples. Type: Expression profiling by high throughput sequencing.
Multi-omics analysis identifies progenitors of CD4-CTLs [scRNA-seq in vitro]
GEO Series GSE288988. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Ketogenesis activates metabolically protective γδ T cells in visceral adipose tissue [scRNA-Seq]
GEO Series GSE137076. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
scRNA-seq, snATAC-seq, and spatial transcriptomics analysis of mammary glands of aged female mice
GEO Series GSE216542. Mus musculus. 22 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Other.
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.