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.
1,434
datasets available to search
ShareScore release 0.9.0
Dataset results
1,434 results for “subtypes”
Fig. 1 in Blastocystis occurrence and subtype diversity in wild European terrestrial mammals - The case of Białowieza˙Primeval Forest (NE Poland)
Fig. 1. Study area with localization and number of Blastocystis-positive and Blastocystis-negative animals of particular mammalian species.
Fig. 2 in Blastocystis occurrence and subtype diversity in wild European terrestrial mammals - The case of Białowieza˙Primeval Forest (NE Poland)
Fig. 2. Bayesian inference tree based on fragment of sequences obtained from the small subunit rRNA gene (SSU rDNA) of Blastocystis isolates of the present study, performed using MrBayes 3.2.7a. The Bayesian posterior probabilities are shown adjacent to branch nodes.
PCA involvement subtypes
<p>Involvement of the PCA (Posterior Cerebral Artery) i.e stenosis or occlusion is presented along the different segments of the artery.</p> <p>This involvement is seen in moyamoya patients.</p>
DeepHisto: Dataset for glioma subtype classification from Whole Slide Images
<p>DeepHisto dataset contains tiles (patches) of hematoxylin and eosin stained Whole Slide Images (WSI) of 28 adult-type diffuse glioma cases collected at the National Center of Pathology (NCP), Luxembourg National Health Laboratory (Laboratoire national de santé - LNS) from 2017 to 2021. WSIs were acquired with an IntelliSite Ultra Fast digital slide scanner from Philips containing a 20x/0.75 NA Plan Apo objective with an average slide resolution of 0.25um/pixel.</p> <p>Three primary diffuse glioma subtypes are classified into IDH-mutant, 1p/19q codeleted oligodendroglioma, IDH-mutant astrocytoma, and IDH-wildtype glioblastoma according to the 5th edition of the WHO classification of central nervous system tumors. The brain WSIs of a non-cancer patients were used as normal brain (white and gray matter) controls.</p> <p>Region annotation of WSIs was done by a board-certified pathologist, and the regions of interest are further divided into square 512×512 tiles, each of them associated with a particular class denoting the respective tumor entity, normal brain tissue or necrosis.<br> Tiles are further divided into training and test subsets patient-wise.</p>
Polygenic risk scores validated in patient-derived cells stratify for mitochondrial subtypes of Parkinson's disease
<p><strong>Background</strong> Parkinson’s disease (PD) is the fastest growing neurodegenerative disorder, with affected individuals expected to double during the next 20 years. This raises the urgent need to better understand the genetic architecture and downstream cellular alterations underlying PD pathogenesis, in order to identify more focused therapeutic targets. While only ∼10% of PD cases can be clearly attributed to monogenic causes, there is mounting evidence that additional genetic factors could play a role in idiopathic PD (iPD). In particular, common variants with low to moderate effect size in multiple genes regulating key neuroprotective activities may act as risk factors for PD. In light of the well-established involvement of mitochondrial dysfunction in PD, we hypothesized that a fraction of iPD cases may harbour a pathogenic combination of common variants in nuclear-encoded mitochondrial genes, ultimately resulting in neurodegeneration.</p> <p><strong>Methods</strong> to capture this mitochondria-related “missing heritability”, we leveraged on existing data from previous genome-wide association studies (GWAS) – i.e., the large PD GWAS from Nalls and colleagues. We then used computational approaches based on mitochondria-specific polygenic risk scores (mitoPRSs) for imputing the genotype data obtained from different iPD case-control datasets worldwide, including the Luxembourg Parkinson’s Study (412 iPD patients and 576 healthy controls) and the COURAGE-PD cohorts (7270 iPD cases and 6819 healthy controls).</p> <p><strong>Results</strong> applying this approach to gene sets controlling mitochondrial pathways potentially relevant for neurodegeneration in PD, we demonstrated that common variants in genes regulating <em>Oxidative Phosphorylation (OXPHOS</em>-PRS<em>)</em> were significantly associated with a higher PD risk both in the Luxembourg Parkinson’s Study (odds ratio, OR=1.31[1.14-1.50], <em>p</em>=5.4e-04) and in COURAGE-PD (OR=1.23[1.18-1.27], <em>p</em>=1.5e-29). Functional analyses in primary skin fibroblasts and in the corresponding induced pluripotent stem cells-derived neuronal progenitor cells from Luxembourg Parkinson’s Study iPD patients stratified according to the <em>OXPHOS</em>-PRS, revealed significant differences in mitochondrial respiration between high and low risk groups (<em>p</em> < 0.05). Finally, we also demonstrated that iPD patients with high <em>OXPHOS</em>-PRS have a significantly earlier age at disease onset compared to low-risk patients.</p> <p><strong>Conclusions</strong> our findings suggest that OXPHOS-PRS may represent a promising strategy to stratify iPD patients into pathogenic subgroups – in which the underlying neurodegeneration is due to a genetically defined mitochondrial burden – potentially eligible for future, more tailored mitochondrially targeted treatments.</p>
Prospects for a sequence-based taxonomy of influenza A virus subtypes
<p>This dataset comprises the multiple sequence alignments (*.fasta) and maximum likelihood phylogenies (Newick tree strings, *.nwk) for all available protein sequences corresponding to the eight genome segments of influenza A virus from the NCBI Genbank database. </p> <p>Each sequence is labelled with the Genbank accession number (e.g., "CY103884"), WHO strain identifier ("A/little yellow-shouldered bat/Guatemala/164/2009"), subtype label ("H17N10"), host species ("Sturnira lilium; gender M"), sampling location ("Guatemala: El Jobo"), and sample collection date ("May-2009"). These fields are separated by underscore characters.</p> <p>These data are provided under a Creative Commons license in support of a manuscript in progress, "Prospects for a sequence-based taxonomy of influenza A virus subtypes".</p>
Fig. 1 in Prevalence and molecular subtyping of Blastocystis sp. in rabbits in Henan, Central China
Fig. 1. Geographical distribution of infection with Blastocystis sp. in domestic rabbits in Henan, Central China. Infection rate expressed as prevalence.
Fig. 2 in Prevalence and molecular subtyping of Blastocystis sp. in rabbits in Henan, Central China
Fig. 2. Phylogenetic relationships among SSU rRNA gene sequences of Blastocystis sp. The phylogenetic tree shown was the constructed using the neighbor-joining method. Accession numbers for the sequences used are shown, followed by the common name of the host in English and the subtypes that the sequences belong to, only values above 50% are shown. The sequences obtained in this study are indicated by filled circles.
Epitranscriptomic subtyping, visualization, and denoising by global motif visualization
<p>The Analysis of large clusters with density histogram based approximate clustering. </p>
Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes - Supplementary Figure 4 representative histology images
<p>This includes the original full-size representative histology images presented in Supplementary Fig. 4 for the paper "Zhang*, Jonsson*, Nathan*, Millard*, et al, Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes, Nature, 2023<strong>"</strong>.</p> <p>Representative fragments from patients in each CTAP, showing composite and individual staining of each marker in the lymphocyte panel or stromal cell panel. A total of 150 fragments from 36 individuals (mean 4.2 fragments per individual, range 2-9 fragments per individual) were stained in batches and analyzed as a single cohort.</p>
Subtyping of common complex diseases and disorders by integrating heterogeneous data. Identifying clusters among women with lower urinary tract symptoms in the LURN study
Open the record for dataset details and reuse information.
Long-lasting, subtype-specific regulation of somatostatin interneurons during sensory learning
Open the record for dataset details and reuse information.
Conserved angio-immune subtypes of the cancer microenvironment predict response to immune checkpoint blockade therapy
Open the record for dataset details and reuse information.
Identification of an inhibitory neuron subtype, the L-stellate cells of the cochlear nucleus
<p>Auditory processing depends upon inhibitory signaling by interneurons, even at its earliest stages in the ventral cochlear nucleus (VCN). Remarkably, to date only a single subtype of inhibitory neuron has been documented in the VCN, a projection neuron termed the D-stellate cell. With the use of a transgenic mouse line, optical clearing and imaging techniques, combined with electrophysiological tools, we revealed a population of glycinergic cells in the VCN distinct from the D-stellate cell. These novel multipolar glycinergic cells were smaller in soma size and dendritic area, but over 10-fold more numerous than D-stellate cells. They were activated by auditory nerve fibers and T-stellate cells, and made local inhibitory synaptic contacts on principal cells of the VCN. Given their abundance, combined with their narrow dendritic fields and axonal projections, it is likely that these neurons, here termed L-stellate cells, play a significant role in frequency-specific processing of acoustic signals.</p>
AhR Gene Expression in Immune cell subtypes
<p>Benjamin J. Schmiedel, Divya Singh, Ariel Madrigal, Alan G. Valdovino-Gonzalez, Brandie M. White, Jose Zapardiel-Gonzalo, Brendan Ha, Gokmen Altay, Jason A. Greenbaum, Graham McVicker, Grégory Seumois, Anjana Rao, Mitchell Kronenberg, Bjoern Peters, Pandurangan Vijayanand,<br> Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression,<br> Cell,<br> Volume 175, Issue 6,<br> 2018,<br> Pages 1701-1715.e16,<br> ISSN 0092-8674,<br> https://doi.org/10.1016/j.cell.2018.10.022.<br> (http://www.sciencedirect.com/science/article/pii/S009286741831331X)</p> <p><br> Abstract: Summary<br> While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (database of immune cell expression, expression quantitative trait loci [eQTLs], and epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis (https://dice-database.org).<br> Keywords: DICE; immunology; GWAS; genetic variants; human immune cells; gene expression; eGenes; eQTLs; sex</p> <p>https://dice-database.org/genes/ahr#boxplot</p>
ImageStream Data of Blastocystis Subtypes
<p>Imaging Flow Cytometer data on <em>Blastocystis </em>isolates NUH9, WR1 and B.</p>
Prediction of mechanistic subtypes of Parkinson's using patient-derived stem cell models
<p>Data and pipelines used to predict mechanistic subtypes of Parkinson's disease using patient-derived stem cell model.</p> <p><strong>Lists of files included;</strong></p> <ul> <li>chemPredPD2022_Imaging process pipelines: pipelines to extract tabular data in Columbus Image Data Storage and Analysis System</li> <li>demo_data_images: a set of data for the Demo</li> <li>ImageData</li> <li>TabularData</li> <li>New test data_PINK1_isoCTRL</li> <li>New test data_SNCA_isoCTRL</li> <li>Tabular_demo_data</li> </ul>
Dataset related to manuscript: Rapid iPSC inclusionopathy models shed light on formation, consequence and molecular subtype of a-synuclein inclusions
<p>Key Resources Table and tabular data related to Lam, Ndayisaba et al 2024.</p> <p>Code for generating graphs can be found at: doi:10.5281/zenodo.12574231 (version 1), doi:10.5281/zenodo.12574230 (all versions)</p>
Improved production of HIV-1 subtype C protease from transgenic E coli
<p>The data set belongs to study carried out by Uraisha Ramlucken at Department of Biochemistry, University of KwaZulu-Natal, Durban, South Africa. This study was made possible through financial support from the National Research Foundation.</p>
Processed data for MethylBoostER: an XGBoost model to classify kidney cancer subtypes
<p>This is a repository containing processed data for MethylBoostER, an XGBoost model that classifies kidney cancer subtypes. The open-source code can be found here: https://github.com/ss-lab-cancerunit/MethylBoostER.</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.